JP6630061B2 - Method and apparatus for processing spread spectrum data - Google Patents

Description

  The present invention relates to a method of processing spread spectrum data and a processing apparatus related thereto, and more particularly to a method of measuring absorption characteristics in a scattering medium.

  The spectral detection method is pollution-free, does not destroy the sample, has a fast detection speed, can perform simultaneous quantitative analysis of multiple components, does not require the use of any reagent or test strip, and is continuous. In addition, it has advantages such as real-time monitoring, and is a truly non-invasive detection technology.

  In practical applications, the analyte to be measured is typically a complex sample that has not gone through a pre-treatment such as purification, for example a scattering medium such as milk, biological tissue or the like. These scattering media are characterized by strong scattering and high absorption in the near infrared band. Compared to a pure absorbing medium, the measured spectrum of the scattering medium contains two effects, scattering and absorption, in which case the Lambert-Beer law does not apply. Also, most of the light is scattered light under the influence of the strong scattering action of the particles in the scattering medium. The traveling path of these diffused photons is not fixed, but changes with changes in optical parameters such as absorption characteristics and scattering characteristics of the medium. Therefore, when a component of a substance in a scattering medium is detected by a spectral method, it is easily interfered by a change in an optical parameter of the medium itself. Difficult to reach.

  At present, measurement of a substance component in a scattering medium is successfully applied mainly when the concentration of the substance component is large and the absorption is strong. In this case, the absorption effect is considered to be the leading information, and a small change in the optical path due to the scattering effect is neglected. For example, the present invention is applied to measurement of blood oxygen saturation and measurement of hemoglobin based on a photoelectric pulse wave. Since hemoglobin is a major absorption component of blood, its concentration is high, and its absorption in the near infrared band is strong, it is approximately considered that the Lambert-Beer law can be applied when measuring a thin layer medium. However, in the case of hemoglobin, the detection accuracy is not yet high. For example, components having low contents of blood sugar, albumin and the like and low absorption do not have good detection accuracy and do not satisfy the requirements of the accuracy of practical application. Therefore, the detection of minute components of the scattering medium is a difficulty in the field of spectral detection.

  Therefore, in the spectral method, a measurement model must be constructed for a specific scattering medium. Hard to port between models. For example, if a measurement model built for one lot of milk is applied to the detection of another lot of milk, the error is always high. It is also difficult to borrow models between different scattering media. For example, models for milk cannot be successfully applied to the detection of constituents of living tissue.

  Two factors that limit the accuracy of the measurement and make it difficult for the model to be transplanted limit the application of the spectral method to the detection of components of scattering media. However, since spectral methods have the advantages of non-destructive, real-time, and online properties, there is a potential demand for applications in fields such as food safety detection, environmental safety detection, and non-invasive detection of biological tissue components. Have.

  Therefore, the present invention provides a spread spectrum data processing method that effectively separates at least optical information due to a change in scattering action and optical information due to a change in absorption action, and performs prediction using these separated information. It is an object of the present invention to provide a method for constructing a model, estimating a concentration of detected components in a scattering medium, and a corresponding processing apparatus.

Accordingly, a first object of the present invention, near-is, the first method is to provide a spread spectrum data processing method obtains the spread spectrum data in one or more first radial position of the medium to be measured Then, based on the acquired spread spectrum data, optical information and / or absorption of the measured medium at one or more second radial positions substantially due to only a change in the scattering characteristics of the measured medium. The purpose is to determine optical information based only on a change in characteristics .

A second object of the present invention is to provide a method for constructing a prediction model. The second method provides a series of media to be measured each comprising a background or reference medium and different known concentrations of a particular component added to the background or reference medium, wherein the reference medium is a background medium and an initial medium. The series of media to be measured, containing a concentration of the particular component, is processed according to the first method, and the optical information and / or each known concentration and corresponding substantially only changes in the absorption characteristics of the media to be measured. Alternatively, it is to obtain a prediction model based on optical information substantially based only on a change in the scattering characteristic of the medium to be measured.

A third object of the present invention, Ri near to provide a method for predicting the concentration, the method of the third, to the measuring medium, for processing by the third method. The medium to be measured includes a background medium or a reference medium, and the reference medium includes a background medium and a specific component of an initial concentration. When the concentration of the specific component in the medium to be measured becomes unknown due to a change in the concentration of the specific component, the medium to be measured is Based on at least one of the optical information substantially due to only the change in the absorption characteristic of the medium to be measured and the optical information substantially due to only the change in the scattering characteristic of the medium to be measured, and the prediction model acquired as described above. Thus, it is to predict the concentration of the specific component.

A fourth object of the present invention, Ri near to provide a method for predicting the concentration, the method of the fourth, the pure absorption background medium, and certain different known concentrations to be added to the pure absorption background medium Provide a series of media each containing the component, obtain the corresponding absorption coefficient or absorbance, obtain a predictive model based on each known concentration and the corresponding absorption coefficient or absorbance, and scatter the Obtain the diffuse spectrum data at the non-sensitive point, the medium to be measured includes a scattering background medium or a reference medium, and the reference medium includes the scattering background medium and a specific component of the initial concentration. When the concentration of the specific component in the medium becomes unknown, the concentration of the specific component is determined based on the diffusion spectrum data and the prediction model at the scattering insensitive point obtained for the measured medium. It is to measure. The scattering insensitive point indicates a radial position at which the luminous intensity information in the spectrum data is insensitive to a change in the scattering characteristic of the medium to be measured.

A fifth object of the present invention, Ri near to provide a processing apparatus, the processing apparatus includes a detector to detect the spectrum of the medium to be measured, the detection of the detector, in one or more radial positions provided by including a processor which is substantially arranged to determine the optical information only by changes in the absorption properties of the optical information and / or substantially the medium to be measured due to changes only in the scattering characteristics of the medium to be measured, the It is in.

  Therefore, the present invention focuses on the fact that optical information based on a change in scattering characteristics and optical information based on a change in absorption characteristics can be separated, and an attempt is made to realize high prediction accuracy using such information. In particular, it is an object of the present invention to be able to extract essentially pure absorption information and to be able to apply it effectively to measuring the concentration of a substance component.

A first aspect of the present invention is to acquire spread spectrum data at one or a plurality of first radial (radial) positions of a medium to be measured,
Based on the acquired spread spectrum data, at one or more second radial positions, optical information and / or substantially the absorption characteristics of the measured medium is substantially due to only the change in the scattering characteristics of the measured medium. change Ru spread spectrum data processing method der by determining the optical information by only. In the present invention, the spread spectrum data is obtained by obtaining spread spectrum data at at least two radial positions, and by using a linear fitting method , the spread spectrum data at the one or more first radial positions is obtained. A method of processing spread spectrum data including determining.
Here, the at least two radial positions include an integrated variation reference point, and the integrated variation reference point is a radial position in which the luminous intensity information in the spectral data is substantially insensitive to a change in the concentration of a specific component in the medium to be measured. position shows the. Wherein the step of determining the optical information, including that determined in accordance with the scattering insensitive point and / or absorption insensitive point.
The scattering insensitive point shows the radial position where the luminous intensity information in the spectral data is not substantially sensitive to changes in scattering characteristics of the medium to be measured.
The absorption insensitive point indicates a radial position at which the luminous intensity information in the spectrum data is substantially insensitive to a change in the absorption characteristic of the medium to be measured.
In the present invention, the medium to be measured includes a background medium and a specific component in the background medium, and a scattering medium including the background medium or the background medium and a specific concentration of the specific component is provided . In the present invention, the change information of the luminous intensity when the scattering coefficient / absorption coefficient of the scattering medium changes and the absorption characteristics / scattering characteristics of the scattering medium at the first wavelength do not basically change is acquired . The operation of acquiring the scattering insensitive point / absorption insensitive point according to the radial position at the point where the change in luminous intensity is substantially zero allows the scattering insensitive point / absorption insensitive point at the first wavelength to be obtained. further including that obtained in advance. Here, the absorption insensitive point is preferably approximated to a position where the radial position is zero. Further, it is preferable to acquire a scattering insensitive point and / or an absorption insensitive point at each wavelength for a plurality of wavelengths.
In addition, the determining step includes acquiring diffusion spectrum data at a scattering non-sensitivity point and / or an absorption non-sensitivity point, and substantially acquiring the diffusion spectrum data at the scattering non-sensitivity point and the absorption non-sensitivity point. obtaining optical information due to the change only in the absorption characteristics of the measuring medium, and / or in accordance with the spread spectrum data and scattering insensitive point in the absorption insensitive point, optical only by changes in the scattering properties of substantially medium to be measured including an acquisition child the information, the.
Further, (1) the step of acquiring spread spectrum data includes:
Selecting a second wavelength that is close to the first wavelength and has relatively weak or essentially no absorption of a specific component contained in the medium to be measured;
Including the obtaining the spread spectrum data of the first and second wavelengths respectively, the.
The method comprises:
The scattering insensitive point at the second wavelength is determined according to the radial position at the point where the change in luminous intensity indicated by the spread spectrum data at the second wavelength is substantially zero .
The method further includes determining the scattering insensitive point at the first wavelength by an operation of determining the scattering insensitive point at the first wavelength in response to the scattering insensitive point at the second wavelength.
In addition, the step of acquiring spread spectrum data includes:
Selecting a second wavelength that is close to the first wavelength and has relatively weak or essentially no absorption of a specific component contained in the medium to be measured;
Including the obtaining the spread spectrum data of the first and second wavelengths respectively, the.
(2) The step of determining the optical information includes:
Based on the spread spectrum data of the second wavelength, determining optical information substantially only by a change in the scattering characteristic of the measured medium at the first wavelength of the measured medium;
A first wavelength of the medium to be measured according to the spread spectrum data at the first wavelength and optical information substantially due to only a change in the scattering characteristic of the medium to be measured at the first wavelength of the medium to be measured; And acquiring optical information substantially only due to a change in the absorption characteristic of the medium to be measured.
Further, (3) the step of acquiring spread spectrum data includes:
Including to obtain a spread spectrum data in the scattering insensitive point and / or absorption insensitive point.
(4) The step of determining the optical information includes:
Determining the spread spectrum data at the scattering insensitive point as optical information substantially due to only the change in the absorption characteristic of the medium to be measured at the scattering insensitive point; And determining as optical information substantially only due to a change in the scattering characteristic of the medium to be measured.
Still further, (5) the step of acquiring spread spectrum data includes:
Acquiring spread spectrum data at a scattering insensitive point and / or an absorption insensitive point at each of the plurality of wavelengths.
Thus, for each of said plurality of wavelengths, spread spectrum data is acquired at at least one fixed radial position, whereby a scattering insensitive point and / or an absorption insensitive at each of said plurality of wavelengths. Spread spectrum data at the point can be determined.

A second aspect of the present invention provides a series of media to be measured each comprising a background medium or reference medium, and different known concentrations of specific components added to the background medium or reference medium, wherein the reference medium is a background medium and an initial concentration. In the case of including the specific component of, the spread spectrum data processing method is applied to the series of measured media,
Obtaining a predictive model based on optical information due to each known concentration and correspondingly substantially only due to a change in the absorption characteristics of the measured medium and / or optical information substantially due to only a change in the scattering characteristics of the measured medium. And a method for constructing a prediction model including the following.
In the present invention, the optical information represents a linear rule,
Obtaining the prediction model includes obtaining a prediction model based on the inclination of the optical information. In addition, the medium to be measured is processed by the above-mentioned spread spectrum data processing method, the medium to be measured includes a background medium or a reference medium, the reference medium includes a background medium and a specific component of an initial concentration, and a concentration change of the specific component. Due to this, the concentration of the specific component in the medium to be measured becomes unknown, and the optical information about the medium to be measured is substantially due to only the change in the absorption characteristic of the medium to be measured and the optical information due to substantially only the change in the scattering characteristic of the medium to be measured The present invention also provides a concentration prediction method including predicting the concentration of the specific component based on at least one of the information and the prediction model. This is a concentration prediction method for performing modeling and prediction according to information. In this method, the spread spectrum data used for modeling and prediction includes luminous intensity, absolute change in luminous intensity, relative change in luminous intensity, absorption coefficient, absolute change in absorption coefficient, and relative change in absorption coefficient. Alternatively, the background medium or the reference medium for acquiring the prediction model, which includes at least one of the related amounts, is preferably different from the background medium or the reference medium of the measured medium waiting for the prediction. Further, when the unknown concentration is predicted by a prediction model, it is preferable to perform a pre-process on the spread spectrum data based on a ratio of an absorption coefficient between two background media or reference media. Accordingly, modeling and prediction can be performed in accordance with optical information substantially due to only a change in the scattering characteristic of the medium to be measured.
Further, in the present method, the spread spectrum data used for modeling and prediction includes luminous intensity, absolute change in luminous intensity, relative change in luminous intensity, scattering coefficient, absolute change in scattering coefficient, and relative change in scattering coefficient. Or a background medium or a reference medium for obtaining the prediction model, which contains at least one of the related amounts, is preferably different from the background medium or the reference medium in the measured medium waiting for prediction, and When estimating the density of the spread spectrum data, it is preferable to perform pre-processing on the spread spectrum data according to the ratio of the scattering coefficient between two background media or reference media. Here, to predict the concentration, for the interference component other than the specific component, to obtain a scattering signal at the time of the unit density change amount, and by the spectral data at the scattering insensitive point of the measured medium Predicting the concentration of the interference component based on the prediction model of the interference component, multiplying the concentration of the interference component by the scatter signal of the unit density change amount to obtain the scatter signal of the interference component in the medium to be measured, The method includes removing the scattered signal of the interference component from the spectrum data of the measurement medium, and predicting the concentration of the specific component from the spectrum data from which the scattered signal of the interference component has been removed.
Also, providing a pure absorption background medium, and a series of media each containing a different known concentration of a specific component added to the pure absorption background medium, to obtain a corresponding absorption coefficient or absorbance;
Obtaining a prediction model based on each known concentration and the corresponding absorption coefficient or absorbance;
For the measured medium, obtain the diffuse spectrum data at the scattering insensitive point, the measured medium includes a scattering background medium or a reference medium, the reference medium includes the scattering background medium and a specific component of the initial concentration, and the specific component By the change in the concentration, the concentration of the specific component in the medium to be measured becomes unknown,
Predicting the concentration of the specific component based on the diffusion spectrum data and the prediction model at the scattering insensitive point obtained for the measured medium,
The scattering insensitive point is a density value in a method of predicting a radial position at which the luminous intensity information in the spectrum data is insensitive to a change in the scattering characteristic of the medium to be measured, and an absorption coefficient when the concentration of the specific component is 0. Alternatively, a prediction model can be obtained based on an absorption coefficient or a relative change in absorbance at a concentration corresponding to the absorbance. Therefore, the diffuse spectrum data includes at least one of luminosity, luminosity change, luminosity relative change, absorption coefficient, absolute change in absorption coefficient, relative change in absorption coefficient or a related amount thereof,
When the concentration is predicted using the prediction model, it is preferable to perform pre-processing on the spread spectrum data based on the ratio of the absorption coefficient between the scattering background medium and the pure absorption background medium.

The present invention also applies the above-mentioned diffuse reflection spectrum data processing method, at least in part, to provide a more universal spectrum measurement method.Specifically, the present invention uses a probe light Irradiating the measured medium containing a specific component, to obtain first spectral data at a first radial position and second spectral data at a second radial position of the measured medium, the first And the second radial position are arbitrarily selected, and a difference processing is performed on the first spectral data and the second spectral data.
Further, the present invention provides a first optical fiber bundle for guiding incident light, wherein the output end face is substantially at the center of the detection end face of the optical fiber probe, and the second optical fiber bundle. And a third optical fiber bundle, wherein at the detection end surface, the end surface of the optical fiber in the second optical fiber bundle and the end surface of the optical fiber in the third optical fiber bundle are respectively the first optical fiber bundle. An optical fiber probe is provided that is at a different distance from the exit end face.
Further, the present invention provides a series of media to be measured, each containing a background medium or reference medium, and a different known concentration of a particular component contained in the background medium or reference medium, wherein the reference medium is a background medium and an initial concentration of the specific components. Including a specific component, processing the series of measured media in accordance with the above method, and obtaining a prediction model based on each known concentration and corresponding processed spectral data, Provide a method for constructing a predictive model, including:
Still further, the present invention provides a method for processing a medium to be measured including a background medium or a reference medium according to the above method, wherein the reference medium includes a background medium and a specific component of an initial concentration, and the medium to be measured is determined by a change in the concentration of a characteristic component. In which the concentration of the specific component becomes unknown and predicting the concentration of the specific component based on the processed spectral data and the prediction model for the medium to be measured. .
Lastly, the present invention provides a probe for detecting spectral data of diffuse reflection and / or diffuse scattered light with respect to a probe light of a medium to be measured containing a specific component, and a probe arbitrarily selected using the probe. Provided is a processing device that includes a processor that detects spectral data at one radial position and a second radial position and performs a difference process on the spectral data.
According to the present invention, there is no need to determine the floating reference position, and a simpler measurement method can be provided.

The specific background where it is desired to provide the spectrum detection method of the present invention is as follows. The spectrum detection method is pollution-free, does not destroy the sample, has a fast detection speed, can perform simultaneous quantitative analysis of multiple components, does not require any reagents or test papers, and can be used continuously. It has the advantages of real-time monitoring and is a truly non-invasive detection technology. In the field of biochemistry, the adoption of the near-infrared absorption spectrum method has already successfully accomplished the rapid and non-invasive detection of biochemical indicators such as blood oxygen saturation in living tissues. External spectroscopy has been recognized as one of the most invasive techniques for non-invasive detection of chemical components in the human body.
When detecting the component concentration of the analyte using the spectral method, the analyte to be measured, usually, does not go through pre-processing such as purification, is a complex sample, or a certain analyte in the human body is there. When the change in the concentration of the component to be measured has a clear wavelength characteristic, a calibration model is constructed by using the multivariate regression method, and the concentration of the component to be measured can be measured. However, complex samples and individuals contain many unpredictable interference components, except for the components to be measured.For example, changes in the concentration of certain components in the human body are affected by changes in the human body temperature, feelings, etc., and the wavelength characteristics are evident. is not. Therefore, it is necessary to remove the influence of these unpredictable backgrounds on the concentration analysis of the object to be measured and then perform the concentration measurement analysis again. Near-infrared spectral analysis requires that the calibration sample set used to build the mathematical model should include various backgrounds of the sample under test.
Taking the non-invasive blood glucose concentration detection as an example, the signal due to the blood glucose change is very faint because the blood glucose content in human body tissue is small and changes within the physiological range are very small. On the other hand, the optical properties of the tissue itself are also very complicated, and when light passes through dynamically changing human tissue, apart from the absorption of some light, the presence of nonlinear scattering also extracts sugar signals. It becomes very difficult. Near-infrared regions such as water, fat, and protein in the tissue may all absorb, and the signal intensity due to these interference factors is higher than the light intensity due to the change in glucose concentration. Then, since the same radical can cause absorption peaks in different frequency regions in this spectral region, a complex sample or individual is likely to have spectral peaks of different molecules and multiple types of radicals in the same near-infrared spectral region. Overlap well. In addition to this, factors such as metabolism of the living body, physiological cycle, mood unevenness and environmental effects all directly or indirectly affect the content of various substance components in human body tissues and are effectively measured. Unable to extract blood glucose concentration information in the sample. Due to the many and complex elements involved in these issues, it is difficult to monitor changes in these elements in real time at the current scientific research level. Therefore, the method of obtaining one type of reference measurement is also a feasible route to solve the above problem. Human blood oxygen saturation measurement is a typical example of taking relative measurements and obtaining success.
In vitro experiments generally employ a method called dual optical reference measurement and adjacent background subtraction to remove common mode interference due to instrument drift, i.e., the background of a reference sample whose spectral properties are close to the DUT. The difference operation is performed by measuring the spectrum. Experimental results show that this method can effectively remove the effects of common mode changes in the measurements.
However, in some applications, for example, measurement of the blood glucose concentration of a human body, it is difficult to realize a reference measurement by obtaining a reference material including background variation information of the measurement object because the optical property is the same as that of the measurement object. In the clinical practice of near-infrared non-invasive blood glucose detection, it is difficult to find a reference whose optical properties resemble that of the human body, and it is difficult for a part of the human body to be free of glucose or to be fixed without changing the glucose concentration. As such, spectral processing methods that subtract background references that can be employed in such in vitro experiments are not yet directly applicable to biological detection. Introducing a standard reflector or mimic in the measurement system as a background reference whose order of reflectance is close to the diffuse reflectance of the human skin will remove some hardware system reference signal effects, And the light propagation method in the imitator is different from the skin of the human body, so the human body does not show its own metabolism, menstrual cycle, mood unevenness and environmental effects in the spectrum of reflectors and mimics, No change signal is available, which is also currently the biggest obstacle to extracting blood glucose levels in the human body using near-infrared spectral methods.
Therefore, when using the near-infrared spectrum method to detect the concentration of a certain component of human body tissue, the practical measurement process is to extract faint concentration change specific information from a complicated overlapping background. The process of extracting useful information can be limited and affected by various physiological factors of the human body.
Therefore, Xu Xin et al. Invented a principle and a method for realizing concentration measurement using a floating reference position (Chinese patent application, publication number CN1699973A), and as shown in FIG. 1, information contained in the measurement spectrum itself. Among them, a reference standard that can be used as a “background” was required. When a concentration of a component, for example, glucose, in an object to be measured, for example, a human body, changes, an optical characteristic such as an absorption coefficient and a scattering coefficient of the object to be measured changes. A predetermined radially directed position r _k away from the light source, the diffuse reflection light energy was changed by absorption and scattering effects in the tissue can be offset essentially each other, varies essentially with a change in glucose concentration it does not have, call this position r _k and the floating reference position. The light energy obtained at this location reflects the removal of the effects of all fundamental interfering factors other than glucose concentration changes during detection. Therefore, the spectrum at this position can be used as a “background” in the process of noninvasive detection of blood glucose in the human body to extract glucose specificity information, which is similar to the reference measurement in an in vitro experiment. The existence characteristics of the position floating reference have been verified by Monte Carlo simulation and in vitro experiments. However, since the change in light energy due to the change in blood glucose concentration is related to the optical characteristics of human body tissue, this reference criterion as "background" is used for different DUTs, different positions of the same DUT, and different probe light wavelengths. Are different, that is, the positions of the floating reference positions are different.
In the Monte Carlo simulation calculation, the skin of the palm was selected as the target tissue layer for measuring the blood glucose concentration of the human body, and the three-dimensional skin model was measured, that is, the skin was divided into the epidermis, dermis, and subcutaneous tissue. Separate. The number of photons of which is provided on a Monte Carlo simulation program is 10 ^9. Based on each layer optical parameters given by Maruo et al. (Maruo K., Tsurugi M., Chin J., et al., Noninvasive blood glucose assay using a newly developed near-infrared system, IEEE Journal of Selected Topics in Quantum Electronics , 2003.9 (2): p. 322-330; Maruo K., Oota T., Tsurugi M., et al., New methodology to obtain a calibration model for noninvasive near-infrared blood glucose monitoring, Applied Spectroscopy, 2006. 60 (4): p. 441-449), when the glucose concentration increases from 0 to 500, 1000 and 1500 mg / dL respectively, the optical parameters of the dermis of the skin model also change correspondingly, Optical parameters do not change. When the epidermis, dermis, and subcutaneous tissue of the three-dimensional skin model are set to 0.5 mm, 3.5 mm, and ∞, respectively, a typical diffuse reflection spectrum in which a detector is radially distributed from a light source at a wavelength of 1200 to 1700 nm. As shown in FIG. 2, the distribution becomes close to a negative exponential distribution, and the diffuse reflection light intensity rapidly decreases as the radial distance increases. The diffuse reflection light intensity after 2.0 mm is weak and decreases from the order of 10 ⁻¹ to 10 ⁻⁸ .
The radial distributions obtained by subtracting the diffuse reflection light intensity of 0 mg / dL from the obtained diffuse reflection light intensity of different glucose concentrations have wavelengths of 1200 nm, 1300 nm, 1400 nm and 1,400 nm, respectively, as shown in FIGS. It corresponds to the control diagram at each wavelength. For the same skin layer thickness, it is considered that there is one radial position where the diffuse reflection light intensity is not sensitive to a change in glucose concentration at different wavelengths at the same measured position of the same measured object. , This position is the floating reference position. However, as can be seen from the figure, this floating reference position has a clear wavelength characteristic, and the position floating reference position changes gradually from 1200 nm to 1300 nm. Hardly changes. At 1300 nm to 1400 nm, the fluctuation of the reference position is large, and the reference position tends to approach the light source. When the wavelength is larger than 1400 nm, the floating reference position does not exist.
Even at the same wavelength, there is a difference in the tissue components of different measurement objects, and the same measurement objects are not all the same at different times, that is, the tissue components are not the same. With the normal human blood glucose concentration (100 mg / dL) as the model environment, the absorption coefficient μ _a and the scattering coefficient μ _s of the dermis layer were changed at a wavelength of, and each of them was changed at a gradient of 20%. As shown in (3), a distribution map is obtained in which the floating reference position in the three-dimensional skin model changes according to the dermis layer optical characteristics. As can be seen from the figure, different measurement objects or the same measurement object have different scattering specificities of skin tissue at different time zones, which significantly affects the positioning of the floating reference position.
Similarly, the skin physiological structure and tissue thickness are not the same for different measurement targets or different physiological sites of the same measurement target, and the floating reference position changes correspondingly at the same wavelength. Similar to the simulation described above, at a wavelength of 1300 nm, a normal human blood glucose concentration (100 mg / dL) is used as a model environment, and the epidermis thickness becomes 0 according to a typical value of the palm skin thickness. When the dermis thickness changes to a range of 2.0 to 4.0 mm and the dermis thickness changes to a range of 2.0 to 4.0 mm, the distribution of the floating reference position in the three-dimensional skin model is as shown in FIG. become. The effect of the change in the skin layer thickness on the extended reflected light is large, and the floating reference position moves away from the light source as the skin layer thickness increases.
As described above, if a certain fixed radial position is selected as a reference point and measured, different measurement targets, different states of the same measurement target and multiple wavelengths cannot be covered, which may result in a measurement error. Become. This is because it is desirable to develop a measurement method that can realize general applicability to different measurement targets and wavelengths.

The above and other objects, features and advantages of the present invention will become more apparent from the following description of embodiments of the present invention with reference to the accompanying drawings. In the drawing,
FIG. 4 is a schematic diagram showing spectrum detection. FIG. 4 is a schematic diagram illustrating spectral data separation according to an embodiment of the present invention. FIG. 4 is a schematic diagram illustrating spectral data separation at different concentrations of a specific component according to an embodiment of the present invention. 5 is a flowchart illustrating a spread spectrum data processing method according to an embodiment of the present invention. 4 is a flowchart illustrating a method of determining a scattering insensitive point according to an embodiment of the present invention. FIG. 4 is a schematic diagram illustrating positions of scattering-insensitive points at different wavelengths according to an embodiment of the present invention. 4 is a flowchart illustrating a method for determining an absorption insensitive point according to an embodiment of the present invention. 9 is a flowchart illustrating a method of determining a scattering insensitive point according to another embodiment of the present invention. 5 is a flowchart illustrating a method for separating into a scattered signal and / or an absorption signal according to another embodiment of the present invention. It is a schematic diagram showing a general principle of constructing a concentration prediction model and performing concentration prediction. 5 is a flowchart illustrating a prediction model construction / concentration prediction method according to an embodiment of the present invention. 5 is a flowchart illustrating a method for performing modeling / prediction using spread spectrum data at a scattering insensitive point according to an embodiment of the present invention. 5 is a flowchart illustrating a method of implanting a model between different scattering media according to an embodiment of the present invention. 4 is a flowchart illustrating a method for implanting a model between a pure absorbing medium and a scattering medium according to an embodiment of the present invention. 4 is a flowchart illustrating a method for performing modeling / prediction using spread spectrum data at an absorption insensitive point according to an embodiment of the present invention. FIG. 4 is a schematic diagram illustrating spectral data separation at 1160 nm wavelength sensing light for a 3% intralipid solution + 10000 mg / dL glucose according to an embodiment of the present invention. FIG. 4 is a schematic diagram showing pure absorption information extracted from spectral data at different glucose concentrations in a 3% intralipid solution according to an embodiment of the present invention. FIG. 5 is a schematic diagram illustrating a change amount of an absorption coefficient due to a change in an ideal 50 mM glucose concentration according to an embodiment of the present invention. FIG. 3 is a schematic diagram illustrating an absorption coefficient of a 3% intralipid solution according to an embodiment of the present invention. FIG. 3 is a schematic diagram illustrating a relative change amount of an absorption coefficient by ideal glucose according to an embodiment of the present invention. FIG. 4 is a schematic diagram illustrating positions of scattering-insensitive points at different wavelengths according to an embodiment of the present invention. FIG. 4 is a schematic diagram showing the amount of change in absorption coefficient and scattering coefficient due to a change in 1 mM glucose concentration according to an example of the present invention. FIG. 4 is a schematic diagram showing absorption information according to a change in glucose concentration in different scattering media according to an embodiment of the present invention. 1 is a block diagram illustrating a processing device according to an embodiment of the present invention. FIG. 6 is a diagram illustrating a linear change rule according to a radial position of a relative intensity change amount obtained by a simulation according to an embodiment of the present invention. FIG. 4 is a schematic diagram showing spectrum data of a scattering insensitive point at each wavelength acquired for a plurality of wavelengths according to an embodiment of the present invention. FIG. 5 is a schematic diagram showing spectrum data of a scattering insensitive point at each wavelength obtained by measuring and fixing two points for a plurality of wavelengths according to an embodiment of the present invention. 4 schematically shows the measurement principle of the position floating reference. 2 schematically shows a typical diffuse reflection spectrum radial distribution. An example of a position floating reference variation is schematically shown. An example of the position floating reference fluctuation is schematically shown, and the position floating reference fluctuation due to a wavelength different from that shown in FIG. An example of the position floating reference fluctuation is schematically shown, and the position floating reference fluctuation due to a wavelength different from those in FIGS. 3 (a1) and 3 (a2) is shown. FIG. 3 (a1) to FIG. 3 (a3) schematically show examples of the position floating reference fluctuation, and FIG. 3 (a1) to FIG. 4 schematically shows an example of position floating reference fluctuation, and shows position floating reference fluctuation due to skin optical characteristics. Fig. 4 shows a position floating reference variation due to skin structure characteristics. Fig. 4 schematically shows a comparison of spectral changes in the inside and outside regions of the floating reference position. 1 schematically illustrates a flowchart of a spectrum data processing method according to an embodiment of the present disclosure. The change rate of the scattering coefficient according to wavelength in a skin model is shown. Jensen et shows the difference between the molar extinction coefficient of water at different temperatures as obtained in Experimental ε _w (λ) and at 30 ℃ ε _w (λ). Rhyn et al. Show the absorbance change curves between water at different temperatures and water at 30 ° C. obtained from experiments. 4 illustrates a gradual reception policy according to an embodiment of the present disclosure. 4 illustrates a gradual reception policy according to an embodiment of the present disclosure. 4 illustrates a gradual reception policy according to an embodiment of the present disclosure. 4 illustrates a gradual reception policy according to an embodiment of the present disclosure. 1 is a side view illustrating an optical fiber probe according to an embodiment of the present disclosure. 1 is a cross-sectional view illustrating an optical fiber probe according to an embodiment of the present disclosure. 1 is a cross-sectional view illustrating an optical fiber probe according to an embodiment of the present disclosure. 1 is a cross-sectional view illustrating an optical fiber probe according to an embodiment of the present disclosure. 1 is a cross-sectional view illustrating an optical fiber probe according to an embodiment of the present disclosure. It is a schematic diagram showing a general principle of constructing a concentration prediction model and performing concentration prediction. 5 is a flowchart illustrating a prediction model construction / concentration prediction method according to an embodiment of the present disclosure. 4 shows a result of calculation of a floating reference position in a Monte Carlo simulation of a 5% intralipid solution. The amount of change in the number of diffuse reflection photons when the glucose in a 5% intralipid solution changes from 50 mM to 100 mM is shown. FIG. 4 shows the variation curve of the number of diffusely reflected photons at different radial positions away from the light source before correcting for light source drift. FIG. 7 shows a change curve of the number of diffuse reflected photons at different radial positions after correcting for light source drift. Each radial position at different temperatures shows the amount of change in the number of diffuse reflected photons obtained with a change in glucose concentration. FIG. 7 shows a curve of the change in the number of diffuse reflected photons depending on the concentration before and after correcting the light source drift. This shows that comparison before and after signal correction is performed with 0 mg / dL glucose as an initialized state. It shows that comparison is made before and after signal correction with 3000 mg / dL glucose as the initialized state. It shows that comparison is made before and after signal correction with 6000 mg / dL glucose as an initialized state. 1 illustrates an example of an arrangement of a measurement system according to an embodiment of the present disclosure. The change of the relative change amount of diffused light depending on the radial position due to the effect of the element X is schematically shown. The light intensity relative change amount inside the floating reference position, itself, and outside the floating reference position after changing the light source power is shown. Shows the existence of a single temperature action line and a temperature reference point.

(Example 1)
Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, it should be understood that these descriptions are exemplary and do not limit the scope of the invention. In the following description, descriptions of known configurations and techniques may be omitted in order to avoid confusing the concept of the present invention.

From the crowded diffusion spectrum data of the scattering medium, the inventor has calculated an optical signal due to a change in the scattering characteristic (always represented by a scattering coefficient _μs or an equivalent scattering coefficient _μs ′) of each component particle of the scattering medium, and an absorption characteristic ( Has always been separated into optical signals due to changes in the absorption coefficient μ _a ). Here, the scattering medium is a medium having a component having a strong scattering action on light (and generally also having an absorption action) (which is different from a pure absorbing medium, and Lambert-Beer's law is applicable). Is not). For example, intralipid solutions are fat emulsions, slurries, and have strong light scattering. Normally, if the optical properties of human skin can be simulated with an intralipid solution, glucose can be added to simulate the measurement of glucose in the skin.

  In particular, for a particular measurement position, "optical signal due to (basically) pure scattering characteristic change" (simply referred to as "pure scattering signal") and "(basically) pure absorption characteristic Only the "optical signal due to the change" (simply referred to as "pure absorption signal") can be obtained. The two "pure signals" can represent the effects of scattering and absorption, respectively.

  This is because the inventor has found that as the measurement position becomes farther, the relative change in luminous intensity exhibits a linear or linearly approximating rule of monotonically increasing or decreasing.

  Hereinafter, this rule will be described with a steady solution in an infinite medium of the diffusion equation in the measurement theory of the scattering medium.

ただし、ρは検出器と光源との間のラジアル距離である；
μ_aは吸収係数である；
μ_s'は等価散乱係数であり、
(1-g)μ_sに定義され、
gは異方性因子であり、
μ_sは散乱係数である；
Dは光子の拡散係数であり、

；
μ_eff有効減衰係数であり、

。 As shown in FIG. 1, in the case of an annular or spherical region where the detection distance from the light source 101 is r, a first-order approximation solution of the detection distance ρ = r and the energy flux density Φ of light is expressed by Expression (1). May be.

Where ρ is the radial distance between the detector and the light source;
μ _a is the absorption coefficient;
μ _s ' is the equivalent scattering coefficient,
(1-g) _μs ,
g is the anisotropy factor,
μ _s is the scattering coefficient;
D is the photon diffusion coefficient,

;
μ _{eff is the} effective damping coefficient,

.

If, in the initial state, the absorption coefficient of the scattering medium is mu _a, the scattering coefficient is mu _s, anisotropy factor g, and the and the refractive index is n, the spectrum to be acquired in this case the initial Spectrum, that is, equation (1). If the optical properties (eg, absorption and / or scattering properties) of the scattering medium change, for example, due to a change in the concentration of the component (further from 0 to a constant value, ie, adding a certain component), and so on, , for example, variation of the absorption coefficient is [Delta] [mu _a, and the variation of the scattering coefficient is [Delta] [mu _s, the light energy flux density to obtain in this case is changed to dΦ or .DELTA..PHI. Expression (2) is obtained by totally differentiating Expression (1).

The energy flux density Φ of light is the light emission intensity within a unit volume of ρ from the light source, and the intensity and the change rule can reflect the actual intensity and change rule of the detected luminous intensity. Here, the relative change amount S of the energy flux density is defined, that is, S = dΦ / Φ. Equation (2) gives an expression for S such as equation (3):

As can be seen from equation (3), after the absorption coefficient and / or the scattering coefficient of the scattering medium has changed, the relative change amount S of the light energy flux density exhibits a rule of linear change according to the detection distance ρ. Further, S is substantially changed only by the change of the scattering characteristic (dμ _s ′) (that is, the first term of the equation (3)), and S is substantially changed only by the change of the absorption characteristic (dμ _a ) (that is, the change is caused by only the change (dμ _a )). , (2) of equation (3)), and it can be seen that these two changes also represent the rules of linear change. In actual detection, the measured value is always luminous intensity, and has a linear relationship with the energy flux density of light when parameters such as the receiving area, angle, and time are fixed. For this reason, it can be assumed that the relative change in luminous intensity also satisfies the above rule. Hereinafter, the relative change amount of the luminous intensity is also described in S.

Although equation (3) has been obtained for infinite media, the inventors have found that such linear rules can be applied to semi-infinite media as well. In the case of semi-infinite measurements, some scattering media do not strictly follow the above linear rule, but can basically meet the linear rule. In particular, when investigating a change in luminous intensity in a small radial distance range instead of the entire radial distance range (from 0 to infinity), it is possible to approximate using the above linear rule. In an actual measurement, there is always a semi-infinite measurement situation, and the inventor has verified that the linear rule can be applied by means of experiments and simulation simulations. For example, the inventor conducted an experiment for measuring a semi-infinite medium of a scattering medium solution. The light source is located above the media, the media extends below and the thickness is large and approximates infinity. In this case, by measuring the luminous intensity at different positions from the light source in order, it can be understood that the relative change amount S of the luminous intensity represents a rule of substantially linear change as shown by a solid line in FIG. 16 according to the radial distance. Further, inventors have simulated to calculate the semi-infinite medium by Monte Carlo simulation, simulating the random travel at 10 ⁸ photons scattering medium. Specifically, the relative change in luminous intensity when the concentration of glucose in a 3% intralipid solution as a scattering medium was changed to 50 mM was simulated. The number of photons emitted from different radial positions can reflect the intensity of the emitted light intensity, and the relative change amount of the emitted photons can reflect the relative change amount S of the emitted light intensity. FIG. 25 reflects a change rule according to the radial distance ρ of S. As can be seen, at some distance from the light source, for example 0.5 mm, the linear rule becomes very apparent.

ただし、ρはラジアル距離であり、Ici(ρ)は散乱媒体のある特定成分の濃度がCiとする場合の測定光度であり、Ic0(ρ）は散乱媒体に該特定成分を含まない場合、あるいは、該特定成分がある固定の初期濃度となる場合の測定光度であり、μs'は散乱媒体の等価散乱係数であり、μaは散乱媒体の吸収係数であり、∂I(ρ)/∂μs'はラジアル距離ρにおける光度I(ρ）の等価散乱係数μs'の変化に対する変化率を表し、∂I(ρ)/∂μaはラジアル距離ρにおける光度I(ρ）の散乱係数μaの変化に対する変化率を表し、Δμs'は等価散乱係数の変化量であり、Δμaは吸収係数の変化量である。 On the other hand, a change in luminous intensity may be expressed by the following equation.

Here, ρ is the radial distance, Ici (ρ) is the measured luminosity when the concentration of a specific component of the scattering medium is Ci, and Ic0 (ρ) is when the scattering medium does not contain the specific component, or Is the measured luminous intensity when the specific component has a fixed initial concentration, μs ′ is the equivalent scattering coefficient of the scattering medium, μa is the absorption coefficient of the scattering medium, and ∂I (ρ) / ∂μs ′ Represents the rate of change of the luminous intensity I (ρ) with respect to the change of the equivalent scattering coefficient μs' at the radial distance ρ, and ∂I (ρ) / ∂μa represents the change of the luminous intensity I (ρ) with respect to the change of the scattering coefficient μa at the radial distance ρ Δμs ′ is the variation of the equivalent scattering coefficient, and Δμa is the variation of the absorption coefficient.

ただし、Δμs,j'(λ）はｊ番目の要素による等価散乱係数の変化を表し、
Δμa,j(λ）はｊ番目の要素による吸収係数の変化を表す。 Among them, as shown in Expression (5), the variation of the scattering coefficient (or equivalent scattering coefficient) and the absorption coefficient is obtained by a combination of a plurality of elements. j is a factor that affects the optical parameter of the medium, for example, the concentration of a component (and further, from 0 to a constant value, that is, the addition of the component), and the change affects the absorption coefficient and It also affects the scattering coefficient (or equivalent scattering coefficient).

Here, Δμs, j ′ (λ) represents a change in the equivalent scattering coefficient due to the j-th element,
Δμa, j (λ) represents a change in the absorption coefficient due to the j-th element.

ただし、λは測定光の波長を表し、これは散乱係数（又は等価散乱係数）及び吸収係数が測定光の波長の変化に従って変化可能であるためである。 For convenience of separation, processing is performed here using the relative change in luminous intensity, that is, the situation in which a plurality of elements change using the expression of S is subsequently analyzed. By substituting S-expression (3) for an infinite medium into (5), expression (5) becomes expression (6). As described above, as shown in FIG. 2, the relative change amount S of the luminous intensity represents a rule of linear change according to the radial detection distance. For any single element j in a plurality of elements, it all represents a linear change according to the distance ρ, here it is called the "action line"; and, as a result of the comprehensive action of the plurality of elements, It is a superposition of lines, which is also a linear "action line".

Here, λ represents the wavelength of the measurement light because the scattering coefficient (or equivalent scattering coefficient) and the absorption coefficient can be changed according to the change in the wavelength of the measurement light.

  The following should now be explained. The relative change amount for calculating the luminosity according to the present application may be subtracted “after taking (natural) logarithm”, in order to make the calculation more convenient (for example, conversion from division to subtraction). it can). However, this operation itself is not essential for the technique of the present invention.

  As shown in FIG. 2, as described above, the relative change in luminous intensity (ΔI (ρ) / I (ρ)) represents a linear rule along the radial position (ρ). The straight line 201 in FIG. 2 shows such a linear change. In this specification, this straight line is referred to as an “overall line of action” (ie, optical information due to the joint action of scattering and absorption), and information on scattering change and absorption change due to changes in each component or element included in the scattering medium. Information.

  Note that the straight line 205 in FIG. 2 is substantially the first term (related to dμs ′) in the above equation (3) or the first term (related to Δμs, j ′ (λ)) in the above equation (6), that is, substantially. 5 shows optical information (for example, a change in luminous intensity) only due to a change in scattering characteristics. Then, in this specification, the straight line is referred to as “scattering line of action”. The straight line 209 in FIG. 2 is the second term of the above equation (3) (related to dμa) or the second term of the above equation (6) (related to Δμa, j (λ)), that is, the change in the absorption characteristic substantially. Only the optical information (for example, change in luminous intensity) is shown. In this specification, the straight line is referred to as “absorption line”. As described above, each of these two terms also represents a linear rule.

  That is, the scattering line can represent the expression at each radial detection position of "optical information (or signal) substantially due to only a change in scattering characteristics"; The expression at each radial detection position of “optical information (or signal) due to only the change of“. On the other hand, the integrated action line mainly considers optical information or signals due to changes directly or indirectly integrated due to changes in the absorption coefficient and the scattering coefficient (or equivalent scattering coefficient). The overall action line may be the result of an actually measured luminous intensity change. The comprehensive result is decomposed into a scattered ray and an absorption ray and used for analyzing absorption and scattering information.

  Here, the concept of the scattering non-sensitive point 203, the absorption non-sensitive point 207, and the overall fluctuation reference point 215 may be introduced, and the zero cross position of the scattering action line 205, the absorption action line 209, and the overall action line 201 may be adopted.

If 位置 I (ρ) / ∂μs = 0 at a certain position at a certain wavelength, “(basically) optical information due to pure absorption change” can be obtained. The position is defined at the scattering insensitive point 203 and described in ρ *. According to equation (3) (the first term is set to zero),

When あ る I (ρ) / ∂μa = 0 at a certain position at a certain wavelength, “(basically) optical information due to pure scattering change” can be obtained. The position is defined as an absorption insensitive point 207,
ρ '. According to equation (3) (the second term is set to zero),

、綜合作用線が０点であることを得ることができる。該位置は綜合変動基準点２１５と定義され、ρ♯に記述される。式（３）（２項の合計を０にする）によれば、

At a certain wavelength, when scattering and absorption work together,

, It can be obtained that the total action line is zero. This position is defined as the total fluctuation reference point 215 and is described in ρ♯. According to equation (3) (to make the sum of the two terms zero),

ただし、∂μｓ'/∂Cjは等価散乱係数μs'が成分ｊの濃度Cjに対して変化する変化率を示し、∂μa/∂Cjは吸収係数μaが成分ｊの濃度Cjに対して変化する変化率を示し、ΔCjは成分ｊの濃度変化量を示す。 Further, in order to consider the effects of different substances, as shown in Equation (6), if the change in the absorption coefficient and the change in the scattering coefficient due to the specific component are directly proportional to the concentration, the concentration is calculated. Is varied within a small range, the differential result of each element (as shown in Expression (10)) is substituted into Expression (6) to obtain Expression (11). At this time, a fixed integrated reference point position exists for the component, and can be obtained by Expression (12). At this time, the scattering action line and the absorption action line are separated as shown in FIG.

Here, ∂μs '/ ∂Cj indicates a change rate at which the equivalent scattering coefficient μs' changes with respect to the concentration Cj of the component j, and ∂μa / ∂Cj indicates that the absorption coefficient μa changes with respect to the concentration Cj of the component j The change rate is shown, and ΔCj indicates the amount of change in density of the component j.

  Referring to FIG. 3, when the concentration of a specific component in the same scattering medium changes (three concentration changes are shown in the figure), corresponding comprehensive action line 301, scattering action ray 305, and absorption action ray 309 are obtained. I do. The positions of the integrated reference point 315, the scattering insensitive point 303, and the absorption insensitive point 307 do not basically change. We apply this rule whenever the optical parameters (especially the scattering coefficient) of the scattering medium vary over a large range (for example, for a given scattering medium, the scattering coefficient changes less than 50%). I discovered what I could do. Absorption changes may be regarded as signals, since the factor affecting the spectral measurement is mainly the variation of the medium scattering coefficient; in the real spectral detection field, such large scattering coefficient variations are substantially less. Does not appear. Therefore, this rule can be applied to general spectrum detection. On the other hand, for a particular component, its concentration may be limited within a certain range, because it is the (high accuracy) measurement of that particular component in a scattering medium that is discussed here. When the detection range is required to be wide (that is, when the concentration change of the specific component is large), if the concentration difference is too large, the medium itself changes, and therefore, the medium in a different measurement range is used. This rule can also be considered as a number of different media; and in the small measuring range, the overall reference point, scattering insensitive point and absorption insensitive point submitted here are basically fixed and do not change, Applicable. That is, this rule is generally always satisfied when used for concentration measurement by the spectral method.

  Based on the above characteristics, the present invention proposes a method for processing diffuse spectrum data. As shown in FIG. 4, the method includes, in operation S401, acquiring spread spectrum data at one or more first radial positions of a medium to be measured. For example, spread spectrum data at a plurality of consecutive positions, for example, relative changes in luminous intensity, can constitute the above “overall action line”. The medium to be measured includes, for example, each type of (scattering) medium such as milk and blood. For convenience of description, the medium under measurement is considered to include the background medium and certain components of the background medium (ie, the background medium may be other components than the specific components of the medium under measurement). It is. Such specific components may be of interest, for example, milk lactose, blood blood sugar, and the like.

  Those skilled in the art are aware of several ways to perform spectrum measurements and obtain spread spectrum data. For example, a light source illuminates a medium to be measured with light of a certain wavelength, and a detector senses diffused and / or diffusely transmitted light of the medium to be measured. For example, the light intensity (for example, the light intensity at a plurality of wavelengths is Can be configured). Alternatively, both the light source and the detector can penetrate into the medium to be measured and measure the spread spectrum data, which is similar to the case of an infinite medium. The position of the detector can be adjusted to achieve multiple radial position measurements. According to the embodiment of the present invention, it is possible to infer and obtain measurement data at other radial positions by using measurement data at at least two radial positions (further, obtain the entire integrated action line). Hereinafter, this will be described in more detail.

In addition, for example, light having one or more wavelengths such as ultraviolet, visible, and infrared bands can be selected and measured according to the characteristics of the medium to be measured and / or the specific components thereof. For example, a wavelength that is sensitive to the scattering and / or absorption properties of the specific component and / or a wavelength that is insensitive to the scattering and / or absorption properties of the background medium can be selected.
Advantageously, the relative change in luminous intensity (for example, due to the change in the concentration of a specific component of the medium to be measured) can be measured as spread spectrum data. For example, when the background medium does not contain the specific component, or when the specific component has a fixed initial density value (hereinafter, the specific component of the background medium and the initial density is referred to as a “reference medium”), The spectrum can be measured at one or more radial detection distances and used as the initial spectrum and described in I1. Then, when the concentration of the specific component changes with respect to the initial concentration in the background medium, the spectrum at one or a plurality of radial detection distances of the measured medium at this time is measured and described in I2. For example, for the measurement of blood glucose in blood, first, the blood spectrum of an empty stomach (where blood glucose is at a stable low level) is measured as an initial spectrum; , The blood sugar changes, and gradually becomes stable up to 2 hours after a meal), thereby obtaining blood sugar change information.

又はs＝(Ｉ_２-Ｉ_１)／Ｉ_１を上記拡散スペクトルデータとして取得することができる。しかしながら、拡散スペクトルデータが上記光度の相対変化量に限られず、下記のように、他の類型のデータ（例えば、光度の変化量）を取得してもよいことを説明すべきである。 The relative change in luminosity by these two spectra

Alternatively, s = (I ₂ −I ₁ ) / I ₁ can be obtained as the spread spectrum data. However, it should be explained that the spread spectrum data is not limited to the above-mentioned relative change in luminous intensity, and other types of data (for example, the luminous intensity change) may be obtained as described below.

  In many embodiments of the present invention, it is necessary to measure an initial spectrum. The spectrum in the case where the background medium does not include the specific component may be used as the initial spectrum, and the spectrum in the case where the background medium includes the specific component having an arbitrary fixed initial concentration (ie, the reference medium) may be used as the initial spectrum. For example, for some media (especially background media that does not contain a specific component), an initial spectral database is constructed and used for duplication (for example, used in advance for experiments and actual measurements). This may reduce the work load.

In addition, when acquiring spectrum data, it is possible to adopt only the measurement data at a small number of radial detection positions and infer by using the above-described linear rule, and acquire data at other positions. For example, at least two sets of spread spectrum data (for example, relative changes in luminous intensity) at the radial position are measured, and the radial position is set as the abscissa. Spectral data (for example, relative change S in luminous intensity) can be obtained. Further, it is possible to infer the data of the absolute change in luminous intensity, ΔI = SSI ₁ , where I ₁ is the case where the specific component is not contained in the background medium or at a fixed initial concentration where the specific component is present. It is the luminous intensity in one case, that is, the initial spectrum. In particular, if one of these two points adopts the zero-cross point of the “overall action line” (also referred to as “overall variation reference point”; for example, see “215” in FIG. 2), this point Since it is practically insensitive to the change in the concentration of the substance component, the measured value can be directly estimated as the initial luminous intensity, and no measurement is required.

  After obtaining the spread spectrum data (e.g., the general action line or one or more points in the general action line), the method may include, in operation S403, one or more second radials in response to the spread spectrum data. Optical information (eg, a scatter line or one or more points in the scatter line) at the location substantially due to a change in the scattering properties of the medium and / or substantially due only to a change in the absorption properties of the medium to be measured. It also includes determining optical information (eg, an absorption line or one or more points in the absorption line). As mentioned above, the extraction of such scattering and absorption effects is possible. The one or more second radial positions may be different, the same, or partially the same as the one or more first radial positions.

  For example, this extraction can be performed according to the scattering insensitive point and / or the absorbing insensitive point of the measured medium. Here, the “scattering insensitive point” means a radial position at which the luminous intensity information in the spectrum data is substantially insensitive to a change in the scattering characteristic in the measured medium, and the “absorption insensitive point” The luminous intensity information in the spectrum data may mean a radial position at which the luminous intensity information is substantially insensitive to a change in the absorption characteristic of the medium to be measured. Referring to FIG. 3, when the concentration of the specific component of the medium to be measured changes, the positions of the scattering non-sensitive point and the absorption non-sensitive point basically do not change. Therefore, the scattering insensitive point and / or the absorbing insensitive point of the measured medium can be obtained by measuring the background medium or the reference medium.

  Extracting the scattered signal and / or the absorption signal by the scatter non-sensitive point and / or the absorption non-sensitive point can be performed, for example, as follows. Specifically, referring to FIG. 2, according to the spectral data (ie, point 213) at the absorption insensitive point 207 and the scattering insensitive point 203, for example, a linear fit or the two points 213, 203 can be directly performed. By connecting, scattering action rays can be obtained. Similarly, depending on the spectral data at scattering insensitive point 203 (ie, point 211) and absorption insensitive point 207, for example, a linear fit or by directly connecting the two points 211, 207 to the absorption line of action Can be obtained.

When spectral data of a plurality of wavelengths are measured, data can be extracted from the spectral data of each wavelength by using a corresponding scattering non-sensitive point and / or absorption non-sensitive point of each wavelength.
With reference to FIG. 3, the scattering action line and / or the absorption action line (or the slope thereof) reflect the change in the concentration of the specific component of the background medium, and can be used for estimating the concentration. Hereinafter, this will be described in more detail.

  Here, it should be understood that it is not necessary to separate into both the scattering action line and the absorption action ray, but it is sufficient to separate into one of them. For example, as described below, the concentration can be predicted only by the scattering action ray or the absorption action ray. Note that it is not necessary to acquire the entire scattered ray or absorption ray, and it is sufficient to acquire one or more points in the scattered ray or absorption ray.

  In the above operation, the scattering insensitive point and the absorption insensitive point of the measured medium are adopted. The scattering insensitive point and the absorption insensitive point can be determined, for example, as follows.

又はs＝(Ｉ_２-Ｉ_１)／Ｉ_１
と計算することができる。光度の変化が、操作Ｓ５０３における背景媒体又は基準媒体の散乱特性の変化による（吸収特性は基本的に変化しない）ため、光度の変化情報は基本的に背景媒体又は基準媒体の散乱特性の変化に完全に反映している。絶対変化量I'又は相対変化量Ｓのゼロクロス点に対応するラジアル位置、すなわち、光度の変化が実質的に零である箇所におけるラジアル位置を、散乱非感応点とすることができ、この原因は、該点はスペクトルデータ（ここでは光度である）が背景媒体又は基準媒体の散乱特性の変化に従って変化せず、すなわち、散乱特性に感応しないことを表すためである。上記のように、該点は被測定媒体の散乱非感応点と見なされてよく、それは、上記のように、該特定成分の濃度の変化が基本的に散乱非感応点の位置に影響しないためである。 Referring to FIG. 5, in operation S501, a measurement light having a constant wavelength and a different radial detection distance with respect to a background medium or a reference medium (the background medium and the reference medium may be generally scattering media). the spectrum was measured as the initial spectrum, described in I _1. Then, in operation S503, the scattering coefficient of the background medium or the reference medium is finely changed, and for example, a small amount of scattering particles may be added. (E.g., the added particles essentially do not exhibit absorption at that wavelength). Here, a “fine” change means that this change causes a change that can be observed in the spectral data, but in addition that the overall optical properties of the background medium or the reference medium do not basically change. means. That is, this minute change is regarded as a differential concept dμs ′ or Δμs, j ′ (λ). Since such a concept is always used in the measurement principle of the differential or difference method, a person skilled in the art will be able to understand the specific numerical selection of this "fine" change and how to realize it in practical applications. Here, this “fine” change is not necessarily the absolute value of a very small number; similarly, a very small absolute value change is not necessarily the “fine” change here (eg, from one skin to another). It should be noted that changes to the skin of the skin are generally not considered as subtle changes, but as changes in the background medium.) At this time, the measurement light of the same wavelength, by measuring the spectrum at different radial detection distance of the background medium or reference medium,
And I _2. Then, in operation S505, a scattering insensitive point at the wavelength can be determined according to the change information of the luminous intensity. Specifically, the absolute change amount of light intensity I ′ = I ₂ −I ₁ or the relative change amount of light intensity S can be calculated,

Or s = (I ₂ −I ₁ ) / I ₁
Can be calculated. Since the change in the luminous intensity is due to the change in the scattering characteristics of the background medium or the reference medium in operation S503 (the absorption characteristics do not basically change), the change information of the luminous intensity basically corresponds to the change in the scattering characteristics of the background medium or the reference medium. Fully reflect. The radial position corresponding to the zero cross point of the absolute change amount I ′ or the relative change amount S, that is, the radial position at a place where the change in luminous intensity is substantially zero can be set as the scattering insensitive point. This point is to indicate that the spectral data (here the luminosity) does not change according to the change in the scattering properties of the background medium or the reference medium, ie it is insensitive to the scattering properties. As described above, the point may be considered as a scattering insensitive point of the measured medium, because, as described above, the change in the concentration of the specific component does not basically affect the position of the scattering insensitive point. It is.

  Here, in the reference medium, the initial concentration of the specific component may be the same as or different from the initial concentration of the specific component in the measured medium when measuring the initial spectrum of the measured medium. Should understand. Similarly, in the following examples, the initial concentrations of the specific components are not necessarily the same in the reference medium used in different cases.

  For different wavelengths, processing as shown in FIG. 5 is performed for each of these wavelengths so as to obtain a scattering insensitive point at each wavelength of the background medium.

  FIG. 6 shows the results of an experiment on an intralipid solution with a concentration of 3%. This intralipid solution can simulate, for example, the condition of the skin of the human body, for example, the optical parameters of one person's skin are similar to 3% concentration of intralipid, but the optical parameters of one person's skin are 4% concentration of intralipid. Similar. For this reason, a biological measurement can be simulated using an intralipid solution simulation experiment (for example, glucose is added to the intralipid solution to simulate the measurement of blood glucose in a living body). In this illustration, the intralipid solution is considered as the background medium and glucose is considered as the specific component. FIG. 6 shows scattering insensitive points for the 1100-1340 nm band.

又はs＝(Ｉ_２-Ｉ_１)／Ｉ_１と計算できる。光度の変化が、操作Ｓ７０３における背景媒体又は基準媒体の吸収特性の変化による（散乱特性は基本的に変化しない）ため、光度の変化情報は基本的に背景媒体又は基準媒体の吸収特性の変化を完全に反映している。絶対変化量I'又は相対変化量Ｓのゼロクロス点に対応するラジアル位置、すなわち、光度の変化が実質的に零である箇所におけるラジアル位置を、吸収非感応点とすることができ、この原因は、該点はスペクトルデータ（ここでは光度である）が背景媒体又は基準媒体の吸収特性の変化に従って変化しなく、すなわち、吸収特性に感応しないことを表すためである。上記のように、該点は被測定媒体の吸収非感応点と見なされてよく、それは、上記のように、該特定成分の濃度の変化が基本的に吸収非感応点の位置に影響しないためである。 The background medium or reference medium, the measuring light having a constant wavelength to measure the spectrum at different radial detection distance, the initial spectrum, described in I _1. Then, in operation S703, the absorption coefficient of the background medium or the reference medium is finely changed, for example, a small amount of an absorbing component is added, so that the scattering characteristics of the background medium or the reference medium at the wavelength are not basically affected. (For example, the added component basically does not exhibit scattering at that wavelength). Here, the “fine” change can refer to the above description. At this time, the measuring beam of the same wavelength, to measure the spectrum at different radial detecting distances background medium or reference medium, and I _2. Then, in operation S705, an absorption insensitive point at the wavelength can be determined according to the luminous intensity change information. Specifically, the absolute change amount of light intensity I ′ = I ₂ −I ₁ , or the relative change amount of light intensity S,

Or, s = (I ₂ −I ₁ ) / I ₁ can be calculated. Since the change in luminous intensity is due to the change in the absorption characteristic of the background medium or the reference medium in operation S703 (the scattering characteristic does not basically change), the change information of the luminous intensity basically indicates the change in the absorption characteristic of the background medium or the reference medium. Fully reflect. A radial position corresponding to the zero cross point of the absolute change amount I ′ or the relative change amount S, that is, a radial position at a position where the change in luminous intensity is substantially zero can be set as an absorption insensitive point. This point is to indicate that the spectral data (here the luminosity) does not change according to the change in the absorption characteristics of the background medium or the reference medium, ie it is insensitive to the absorption characteristics. As described above, the point may be regarded as an absorption insensitive point of the medium to be measured because, as described above, a change in the concentration of the specific component basically does not affect the position of the absorption insensitive point. It is.

  As described above, the initial concentration of the specific component in the reference medium when measuring the absorption insensitive point is the same as the initial concentration of the specific component in the measurement medium when measuring the initial spectrum of the measurement medium. The initial concentration of the specific component in the reference medium when measuring the scattering insensitive point may be the same or different.

  Similarly, processing as shown in FIG. 7 is performed for different wavelengths, and scattering insensitive points at each wavelength of the background medium can be obtained for these wavelengths.

  Actually, since the absorption insensitive point is always close to the light source, it can be approximated to ρ ′ = 0, or can take a relatively small numerical value.

  In the processing shown in FIGS. 5 and 7, the scattering insensitive point and the absorption insensitive point at the required wavelengths are determined in advance by experiments. However, the present invention is not limited to this. For example, a scattering insensitive point at a target wavelength can be estimated according to measurement data at another wavelength. The absorption insensitive point can be determined in advance by the above experiment, or may be directly approximated using a relatively small position (for example, ρ ′ = 0).

  Referring to FIG. 8, in operation S801, an approximate wavelength λr of a target wavelength λ for measuring a spectrum of a medium to be measured can be set as a reference wavelength. The reference wavelength λr can be selected as a wavelength at which a specific component contained in the medium to be measured has weak absorption or a wavelength at which no absorption occurs. For example, for glucose as a specific component, a wavelength of 1150 nm can be the target wavelength (ie, used for measurement), at which wavelength the absorption of glucose is relatively strong (the absorption information indicates that the component Can be well reflected, as described below); and a wavelength of 1050 nm can be the reference wavelength because at that wavelength the absorption of glucose is relatively weak. Note that the scattering line at the reference wavelength λr and the scattering line at the target wavelength λ may be approximated.

Subsequently, in operation S803, spectral data of the medium to be measured can be obtained for the target wavelength λ and the reference wavelength λr. This spectral data includes, for example, the above-mentioned luminous intensity variation or luminous intensity relative variation. Specifically, for example, spectrum I _2Ramudaaru of the medium to be _measured, can be measured I _{2 [lambda],} the spectrum I _1Ramudaaru the initial state (e.g., including the specific components of the specific component is not contained, or a fixed concentration in the background medium) processed for I _{1 [lambda,} acquires for example the light intensity of the relative change amounts Esuramudaaru, the Esuramuda. They can be spectral data at the reference wavelength λr and the target wavelength λ, respectively (eg, the overall action line).

、吸光度A₂
、吸光度の絶対変化量

、吸光度の相対変化量

又は上記信号により構成する他の関連量（例えば、これらの情報を線形変化して取得した信号）（ただし、I₁、μa₁及びA₁はそれぞれ散乱非感応位置における初期光度（すなわち、背景媒体又は基準媒体を測定するときの光度）、初期吸収係数（すなわち、背景媒体又は基準媒体の吸収係数）及び初期吸光度（すなわち、背景媒体又は基準媒体の吸光度）であり、I_２、μa_２及びA_２はそれぞれ被測定成分の濃度が変化した後（モデリングするとき、背景媒体又は基準媒体に既知濃度の特定成分を添加した後；予測するとき、背景媒体又は基準媒体に特定成分の濃度が変化した後）で散乱非感応位置における光度、吸収係数及び吸光度である）を含むが、これらに限られない。上記信号は基本的にいずれも特定成分の吸収変化によるものであり（散乱非感応点におけるデータであるため）、これらの間は以下のように、直接的に線形変換できる。
具体的には、光度、吸収係数、吸光度の間の理論的関係は、

であり、ただし、L*は散乱非感応点における平均等価光路であり、同一の媒体にとって、それを定数と見なされる；I_０光源の入射光度である。
無限媒体にとって、（散乱非感応点で）以下の関係がある：

したがって、同一の媒体にとって、光度の相対変化量、吸収係数の相対変化量及び吸光度の相対変化量は等価である。
一方、半無限媒体にとって、散乱非感応位置で、上記関係が変化している。しかしながら、固定の被測定媒体にとって、光度の相対変化量、吸収係数の相対変化量及び吸光度の相対変化量は下式のように、直接的に線形変換でき、ただし、特定の媒体にとってαは固定の定数である：

また、上記相対変化量以外に、他の形式の信号の間も互いに変換できる。例えば、式（１３）又は式（１４）によって、光度の度量、吸収係数の度量及び吸光度の度量という３つの関連を実現でき、そして、初期光度、初期吸収係数又は初期吸光度を基礎とし、光度、吸収係数及び吸光度の絶対変化量又は絶対値を取得することができる。例えば、散乱非感応点における絶対光度I_２を測定し、あるいは推測すれば、初期光度I_１によって、相対光度変化量S₁=ΔI/I＝（I₂-I_1）/I₁を算出でき、式（１３）又は式（１４）によって吸収係数又は吸光度の相対変化量Sμa又はS_Aを取得できる。さらに、取得された吸収係数又は吸光度の相対変化量Sμa又はS_Aに基づき、初期吸収係数μa₁又は吸光度A₁を結合して、吸収係数μa_２又は吸光度A_２を取得できる。
ここでは、モデリング及び予測するときに同じ信号形式を採用してもよく、異なる信号形式を採用してもよいことを理解すべきである。例えば、モデリング及び予測するときに、光度の相対変化量又は吸収係数の相対変化量などを採用できる。あるいは、例えば、モデリングするときに、光度の相対変化量（あるいは、ほかの信号形式）を採用するが、予測するときに、吸収係数の相対変化量（あるいは、他の信号形式）を採用できる。この場合、上記の信号の間が直接的に変換できるため、予測するとき、吸収係数の相対変化量を光度の相対変化量に変換して、予測モデルを入力することができる。
モデリングと予測するときに異なる信号形式を採用する場合、変換しなくてもよい（例えば、上記のように、予測するときに採用する信号形式をモデリングするときに採用する信号形式に変換する）。このとき、予測するときに大きいシステム誤差を生する可能性がある。しかしながら、該システム誤差は、濃度の真値を取得した後で推定でき、例えば、定期に被測定成分の濃度の真値によってシステムの予測誤差Ce及び補正係数ｋを取得して、例えば式（１５）に従って濃度の予測値を線形補正する。

ここでは、Ｃ_予測は予測の濃度を示し、Ｃ_補正は補正後の濃度を示す。
つまり、モデリング及び予測するとき、上記任意の信号形式を採用することができる。
モデルを長時間の予測に用いるとき、長時間以前の初期信号を採用すれば、予測の精度が低下する可能性があり、その原因は、機械の移動、環境の変化などの測定背景の変化がシステム誤差を引き起こす可能性があるためである。初期光度、初期吸収係数又は初期吸光度を含む初期信号を定期に更新することができる。初期信号を更新するとともに、このときの被測定成分の濃度の真値を取得することができる。この値は、モデル予測により取得でき、あるいは精度がより高い他の検出方法又は機械によって検出して取得されることもできる。そして、濃度の予測値はいずれも該真値に対する濃度変化値である。あるいは、元の初期信号を採用してもよいが、濃度の予測値に対してシステム補正を行い、あるいは、式（１５）に従って濃度の予測値を補正する。
「散乱非感応点」における上記信号又はそれらに関連する他の信号を採用すると、同じ背景媒体又は基準媒体における該特定成分に対する測定を実現できるとともに、モデル変換によって、他の背景媒体又は基準媒体における該特定成分に対する測定も実現できる。例えば、生体を測定するとき、被測定成分と干渉成分とを変動させて異なる状況のスペクトルデータを取得することは実現され難しい。例えば、生体のいくつかの成分の濃度は、短期において安定であり、変化後の測定データを取得し難しい。生体から離れてモデリング実験を行うことは便利であり、純粋な吸収媒体を採用すると、モデリングはより便利になる。したがって、若し、散乱媒体の間、散乱媒体と純粋な吸収媒体との間は便利に変換できれば、モデルの汎用性が強くなり、移植性も強くなる。生体のスペクトル検出に対して、個体の差異によるモデルの汎用性がない、及びしょっちゅう失効するという課題を解決する可能性もある。
図１３を参照して、操作Ｓ１３０１において、（既知）予測モデルを構築するための背景媒体又は基準媒体の吸収係数μ_as1、および予測するときの背景媒体又は基準媒体（モデリングするための背景媒体又は基準媒体と異なっている；ここでは、「異なる」とは、特定成分の濃度が異なる以外に、互いの背景媒体も異なり、例えば、成分の組成が異なる）の吸収係数μ_as2を測定できる。例えば、吸収係数は、積分球又は他の汎用な光学パラメーターの測定方法により測定できる。上記のように、モデリングするための背景媒体又は基準媒体に一連の既知濃度の特定成分を添加し、相応的なスペクトルデータを測定して、モデリングすることができる。なお、予測待ちの背景媒体又は基準媒体の特定成分の濃度は変化でき、これにより、上記のようにその光度の変化情報を取得することができる。
続いて、操作Ｓ１３０３において、取得した吸収係数μ_as1及びμ_as2（例えば、その比率）によって、予測待ちの媒体の散乱非感応点における拡散スペクトルデータに対してプリ処理することができる。拡散スペクトルデータは例えば上記信号形式を含む。例えば、２つの背景媒体又は基準媒体間の吸収係数の比率により、以下のようにプリ処理することができる。
具体的には、モデリング及び予測するときに光度の相対変化量、吸収係数の相対変化量又は吸光度の相対変化量を採用すれば、以下のようにプリ処理を行うことができる：

ただし、S_μa'は予測媒体に対して取得した吸収係数の相対変化量であり、S_μaはS_μa'に対してプリ処理を行った後で取得したプリ処理後の信号である；S_A'は予測媒体に対して取得した吸光度の相対変化量であり、S_AはS_A'に対してプリ処理を行った後で取得したプリ処理後の信号である；S_I'は予測媒体に対して取得した光度の相対変化量であり、S_IはS_I'
に対してプリ処理を行った後で取得したプリ処理後の信号である。そして、プリ処理後の信号をモデリングするときに取得したモデルに入力することができる。若し、モデリングするときの背景媒体又は基準媒体と予測するときの背景媒体又は基準媒体との吸収係数が近似すれば、又はほぼ同じであれば、それらの区別は、主に散乱係数又は等価散乱係数が異なると（これは例えば背景媒体又は基準媒体の成分により確定でき、例えば、それらの成分の差異は吸収係数の変化を基本的に引き起こさない）、吸収係数を測定するステップＳ１３０１を省略でき、式（１６）の係数は基本的に１であるためである。
上記のように、モデリング及び予測するときに同じ信号形式を採用するか否かに応じて、これらの信号を変換するか否かを確定できる；あるいは、変換せずに、式（１５）によって濃度予測値に対してシステム補正を行うことができる。
あるいは、プリ処理せずに、２つの媒体の吸収係数間の差異をシステム誤差と見なし、式（１５）によって濃度予測値を補正することができる。
もちろん、他の信号形式を採用してもよい。モデリング及び予測するときに異なる信号形式を採用すれば、上記のように、式（１３）及び（１４）によって、予測するときに採用する信号形式をモデリングするときに使用する信号形式に変換し、変換後の信号を予測モデルに入力することができる。このとき、同じ信号であるが、異なる媒体であるため、一般的には、その初期信号に大きい差異がある。このため、システム誤差を生じる可能性もある。同様に、式（１５）に従ってシステム補正を行うことができる。あるいは、信号を変換せずに、式（１５）に従って濃度予測値に対してシステム補正を行うこともできる。
あるいは、吸収係数によってプリ処理を行ってもよい。例えば、絶対光度I_２を用いるとき、それを光度の相対変化量S₁=ΔI/I＝（I₂-I_1）/I₁に変換し、式（１６）に従ってプリ処理を行って、プリ処理後の光度の相対変化量を取得できる。プリ処理後の光度の相対変化量を初期光度I₁にかけて、初期光度I₁と加算して、プリ処理後の絶対光度を取得できる。プリ処理後の絶対光度を予測モデル（例えば、絶対光度に基づく予測モデル）に入力することができる。他の信号形式に対して類似的に処理できる。
そして、操作Ｓ１３０５において、予測モデルによって、予測待ちの媒体における特定成分の濃度予測値を取得できる。
上記プリ処理は例えば以下のように理解できる。
式（７）を式（３）に代入して、散乱非感応点における光度の相対変化量（すなわち、純粋な吸収情報）を取得できる：

散乱非感応点で測定した信号Ｓは被測定媒体の吸収係数及び吸収係数の変化量のみに関連しており、散乱係数又は等価散乱係数に関連していない。したがって、散乱媒体の散乱係数が異なり、吸収係数が同じであれば、同じ測定情報Ｓを取得する。
異なる吸収係数の散乱媒体（例えば、μ_a1とμ_a2という２つの媒体）に対して、同じ特定成分による吸収係数の変化Δμ_aを測定するとき、Ｓが反映する吸収情報の区別は、係数項１／μ_aのみであり、該係数は、μ_a1及びμ_a2を予め測定して、両者の比例係数を取得することによって補正されることができる。

したがって、異なる散乱媒体間に構築されるスペクトル測定モデルは、便利に移植及び使用することができる。
ここで以下のことを理解すべきである。上記散乱非感応点における拡散スペクトルデータによってモデリング／予測を行うことに対する説明は、同様に吸収作用線の他の点における拡散スペクトルデータによってモデリング／予測を行うことにも適用できる。その原因は、吸収作用線において、全ての点の拡散スペクトルデータが基本的にいずれも媒体の吸収特性の変化による（以上のように、散乱非感応点における拡散スペクトルデータの方はより抽出しやすいだけである）ためである。
上記のように、異なる散乱係数の散乱媒体がスペクトルモデルを互いに移植できる以外に、純粋な吸収背景媒体における測定モデルによって移植することもできる。その前提としては、当該純粋な吸収背景媒体の吸収係数と散乱媒体の吸収係数とが近似しており、あるいは、両者の吸収係数が予め測定され、式（２０）を用いてデータ変換を行う。純粋な吸収媒体によって測定モデルを構築するとき、光路がL*＝１／μaである透過測定に相当し、取得及び実現しやすい。そして、この光路は透過測定の最適な光路であり、この光路における測定は最も感度よいである。
具体的には、図１４を参照して、操作Ｓ１４０１において、純粋な吸収媒体を用いて予測モデルを構築することができる。モデリングするとき、上記各種類の信号形式を採用できる。以下の説明において、吸収係数を例とする。例えば、異なる濃度の特定成分を含む純粋な吸収背景媒体に対して吸光度Aciの測定を行い、背景は空気又はある固定の純粋な吸収媒体である。具体的には、吸光度Aci=lnI-lnI₀、ただし、Ｉは測定スペクトルであり、I₀は背景スペクトルである。一連の濃度に対して、一連の吸収係数μ_a,ciの値を更に取得し、μ_a,ci=A/L、Ｌは透過光路である；濃度が０である場合、μ_aは該純粋な吸収背景媒体の吸収係数に記述される。濃度値と相応的な濃度での吸収係数及び初期濃度とを比較するときの相対変化値Ri=(μ_a,ciーμ_a)/μ_aを用いて、濃度予測モデルを構築することができる。吸収係数の相対変化量と吸光度係数の相対変化量とは実質的に同じであるため、吸光度の相対変化量によって直接的に取得されることができる。
操作Ｓ１４０３において、被測定媒体の散乱非感応点における拡散スペクトルデータを取得できる。例えば、被測定媒体は背景媒体及び特定成分を含め、拡散スペクトルデータは上記各種類の信号形式を含める。例えば、散乱背景媒体／基準媒体（散乱背景媒体に初期濃度の特定成分が含まれる）に対して初期スペクトルを取得し、特定成分の濃度が変化（未知の濃度に変化する）した後で測定スペクトルを取得できる。
次に、操作Ｓ１４０５において、純粋な吸収背景媒体の吸収係数μ_a及び散乱背景媒体／基準媒体の吸収係数μ_a'（例えば、その比率）に基づいて、散乱非感応点における拡散スペクトルデータに対してプリ処理を行うことができる。プリ処理の方式は上記図１３に対して記載のプリ処理の方式と同じであってよい。散乱背景媒体／基準媒体の吸収係数μ_a'は積分球又は他の汎用な光学パラメーターの測定方法によって測定されてよく、背景は純粋な吸収背景媒体で吸光度を測定するときに同じであってよい。複数の波長の場合、それぞれの波長に対して上記処理を行って、各波長でのプリ処理の信号を取得してよい。あるいは、プリ処理せずに、例えば式（１６）に従ってシステム補正を行ってよい。
そして、操作Ｓ１４０７において、予測モデルによって、散乱背景媒体の特定成分の濃度予測値を取得できる。
上記散乱非感応点における拡散スペクトルデータを利用する実施例に類似的に、吸収非感応点における拡散スペクトルデータを利用することができる。
具体的には、図１５を参照して、操作Ｓ１５０１において、例えば、光度の変化又は相対変化という吸収非感応点におけるスペクトルデータを取得できる。そして、操作Ｓ１５０３において、吸収非感応点におけるスペクトルデータによってモデリング及び／又は予測を行うことができる。
吸収非感応点の位置に対して、例えば上記のように、予め実験によって確定してもよく（例えば、図７を参照する），あるいは、比較的に小さい値（例えば、０）によって近似してもよい。
吸収非感応点を確定した後で、該位置におけるスペクトルデータを取得するために、該位置のスペクトルを実際に検出しなくてもよく、他（少なくとも２つ）のラジアル距離での光度を測定し、その光度の相対変化量を算出することにより、吸収非感応点における値を推測できる。
上記散乱非感応点におけるデータによってモデリング及び予測を行う場合に類似的に、吸収非感応点におけるデータによってモデリング及び予測を行うとき、採用できるデータの形式は、「吸収非感応点」における絶対光度I₂、光度の絶対変化量I'=I₂-I₁、光度の相対変化量、散乱係数、散乱係数の絶対変化量、散乱係数の相対変化量又は関連量を含めるが、これらに限られない。これらの信号の間は実質的に互いに変換できる。その原因は、下記のように、光度の相対変化量が散乱係数の相対変化量に近似しており、あるいは、両者の間にある固定の係数が異なっている（すなわち、上記式（１３）又は（１４）に類似する関係がある）ためである。したがって、上記各信号形式の間の変換、プリ処理、補正に関する説明（例えば、式（１３）-（１６）を結合する説明）はここでも適用できる。
一例示によれば、吸収非感応点における光度の相対変化量を取得でき、ｗに記述する。例えば、モデリングするとき、背景媒体又は基準媒体に対して、初期スペクトルを取得し、背景媒体又は基準媒体に一連の既知濃度の特定成分を添加した後で、測定スペクトルを取得し、これにより、光度の相対変化量を取得できる。予測するとき、背景媒体又は基準媒体（その中、特定成分の初期濃度は、モデリングするときの基準媒体における特定成分の初期濃度とは同じであってもよく、異なってもよい）に対して、初期スペクトルを取得し、背景媒体又は基準媒体の特定成分の濃度が変化（未知の濃度に変化する）した後で測定スペクトルを取得し、これにより、光度の相対変化量を取得できる。測定波長で、吸収係数が散乱係数よりも非常に小さければ、ｗは該被測定媒体の散乱係数の相対変化量を表してよい（下式（２１）を参照する）。一方、測定波長で、吸収係数が大きければ、ｗを変換し、定数k(μ_a,μ_s')にかけた後で、w'=w・k(μ_a,μ_s')に変換してよい。ただし、ｋは被測定媒体の光学パラメーターに関連する定数であり、k(μ_a,μ_s')=(2μ_a+μ_s')/μ_s'
、ただし、μ_aは背景媒体又は基準媒体の吸収係数であり、μ_s'は背景媒体又は基準媒体の等価散乱係数である。w'は散乱係数の相対変化量を表してよい。
若し、モデリングに用いられる背景媒体又は基準媒体と予測するときの背景媒体又は基準媒体と同じであれば（成分組成は同じであり、基準媒体の特定成分の濃度は異なってもよい）、散乱係数の相対変化量を直接的に採用することができ、物質の濃度と共に予測モデルを構築する。若し、モデリングに用いられる背景媒体又は基準媒体と予測するときの背景媒体又は基準媒体と異なれば（特定成分の濃度が異なる以外に、同士の背景媒体は異なり、例えば、成分組成は異なる）、例えば、以下のように、モデル移植を行うことができる。例えば、モデリングするときに散乱係数の絶対変化量を採用してよい；予測するときに、散乱係数の相対変化量によって散乱係数の絶対変化量を間接的に取得し、それをモデルに入力して濃度の予測を行ってもよい。あるいは、モデリングするときに、散乱係数の相対変化量を採用してよい；予測するときに、光度の相対変化量を係数ｈにかけて、予測モデルに入力してもよく、ただし、ｈは２つの媒体の散乱係数の比率であり、
ｈ＝

、ただし、

はモデリングに用いられる背景媒体又は基準媒体の等価散乱係数を示し、

は予測するときの背景媒体又は基準媒体の等価散乱係数を示す。
ここでは散乱係数の相対変化量を例として説明するが、本発明はこれに限られない。例えば、上記他の信号形式を採用でき、これはこれらの信号の間が互いに変換できるためである。具体的な変換及びプリ処理について、上記散乱非感応点における各信号形式に対する説明を参照でき、散乱係数が吸収係数を切り替える以外に、それらは類似している。
上記実施例は例えば以下のように理解できる。
式（８）を式（３）に代入すると、吸収非感応点における光度相対変化量（すなわち、純粋な散乱情報）を取得できる：

式（２１）に示すように、吸収非感応点で測定した信号Ｓは散乱作用の影響のみを反映する。そして、該点は常に光源位置に隣接し、光源の位置に簡単化することができる。特別に、吸収が弱い波長において、μ_a値は小さく、あるいは、吸収係数が散乱係数よりも非常に小さい場合、すなわち、μ_s'>>μ_a、吸収非感応点における光度相対変化量は散乱係数又は等価散乱係数の相対変化量Δμ_s'/μ_s'を反映できる。該情報はある物質の濃度が変化した後でのそれによる散乱係数の相対変化量及び絶対変化量を測定することに適用されることができる。
ここで以下のことを理解すべきである。上記吸収非感応点における拡散スペクトルデータによってモデリング／予測を行うことに対する説明は、同様に散乱作用線の他の点における拡散スペクトルデータによってモデリング／予測を行うことにも適用できる。その原因は、散乱作用線において、全ての点の拡散スペクトルデータが基本的にいずれも媒体の散乱特性の変化による（以上のように、吸収非感応点における拡散スペクトルデータの方はより抽出しやすいだけである）ためである。
上記のように、散乱信号と吸収信号とはそれぞれの長所を有するため、散乱信号と吸収信号を綜合的に用いて濃度の予測を行うと、より正確な物質成分の検出を実現できる。特に、いくつかの特定成分（例えば、ブドウ糖）の吸収が弱くて、上記方法によって抽出した吸収信号応じてブドウ糖を直接的に予測すれば（予め構築されたブドウ糖に対する予測モデルを利用する）、機械の測定精度が非常に高い必要があり、同時に、生体を測定するとき、ランダム誤差が測定に大きく影響する。散乱信号も利用すれば、吸収信号によって取得した測定結果を一定の程度に補助し、さらに補正することができる。これは、通常、これらの特定成分（例えば、ブドウ糖）による散乱信号が吸収信号よりも大きいためである。したがって、機械の精度に対する要求は低くなる一方、生体測定のランダム誤差を耐える能力は強くなる。
本発明の実施例れによれば、例えば以下のように濃度の予測を行うことができる。
具体的には、被測定媒体の特定成分（例えば、ブドウ糖）以外の干渉成分（例えば、ヘモグロビン）に対して、その単位濃度の変化量での散乱信号を（予め）取得してよい。例えば、該干渉成分の濃度を単独に変化させ（該干渉成分を含まない背景媒体あるいは初期濃度の該干渉成分を含む背景媒体について；ここで、「背景媒体」とは、測定される干渉成分に対することであり、すなわち、このとき、該「干渉成分」は「特定成分」である）、その拡散スペクトルデータを測定し、上記のように、散乱信号を分離し、それを濃度変化値で割って、単位濃度変化量の散乱信号を取得できる。
被測定媒体（その特定成分の濃度と干渉成分とはいずれも変化してよい）に対して、散乱非感応点におけるデータ（被測定成分及び干渉成分の総吸収情報を反映する；干渉成分の吸収が強く、例えば、特定成分の吸収よりも非常に大きい場合、主に干渉成分の吸収を表す）を採用し、干渉成分の濃度予測モデル（例えば、上記のように構築する。例えば、散乱非感応点におけるデータによって構築する）に入力し、干渉成分の濃度を予測できる。ここで散乱非感応点におけるデータによって予測したが、上記のように、吸収作用線の他の点のデータによって予測してもよい。
予測された干渉成分の濃度を単位濃度変化量の散乱信号にかけることによって、被測定媒体の干渉成分の散乱信号を取得できる。
被測定媒体の拡散スペクトルデータ（例えば、綜合作用線）から、取得した干渉成分の散乱信号を差し引く。全ての干渉成分に対して上記操作を行って、それらの影響を差し引くことができる。
上記のように処理された拡散スペクトルデータによって被測定成分に対して濃度の予測を行うことができる（例えば、上記のように特定成分に対して構築する予測モデルに入力する）。ここでは、吸収非感応点におけるデータを採用でき、あるいは、吸収が弱い波長に対して、散乱非感応点以外の他の位置におけるデータを直接的に採用こともできる。この場合、特定成分の散乱作用によって濃度の予測を行う。散乱情報が強くて、高いＳＮＲの測定を実現しやすいため、濃度予測の精度は向上される。
図１６は一例示の綜合作用線、それから分離した吸収作用線及び散乱作用線を示す。具体的には、３％のｉｎｔｒａｌｉｐｉｄ溶液に対して、濃度が１００００ｍg／dＬであるブドウ糖を添加し、そのスペクトルを測定する。測定スペクトルに対して信号分離を行い、１１６０ｎｍの波長を例として、図１６の結果を得た。
したがって、全ての波長に対して信号分離を行った後で、純粋な吸収作用線及び純粋な散乱作用線を取得することができる。特に、散乱非感応点で純粋な吸収作用の情報を取得でき、それは論理的に吸収係数の相対変化量である。図１７は、３％ｉｎｔｒａｌｉｐｉｄの溶液に濃度が１８００ ｍg／dＬ、５０００ ｍg／dＬ、１００００ ｍg／dＬであるブドウ糖をそれぞれ添加した後で、１１００-１３５０帯域から抽出した純粋な吸収情報（すなわち、吸収係数の相対変化量）を示す。
理想な５０ｍＭブドウ糖による吸収係数変化量は図１８に示すようであり、３％ｉｎｔｒａｌｉｐｉｄの吸収係数は図１９に示すようである。理想なブドウ糖による吸収係数の相対変化量は図２０に示すようである。
図１７と図２０とを比較して分かるように、１１００-１３５０ｎｍ帯域で、散乱媒体を分離して取得する純粋な吸収情報と、理想な純粋な吸収媒体における透過スペクトルの吸収情報とは類似しており、両者のスペクトルモデルは互いに移植できる。
別の例示によれば、モンテカルロは２％、３％、４％ｉｎｔｒａｌｉｐｉｄ溶液の異なるブドウ糖濃度での半無限媒体の拡散スペクトルを模擬する。その中、模擬に用いられる光学パラメーターは、吸収係数、散乱係数、異方性因子和散乱係数を含み、波長範囲は１０００-１７００ ｎｍであり、ブドウ糖の濃度はそれぞれ０-１００ ｍＭであり、間隔は１０ｍＭであり、光子数は１０^８である。
まず、仮に、全ての波長で、ブドウ糖の濃度の変化が吸収係数の変化を引き起こさなければ、すなわち、散乱係数のみを影響すれば、異なる濃度での光度の模擬結果を差分すると、光度が変化しない位置を取得でき、該波長での散乱非感応点位置に記述する。３つの２％、３％、４％ｉｎｔｒａｌｉｐｉｄ溶液の散乱非感応位置は図２１に示すようである。
ここで、図６と図２１の３％ ｉｎｔｒａｌｉｐｉｄ溶液に関する結果が異なっていることを理解すべきである。これは以下の原因による。図６の結果は無限媒体の実験データに応じて取得されており、その中、３％ ｉｎｔｒａｌｉｐｉｄ溶液の配置に誤差があり、その光学パラメーターは必ずしも理論値と一致すると言えない。図２１は、ｉｎｔｒａｌｉｐｉｄの理論な光学パラメーター値を採用しており、モンテカルロ模擬プログラムに入力し、半無限媒体の模擬を行う結果である。その中、実際な実験とコンピューターのシミュレーションとの区別があり、無限と半無限との自身が異なる原因もある。
そして、ブドウ糖の濃度を変化させるとき、吸収係数及び散乱係数はいずれも変化し、真実な光度の変化を模擬する。模擬するとき、単位ｍＭ（１ｍＭ）のブドウ糖の濃度による吸収係数の変化規則及び散乱係数の変化規則は図２２に示すようであり、他の濃度での吸収係数及び散乱係数の変化量は単位濃度での変化量を濃度にかけるものであてよい。
ブドウ糖の濃度が０であるときを初期スペクトルとし、異なる濃度のブドウ糖のスペクトルに対して差分処理を行い、ブドウ糖による光度相対変化量を取得し、そして、それに対して信号分離を行い、特に、図２１の散乱非感応位置で、ブドウ糖による純粋な吸収情報を取得する。図２３に示すように、３つの媒体に対してそれぞれ抽出した純粋なブドウ糖吸収情報を比較する。
図２３から分かるように、半無限媒体を測定するとき、光源からの検出距離は散乱不感応位置において、異なる散乱媒体に対して、類似な測定情報を取得でき、その形状は純粋な吸収媒体の吸収係数の相対変化量に類似しており、簡単な線形変化により、両者のスペクトルモデルを互いに移植することができる。
本発明の実施例によれば、スペクトルデータから散乱信号及び吸収作用を抽出し、モデリング及び予測にそれぞれ用いる。特に、吸収信号は、散乱粒子の散乱媒体の測定に対する影響を除去し、測定精度を向上することができる。また、これらの吸収信号に対して構築する濃度予測モデルも、媒体の散乱特性及び散乱特性の変化によらず、したがって、これらのモデルは互いに移植でき、さらに純粋な吸収媒体で構築するモデルと汎用することができる。
本発明の実施例によれば、処理装置を提供している。図２４を参照して、該処理装置は、被測定媒体のスペクトル（例えば、ラジアル位置に沿う光度）を探知するように配置される探知器２４０１（例えば、光度の探知器）を含める。探知器２４０１は、１つ又は複数のラジアル位置に固定され、該１つ又は複数のラジアル位置のスペクトルを測定するための相応的な１つまたは複数の探知器を含め、あるいは、ラジアル位置に沿って移動し、１つまたは複数のラジアル位置のスペクトルを測定するための探知器を含める。
該処理装置はプロセッサ２４０３を更に含める。プロセッサ２４０３は、探知器２４０１が探知したスペクトル（たとえば、１つの複数の第１のラジアル位置における拡散スペクトルデータ）に応じて、１つ又は複数の第２のラジアル位置で実質的に被測定媒体の散乱特性の変化のみによる光学情報及び／又は実質的に被測定媒体の吸収特性の変化のみによる光学情報を確定するように配置されることができる。該１つ又は複数の第２のラジアル位置と上記１つ又は複数の第１のラジアル位置とは異なってもよく、同じであってもよく、部分的に同じであってもよい。
プロセッサ２４０３は、例えば汎用コンピューター、専用集積回路（AＳＩＣ）、ＦＰＧＡなどの各形式の計算設備を含める。プロセッサ２４０３は、記憶装置に記憶されるプログラム、コードセグメントなどをロードすることによって、上記のような各方法、フローに従って動作して、散乱／吸収信号の抽出、モデルの創立及び濃度予測を実現することができる。
該処理装置は、例えばマウス、キーボードなどの、ユーザの命令、データなどを入力するための入力装置２４０５と、例えばディスプレイなどの、プロセッサ２４０３の処理結果（例えば、分離した散乱信号／吸収信号、予測結果など）を出力するための出力装置２４０７と、をさらに含める。入力装置２４０５及び出力装置２４０７は組み合ってタッチパネルとして実現されることができる。
本発明の技術は、データ処理装置で実行できるアルゴリズムのプログラムを含むように実現でき、あるいは、非一時的なコンピューター読み取り可能な媒体に記憶されて提供されることができる。
本発明の技術はコンピューターの読み取り可能な媒体におけるコンピューター読み取り可能なコードとして実現されることができる。コンピューター読み取り可能な媒体は、コンピューターの読み取り可能な記録媒体及びコンピューター読み取り可能な伝送媒体を含む。コンピューター読み取り可能な記録媒体は、データをその後コンピューターシステムにより読み取る可能なプログラムとして記憶する任意のデータ記憶装置である。コンピューター読み取り可能な記録媒体の例示は、リードオンリーメモリ（ＲＯＭ）、ランダムアクセスメモリ（ＲＡＭ）、シーディーＲＯＭ（ＣＤ-ＲＯＭ）、テープ、ディスク及び光データの記憶装置を含む。コンピューター読み取り可能な記録媒体はインターネットに接続されるコンピューターシステムにおいて分布されてもよく、これにより、分散的な形式によってコンピューター読み取り可能なコードを記憶して実行する。コンピューター読み取り可能な伝送媒体は、搬送波又は信号によって伝送されることができる（例えば、インターネットを介する有線又は無線データ伝送）。また、本発明技術を実現する機能プログラム、コード及びコードセグメントは、本発明の全体構想の本分野のプログラマーにより容易に解釈されることができる。
以上、複数の実施例に本発明の複数の特徴をそれぞれ説明している。しかしながら、これは、これらの特徴が有利に結合されて使用できないことを意味しない。
以上、本発明の実施例を説明している。しかしながら、これらの実施例は説明するためものであり、本発明の範囲を限定しない。本発明の範囲は権利請求項及びその等価物により限定される。本発明の範囲を逸脱しない限り、当業者は複数の置換及び補正を行え、これらの置換及び補正は全て本発明の範囲に含まれるべきである。   Then, in operation S805, the scattering insensitive point at the target wavelength λ can be determined according to the spectrum data at the reference wavelength λr (for example, the above-mentioned overall action line). For example, the scattering insensitive point ρ * λr at the reference wavelength λr can be determined according to the spectrum data at the reference wavelength λr. As described above, since the reference wavelength λr can be selected as a wavelength at which the medium to be measured has weak absorption or a wavelength having no further absorption, the obtained integrated action line (Sλr) can be directly used as the scattering action line ( The overall action line at this time represents optical information due to the change in the concentration of the specific component in the medium to be measured with respect to the concentration in the initial state, and the absorption information due to the change in the concentration is very small or even zero. Therefore, it can be ignored), whereby a scattering insensitive point ρ * λr (for example, a zero-cross point of a change in luminous intensity or a relative change) can be obtained. Thereafter, the scattering insensitive point ρ * λ at the target wavelength λ can be determined according to ρ * λr. For example, ρ * λr can be directly used as ρ * λ, or ρ * λr can be easily calculated to obtain ρ * λ. This "simple operation" may be, for example, a linear or quadratic fit.
  Referring to equation (7), the position of the scattering insensitive point ρ * is related to the effective attenuation coefficient μeff. For the same background medium (or reference medium) (as described above, a change in the concentration of a particular component does not essentially cause a change in the position of the scattering insensitive point), for example, μeff at their different wavelengths (more specifically, In this case, estimation of the scattering insensitive point between wavelengths can be realized according to the absorption coefficient μa and the scattering coefficient μs). The mapping rules between different wavelengths can be predetermined and, as mentioned above, only relevant for the background medium (or reference medium). In a band in which the absorption of the background medium is relatively stable (for example, 1200 to 1250 nm), the absorption of adjacent wavelengths is close (in addition, since scattering is similar, the scattering insensitive point between wavelengths is approximated). Ρ * λr can be directly used as ρ * λ.
  The process shown in FIG. 8 is particularly applicable, for example, when a medium for measuring blood glucose in a living body is difficult to perform an experiment in advance. In this case, it is difficult to change the scattering / absorption coefficient of blood alone and obtain a scattering / absorption insensitive point by the processing shown in FIGS.
  According to another embodiment of the present invention, it is possible to acquire spread spectrum data at a scattering insensitive point. This acquisition may be performed, for example, by measuring the spectrum directly at the scattering insensitive point, or by measuring the spectrum at at least two positions other than the scattering insensitive point, for example, by a linear fit, The spectral data at the point can be estimated. Referring to FIG. 2, since the luminous intensity is not sensitive to the change in the scattering characteristic at the scattering insensitive point 203, the (integrated) spread spectrum data (for example, point 211) basically includes only the signal due to the change in the absorption characteristic. Including. That is, the spread spectrum data at the scattering insensitive point can be determined as optical information (for example, the value of the absorption line at the scattering insensitive point) substantially due to only the change in the absorption characteristic of the medium to be measured.
Similarly, diffusion spectrum data at an absorption insensitive point can be obtained. This acquisition is performed, for example, by directly measuring the spectrum at the absorption insensitive point, or by measuring the spectrum at at least two positions other than the absorption insensitive point, for example, by a linear fit, The spectral data at the point can be estimated. Referring to FIG. 2, at the absorption-insensitive point 207, since the luminous intensity does not respond to the change in the absorption characteristic, the (integrated) spread spectrum data (for example, point 213) basically includes only the signal due to the change in the scattering characteristic. . That is, it is possible to directly determine the optical information (for example, the value of the scattering action line at the absorption insensitive point) based on only the change in the scattering characteristic of the medium to be measured, from the diffusion spectrum data at the absorption insensitive point. . In such an embodiment, when obtaining the spread spectrum data, the scattering information and / or the absorption information is directly extracted.
  In the above embodiment, the total action line (or one or more points thereon) is separated based on the scattering non-sensitivity point and / or the absorption non-sensitivity point, and the scattering action line and / or the absorption action line (or (One or more points on it). However, the present invention is not limited to this. For example, this separation can be performed independent of scattering and absorption insensitivity points.
  Referring to FIG. 9, in operation S901, an approximate wavelength λr (for example, 1050 nm for glucose) is set to a reference wavelength for a target wavelength λ (for example, 1150 nm for glucose) for measuring the spectrum of the medium to be measured. can do. The reference wavelength λr can be selected as a wavelength at which the specific component contained in the medium to be measured has weak absorption or a wavelength at which no specific component is absorbed. Note that the scattering line at the reference wavelength λr and the scattering line at the target wavelength λ can be approximated.
  Subsequently, in operation S903, spectral data of the medium to be measured can be obtained for the target wavelength λ and the reference wavelength λr. This spectral data includes, for example, the above-mentioned change in light intensity or the relative change in light intensity. Specifically, for example, the spectra I2λr and I2λ of the medium to be measured are measured, and the spectra I1λr and I1λ in the initial state (for example, the background medium does not include a specific component or includes a specific component having a certain fixed concentration). To obtain, for example, the relative change amounts Sλr and Sλ of the luminous intensity. They can be spectral data at the reference wavelength λr and the target wavelength λ, respectively (eg, the overall action line).
  Then, in operation S905, the scattering action line and / or the absorption action line at the target wavelength λ can be determined in accordance with the spectrum data at the reference wavelength λr (for example, the above-mentioned integrated action line). As described above, since the reference wavelength λr can be selected as a wavelength at which the medium to be measured has weak absorption or a wavelength at which there is no further absorption, the acquired integrated action line (Sλr) can be directly used as the scattering action line. The scattered ray at the reference wavelength λr can be used as it is or by a simple calculation as the scattered ray at the target wavelength λ. Here, due to the closeness between adjacent wavelengths, this "simple operation" can be, for example, a linear or quadratic fit. Further, it is possible to obtain the absorption action line from the total action line (Sλ) at the target wavelength λ, excluding the estimated scattering action line, and realize the separation.
  As described above, the concentration is predicted using the data of the separated "scattering action line" or one or more points thereon, and the data of the "absorption action line" or one or more points thereon. Or they may be used comprehensively for concentration prediction.
  FIG. 10 shows a general principle of estimating a concentration based on spectral data. As shown in FIG. 10, the background medium or the reference medium (including the background medium and the specific component of the initial concentration) is provided with a series of known concentrations {C_i}, The corresponding diffusion spectrum data {I (ρ)} can be obtained. A prediction model M can be constructed from these known concentration data set X⌒ and corresponding set of spread spectrum data Y 拡 散. The person skilled in the art knows several ways of constructing the prediction model M, for example, partial least squares (PLS) regression. Then, the unknown concentration (or concentration change) C ′ of the specific component in the background medium or the reference medium (which may be different from the background medium or the reference medium at the time of modeling, as described below)._i, Corresponding spread spectrum data I ′ (ρ) (“Y”) can be obtained. The concentration (“X”) can be predicted by I ′ (ρ) and the prediction model M.
  As described above, the spread spectrum data includes, for example, appropriate data such as a change in luminous intensity or a relative change. In the case of utilizing the relative light intensity change, for example, as shown in FIG. 3, an overall action line of one cluster corresponding to each concentration (or a scattering action line and / or an absorption action line of a corresponding cluster). ) Can be obtained. It should be noted that appropriate spread spectrum data can be obtained using one or more wavelengths.
  When modeling, a spectrum of a background medium or a reference medium can be measured to be an initial spectrum, and a spectrum to which a specific component of a known concentration {Ci} is added can be measured to be a measured spectrum. Accordingly, it is possible to acquire the change information of the luminous intensity. When predicting, the spectrum of the background medium or the reference medium (the initial concentration of the specific component in the reference medium may be the same as or different from the initial concentration of the specific component in the reference medium when modeling) is similarly calculated. The spectrum can be measured as the initial spectrum, and the spectrum after the concentration of the specific component has changed can be measured as the measurement spectrum, and the luminous intensity change information can be obtained accordingly. What is predicted and obtained is a density relative value (that is, a density change amount), and an initial value (0 for a background medium; the initial density for a reference medium) is added to the density. You can get the predicted value.
  According to embodiments of the present invention, these spread spectrum data can be processed to extract scattered and / or absorbed signals. For example, this separation is performed as described above. Here, such a modeling and / or concentration prediction method is proposed. Referring to FIG. 11, in operation S1101, spread spectrum data can be obtained. For example, when modeling, obtain diffusion spectrum data (for example, light intensity change information before the specific component is added) for the background medium or the reference medium after the specific component of known concentration {Ci} has been added. When predicting, it is possible to acquire spread spectrum data (for example, light intensity change information before the specific component concentration changes) with respect to the background medium or the reference medium in which the specific component concentration has changed. Subsequently, in operation S1103, the spread spectrum data is separated and, for example, a scattered signal (for example, a scattering action line or one point or a plurality of points on the scattering action line) and / or an absorption signal (for example, an absorption action line or a point on the Multiple points). Then, in operation S1105, the separated scattered signal (for example, the scattering line or one or more points thereon) and / or the absorption signal (for example, the absorption line or one or more points thereon) are used. To perform modeling or prediction. The processing of FIG. 11 is basically the same when applied to modeling and when applied to prediction. The distinction is that when modeling, the concentration of a specific component is known, and the concentrations (X⌒) and Obtain the prediction model (M) from the spectrum data (Y⌒); at the time of prediction, the concentration (or change in concentration) of a specific component is unknown, and the predicted concentration (or Density change) (X).
  Specifically, when modeling, the separated scatter signal (ie, Y includes the scatter signal as spectral data) can be employed, and when predicting, the separated scatter signal (ie, Y (Including scattered signals). Since the signal due to scattering is always stronger than the absorption signal, modeling and predicting with the scattering signal has the advantage that the signal strength is large. However, there is a possibility that the difference in the scattering information between the wavelengths is not large, and the mixed components cannot be distinguished, so that the mixed components may not be directly used for quantitative analysis.
  Alternatively, when modeling, the separated absorption signal (ie, Y⌒ includes the absorption signal as spectral data) can be employed, and when predicting, the separated absorption signal (ie, Y is the absorption signal as spectral data) ) Can also be employed. In this case, the absorption information is directly related to the atomic or molecular structure of the substance components, and each component has its own specific wavelength absorption peak or band, which is similar to the measurement of a pure absorption medium. And can be used for quantitative analysis of mixed components. However, some components of interest have poor absorption, have low absorption signals, and are susceptible to noise.
  Alternatively, as described above, modeling and prediction can be performed using the scatter signal and the absorption signal, respectively, to obtain two prediction results. Depending on the actual environment (sensitivity of scattering / absorption at different wavelengths, etc.), one of the two results is selected or the two results are merged (eg, weighted average, scattered signal And the weight of the absorption signal is determined according to the scattering and absorption characteristics of the specific component at different wavelengths. For example, each can be determined to be 0.5), and the prediction result can be obtained.
  Alternatively, modeling and prediction can be performed using scatter and absorption signals. That is, Y⌒ includes the scatter signal and the absorption signal as the spectrum data, and Y includes the scatter signal and the absorption signal as the spectrum data.
  According to another embodiment, when modeling and / or predicting, spectral data at at least two radial positions can be used. For example, Y⌒ includes spectral data at at least two radial positions (eg, a change or relative change in light intensity), and Y includes spectral data at at least two radial positions (eg, a change or relative change in light intensity). The radial positions employed when modeling and predicting may be different. Alternatively, the slope of the scatter and / or absorption lines can be used when modeling and / or predicting. For example, Y⌒ includes the slope of the scattering and / or absorption lines as spectral data, and Y includes the slope of the scattering and / or absorption lines as spectral data.
  The prediction model M may be pre-constructed for the background medium / reference medium and the specific component, and may be stored in, for example, a database or a server. When necessary, the prediction model M may be obtained from a database or a server.
  According to the above embodiment, when measuring spectral data, some specific radial positions (eg, scattering insensitive and / or absorbing insensitive) are selected to measure the scatter signal and / or when measuring. Direct extraction of the absorption signal can be realized. In this case, for example, modeling and / or prediction can be performed as follows.
  In particular, for the scattering insensitive point, since the luminous intensity here does not respond to the change in the scattering characteristic, the measurement data basically includes only the signal due to the change in the absorption characteristic, and it is not possible to predict the concentration using the signal. In principle, interference with the measurement from changes in the scattering properties of all media can be eliminated. Then, the composition of the signal is basically the initial spectrum of the medium (that is, the spectrum when the measured component is not contained or the concentration of the measured component is a fixed initial concentration) and the variation of the absorption coefficient. The initial spectrum is known, and if removed in a mathematical way, the same signal-absorption coefficient change is obtained for different scattering media, resulting in a measurement result that is consistent with a pure absorbing medium I do. Based on this principle, the spectral prediction model constructed for scattering media having different scattering coefficients is portable, and the measurement for the target medium is based on the measured spectral data of another scattering medium or pure absorption medium. It is performed using. For example, the measurement of the constituents of living tissue can be modeled by experiments away from the living body; the measurement of the constituents of complex scattering media builds the model with simple systematic scattering media and even pure absorbing media. be able to. Thus, in practical applications, building a spectral model is simplified. In particular, for biological measurements, the method can eliminate model differences due to differences in optical parameters of each measured biological material.
  At the absorption-insensitive point, since the luminous intensity here does not respond to the change in the absorption characteristic, the measurement data basically includes only the signal due to the change in the scattering characteristic, and the change in the scattering coefficient due to the component to be measured or other factors. May be used for the detection of the concentration, or may be used for measuring the component concentration based on the scattering information.
  Hereinafter, examples will be described in which modeling / prediction is performed using spectral data at a scattering insensitive point and spectral data at an absorption insensitive point, respectively.
Specifically, referring to FIG. 12, in operation S1201, spectral data at a scattering insensitive point, such as a change in luminous intensity or a relative change, can be acquired. Then, in operation S1203, modeling and / or prediction can be performed based on the spectral data at the scattering insensitive point.
  The position of the scattering insensitive point can be determined in advance by experiment (for example, see FIG. 5) or by estimation between wavelengths as described above (for example, see FIG. 8). ).
  After determining the scattering insensitive point, it is not necessary to actually detect the spectrum at the position in order to acquire spectral data at the position, and to measure the luminous intensity at other (at least two) radial distances. Thereby, the relative change amount of the luminous intensity can be calculated, and the value at the scattering non-sensitive point can be estimated. In the radial distance, a rule that the relative change in the luminous intensity is linear or approximates linear is expressed, so that the value of another point can be estimated from any two points. In particular, if one point adopts the fluctuation reference point of the substance component, the luminous intensity of the point does not change according to the concentration, and only the initial spectrum need be recorded. In this manner, data at other difficult-to-detect positions can be estimated from data at easy-to-detect positions. For example, some scattering insensitive points are located far away from the light source, and the luminous intensity is weak, making it difficult to achieve accurate measurement. If the above method is adopted, the positions of the other two points close to the light source and the position of one point can be selected. In this case, the luminous intensity is strong, accurate measurement can be easily realized, and the other positions can be selected. The magnitude can be estimated.
  This method can also be applied to simplify the measurement of the scattering insensitive point at a plurality of wavelengths. For example, if the spectra at the scattering insensitive points corresponding to the N wavelengths are respectively measured, the wavelength dependence of the scattering insensitive points (see, for example, FIG. 6) indicates that the N wavelengths It is necessary to perform measurements at the positions of the corresponding N scattering insensitive points. For example, as shown in FIG. 26, it is necessary to move the position of the detector to realize measurement at these N positions. This is complicated.
  However, according to the above method, it is possible to fix and measure spectra at at least two positions. For example, the light source is fixed, the detector is installed at each of at least two positions, and the spectrum at the corresponding position is measured. Thus, only the wavelength emitted from the light source needs to be changed, and there is no need to move the detector. However, according to the measured spectra at the at least two positions, the spectral data at the scattering insensitive point corresponding to each wavelength can be estimated as described above. For example, as shown in FIG. 27, measurement can be performed at two points ρA and ρB for a plurality of wavelengths λ1, λ2, λ3, and λ4. If one of the points is a fluctuation reference point that is insensitive to a specific component at a specific wavelength, this point does not need to be measured at the specific wavelength, and the initial spectrum may be used. For example, in the example of FIG. 27, the point ρA is a fluctuation reference point at the wavelength λ2, and at the wavelength λ2, the point ρA does not need to be measured, and the initial spectrum may be used. As described above, it is sufficient that the detection position is only one point (the point and the fluctuation reference point at each wavelength constitute a pair of measurement positions), and this point is the fluctuation reference point at any of the N wavelengths. If not, one more measurement position must be selected for this wavelength. For example, as shown in the example of FIG. 27, it is possible to detect the point ρB, and since this point ρB is not a fluctuation reference point at any one of the plurality of wavelengths λ1, λ2, λ3 and λ4, (Meaning that these points do not need to be measured and can be simplified by S = 0) to form a measurement pair (eg, for wavelength λ2, Constitution), the S value at each scattering insensitive point can be estimated. When the point ρA is selected and one point measurement is performed, it is a fluctuation reference point of the wavelength λ2. Therefore, it is necessary to select one more measurement position for the wavelength λ2 and configure a measurement pair.
When modeling and estimating concentration using data at the scattering insensitive point, the data format that can be adopted is the absolute luminous intensity I2 at the “scattering insensitive point” (actually measured at the scattering insensitive point, or as described above. ), The absolute change in luminous intensity I '= I_Two-I₁, Relative magnitude of luminous intensity
S1 = ΔI / I = (I_Two-I₁₎/ I₁, Absorption coefficient μa_Two, The absolute change in absorption coefficient Δμa = μa_Two-μa₁, Relative change in absorption coefficient

, Absorbance A_Two
, Absolute change in absorbance

, Relative change in absorbance

Or another related amount constituted by the signal (for example, a signal obtained by linearly changing such information) (where I₁, Μa₁And A₁Are the initial luminosity (ie, the luminosity when measuring the background or reference medium), the initial absorption coefficient (ie, the absorption coefficient of the background or reference medium) and the initial extinction (ie, the background or reference medium) at the scattering-insensitive position, respectively. Medium absorbance) and I₂, Μa₂And A₂After the concentration of the component to be measured changes (after modeling, after adding a specific component of a known concentration to the background or reference medium; when predicting, after the concentration of the specific component changes to the background or reference medium) ), Which are the luminosity, absorption coefficient, and absorbance at the scattering-insensitive position). Each of the above signals is basically due to a change in absorption of a specific component (because it is data at a scattering insensitive point), and a linear conversion can be directly performed between these signals as follows.
  Specifically, the theoretical relationship between luminosity, absorption coefficient, and absorbance is:

Where L * is the average equivalent optical path at the scattering insensitive point, and for the same medium it is considered a constant;₀The luminous intensity of the light source.
For an infinite medium, the relationship (at the scattering insensitive point) is:

Therefore, for the same medium, the relative change in luminous intensity, the relative change in absorption coefficient, and the relative change in absorbance are equivalent.
  On the other hand, for a semi-infinite medium, the above relationship changes at the scattering insensitive position. However, for a fixed medium to be measured, the relative change in luminous intensity, the relative change in absorption coefficient, and the relative change in absorbance can be directly linearly converted as shown in the following equation. Is a constant of:

In addition to the relative change amount, signals of other formats can be mutually converted. For example, according to equation (13) or (14), three relationships can be realized: luminosity magnitude, absorption coefficient magnitude and absorbance magnitude, and based on initial luminosity, initial absorption coefficient or initial extinction, luminosity, The absolute change amount or the absolute value of the absorption coefficient and the absorbance can be obtained. For example, the absolute luminous intensity I at the scattering insensitive point₂Is measured or estimated, the initial luminous intensity I₁The relative light intensity change S₁= ΔI / I = (I_Two-I₁₎/ I₁Can be calculated, and the relative change amount Sμa or S of the absorption coefficient or the absorbance can be calculated by the equation (13) or (14)._ACan be obtained. Further, the relative change Sμa or S of the acquired absorption coefficient or absorbance_ABased on the initial absorption coefficient μa₁Or absorbance A₁And the absorption coefficient μa₂Or absorbance A₂Can be obtained.
  Here, it should be understood that the same signal format may be employed when modeling and predicting, or different signal formats may be employed. For example, when modeling and predicting, a relative change in luminous intensity or a relative change in absorption coefficient can be adopted. Alternatively, for example, when modeling, a relative change in luminous intensity (or another signal format) is used, but when predicting, a relative change in absorption coefficient (or another signal format) can be used. In this case, since the signals can be directly converted, the prediction model can be input by converting the relative change amount of the absorption coefficient into the relative change amount of the luminous intensity at the time of prediction.
  When a different signal format is used for modeling and prediction, the conversion need not be performed (for example, as described above, the signal format used for prediction is converted to the signal format used for modeling). At this time, there is a possibility that a large system error will occur when performing prediction. However, the system error can be estimated after obtaining the true value of the concentration. For example, the prediction error Ce and the correction coefficient k of the system are periodically obtained based on the true value of the concentration of the component to be measured, and for example, the equation (15) is obtained. )), And linearly correct the predicted value of the concentration.

Here, C_predictionIndicates the predicted concentration and C_correctionIndicates the density after correction.
That is, when modeling and predicting, any of the above signal formats can be adopted.
When the model is used for long-term prediction, if the initial signal before long time is used, the accuracy of the prediction may be reduced, because the change of the measurement background such as the movement of the machine or the change of the environment may be caused. This is because a system error may be caused. The initial signal including the initial light intensity, the initial absorption coefficient, or the initial absorbance can be updated periodically. In addition to updating the initial signal, the true value of the concentration of the component to be measured at this time can be obtained. This value can be obtained by model prediction, or it can be detected and obtained by other more accurate detection methods or machines. Each of the predicted values of the density is a density change value with respect to the true value. Alternatively, the original initial signal may be employed, but system correction is performed on the predicted value of the density, or the predicted value of the density is corrected according to the equation (15).
  Employing the above signal at the "scattering insensitive point" or another signal related thereto can realize a measurement for the specific component in the same background medium or reference medium, and can perform model conversion to perform the measurement in another background medium or reference medium. Measurement for the specific component can also be realized. For example, when measuring a living body, it is difficult and difficult to obtain spectrum data in different situations by changing the measured component and the interference component. For example, the concentrations of some components of a living body are stable in a short term, and it is difficult to obtain measurement data after a change. It is convenient to carry out modeling experiments away from the body, and if a pure absorbing medium is employed, modeling becomes more convenient. Therefore, if the conversion between the scattering medium and the scattering medium and the pure absorbing medium can be conveniently performed, the versatility of the model is enhanced and the portability is enhanced. There is also a possibility to solve the problem that there is no versatility of the model due to the difference between individuals and that the model is frequently invalidated for spectrum detection of a living body.
  Referring to FIG. 13, in operation S1301, the absorption coefficient μ of the background medium or the reference medium for constructing the (known) prediction model is described._as1, And the background medium or reference medium for prediction (different from the background medium or reference medium for modeling; here, “different” means that not only the concentration of the specific component is different but also the background medium of each other is different. , For example, the composition of the components is different)_as2Can be measured. For example, the absorption coefficient can be measured by an integrating sphere or other common optical parameter measurement method. As described above, a series of known concentrations of a particular component can be added to a background or reference medium for modeling, and corresponding spectral data can be measured and modeled. In addition, the concentration of the specific component of the background medium or the reference medium waiting for prediction can be changed, and thereby, the change information of the luminous intensity can be obtained as described above.
  Subsequently, in operation S1303, the acquired absorption coefficient μ_as1And μ_as2The spread spectrum data at the scattering insensitive point of the medium waiting for prediction can be pre-processed by (for example, the ratio). The spread spectrum data includes, for example, the above signal format. For example, according to the ratio of the absorption coefficient between two background media or reference media, pre-processing can be performed as follows.
  Specifically, if a relative change in luminous intensity, a relative change in absorption coefficient, or a relative change in absorbance is used when modeling and predicting, preprocessing can be performed as follows:

Where S_μa'Is the relative change of the absorption coefficient obtained for the prediction medium, and S_μaIs S_μa'Is the pre-processed signal obtained after performing pre-process on'; S_A'Is the relative change in absorbance obtained for the prediction medium, S_AIs S_A'Is the pre-processed signal obtained after performing pre-process on'; S_I'Is the relative change in luminosity obtained for the prediction medium, and S_IIs S_I'
Is a signal after the pre-processing acquired after the pre-processing has been performed. Then, the preprocessed signal can be input to a model obtained when the signal is modeled. If the absorption coefficient of the background or reference medium for modeling and the background or reference medium for prediction is similar or nearly the same, their distinction is mainly based on the scattering coefficient or equivalent scattering. If the coefficients are different (this can be determined, for example, by the components of the background or reference medium, for example, the differences in those components do not essentially cause a change in the absorption coefficient), the step S1301 of measuring the absorption coefficient can be omitted, This is because the coefficient in equation (16) is basically one.
  As described above, whether to convert these signals can be determined depending on whether to adopt the same signal format when modeling and predicting; or, without conversion, System corrections can be made to the predicted values.
  Alternatively, without performing the pre-processing, the difference between the absorption coefficients of the two media can be regarded as a system error, and the density predicted value can be corrected by Expression (15).
Of course, other signal formats may be employed. If a different signal format is used for modeling and prediction, as described above, the signal format used for prediction is converted into a signal format used for modeling, using Equations (13) and (14). The converted signal can be input to the prediction model. At this time, although the signals are the same but different media, there is generally a large difference in the initial signals. Therefore, a system error may occur. Similarly, system correction can be performed according to equation (15). Alternatively, it is also possible to perform a system correction on the predicted density value according to the equation (15) without converting the signal.
Alternatively, the pre-processing may be performed based on the absorption coefficient. For example, absolute luminosity I₂Is used, it is calculated as the relative change S₁= ΔI / I = (I_Two-I₁₎/ I₁The pre-processing is performed according to the equation (16), and the relative change in luminous intensity after the pre-processing can be obtained. Initial light intensity I₁To the initial luminosity I₁And the absolute luminosity after the pre-processing can be obtained. The absolute luminosity after the pre-processing can be input to a prediction model (for example, a prediction model based on the absolute luminosity). Similar processing can be performed for other signal types.
Then, in operation S1305, the predicted concentration value of the specific component in the medium waiting for prediction can be obtained by the prediction model.
  The pre-processing can be understood, for example, as follows.
  Substituting equation (7) into equation (3), one can obtain the relative change in luminous intensity at the scattering insensitive point (ie, pure absorption information):

The signal S measured at the scattering insensitive point is related only to the absorption coefficient of the medium to be measured and the amount of change in the absorption coefficient, and is not related to the scattering coefficient or the equivalent scattering coefficient. Therefore, if the scattering coefficients of the scattering media are different and the absorption coefficients are the same, the same measurement information S is obtained.
  Scattering media of different absorption coefficients (eg, μ_a1And μ_a2Change of the absorption coefficient due to the same specific component Δμ_aIs measured, the difference between the absorption information reflected by S is determined by the coefficient term 1 / μ_aAnd the coefficient is μ_a1And μ_a2Can be corrected by measuring in advance and obtaining the proportionality coefficient of both.

Thus, a spectral measurement model constructed between different scattering media can be conveniently implanted and used.
  Here, the following should be understood. The description of performing the modeling / prediction with the diffusion spectrum data at the scattering insensitive point can be similarly applied to the modeling / prediction with the diffusion spectrum data at other points of the absorption line. The cause is that the diffusion spectrum data at all points in the absorption line is basically due to the change in the absorption characteristics of the medium. (As described above, the diffusion spectrum data at the scattering insensitive point is easier to extract. Only).
  As mentioned above, in addition to the scattering media of different scattering coefficients being able to transplant the spectral models to one another, they can also be transplanted by means of a measurement model in a pure absorbing background medium. The premise is that the absorption coefficient of the pure absorption background medium is close to the absorption coefficient of the scattering medium, or the absorption coefficients of both are measured in advance, and data conversion is performed using equation (20). When constructing a measurement model with a pure absorbing medium, the optical path corresponds to a transmission measurement with L * = 1 / μa, which is easy to acquire and realize. This optical path is the optimal optical path for transmission measurement, and the measurement in this optical path is the most sensitive.
  Specifically, referring to FIG. 14, in operation S1401, a prediction model can be constructed using a pure absorbing medium. When modeling, each of the above signal types can be adopted. In the following description, an absorption coefficient is taken as an example. For example, the absorbance Aci is measured on a pure absorbing background medium containing different concentrations of a particular component, where the background is air or some fixed pure absorbing medium. Specifically, the absorbance Aci = lnI-lnI₀Where I is the measured spectrum and I₀Is the background spectrum. For a series of concentrations, a series of absorption coefficients μ_{a, ci}To obtain the value of μ_{a, ci}= A / L, L is the transmitted light path; when the concentration is 0, μ_aIs described in the absorption coefficient of the pure absorbing background medium. The relative change value Ri = (μμ) when comparing the concentration value with the absorption coefficient at the appropriate concentration and the initial concentration._{a, ci ー}μ_a) / μ_aCan be used to construct a concentration prediction model. Since the relative change in the absorption coefficient and the relative change in the absorbance coefficient are substantially the same, they can be obtained directly from the relative change in absorbance.
  In operation S1403, diffusion spectrum data at the scattering insensitive point of the medium to be measured can be obtained. For example, the medium to be measured includes a background medium and a specific component, and the spread spectrum data includes the above-described signal types. For example, an initial spectrum is obtained for a scattering background medium / reference medium (the scattering background medium contains a specific component of an initial concentration), and the measured spectrum is obtained after the concentration of the specific component changes (changes to an unknown concentration). Can be obtained.
  Next, in operation S1405, the absorption coefficient μ of the pure absorbing background medium_aAnd scattering coefficient μ of scattering background medium / reference medium_a'(For example, the ratio), preprocessing can be performed on the spread spectrum data at the scattering insensitive point. The pre-processing method may be the same as the pre-processing method described with reference to FIG. Scattering background medium / reference medium absorption coefficient μ_a'May be measured by an integrating sphere or other common method of measuring optical parameters, and the background may be the same when measuring absorbance with a pure absorbing background medium. In the case of a plurality of wavelengths, the above-described processing may be performed on each wavelength to obtain a pre-processing signal at each wavelength. Alternatively, without performing the pre-processing, the system correction may be performed according to, for example, Expression (16).
Then, in operation S1407, a predicted value of the concentration of the specific component of the scattering background medium can be acquired by the prediction model.
  Similar to the embodiment using the spread spectrum data at the scattering insensitive point, the spread spectrum data at the absorption insensitive point can be used.
  Specifically, with reference to FIG. 15, in operation S1501, for example, spectral data at an absorption non-sensitive point such as a change in luminous intensity or a relative change can be obtained. Then, in operation S1503, modeling and / or prediction can be performed based on the spectral data at the absorption-insensitive point.
  The position of the absorption-insensitive point may be determined in advance by an experiment, for example, as described above (for example, see FIG. 7), or approximated by a relatively small value (for example, 0). Is also good.
  After the absorption-insensitive point is determined, the spectrum at the position does not need to be actually detected in order to acquire spectral data at the position, and the luminous intensity at other (at least two) radial distances is measured. By calculating the relative change in the luminous intensity, the value at the absorption non-sensitive point can be estimated.
  Similar to the case where the modeling and the prediction are performed by the data at the scattering insensitive point, when the modeling and the prediction are performed by the data at the absorption insensitive point, the data format that can be adopted is the absolute luminous intensity I at the “absorption insensitive point”._Two, The absolute change in luminosity I '= I_Two-I₁, The relative change in luminous intensity, the scattering coefficient, the absolute change in the scattering coefficient, the relative change in the scattering coefficient, or the related amount, but is not limited thereto. These signals can be converted to each other substantially. The cause is that the relative change in the luminous intensity is close to the relative change in the scattering coefficient as described below, or the fixed coefficient between the two is different (that is, the above equation (13) or (There is a relationship similar to (14).) Therefore, the description regarding conversion, pre-processing, and correction between the above signal formats (for example, a description combining expressions (13) to (16)) can be applied here.
According to one example, the relative change amount of the luminous intensity at the absorption non-sensitive point can be obtained and described in w. For example, when modeling, for a background or reference medium, an initial spectrum is obtained, and after adding a series of known concentrations of certain components to the background or reference medium, a measured spectrum is obtained, thereby obtaining a photometric Can be obtained. When predicting, relative to a background medium or a reference medium (where the initial concentration of a particular component may be the same as or different from the initial concentration of the particular component in the reference medium when modeling) An initial spectrum is obtained, and a measured spectrum is obtained after the concentration of a specific component of the background medium or the reference medium changes (changes to an unknown concentration), whereby a relative change in luminous intensity can be obtained. If the absorption coefficient is much smaller than the scattering coefficient at the measurement wavelength, w may represent the relative change in the scattering coefficient of the medium to be measured (see the following equation (21)). On the other hand, if the absorption coefficient is large at the measurement wavelength, w is converted to a constant k (μ_a, μ_s'), Then w' = wk (μ_a, μ_sMay be converted to '). Here, k is a constant related to the optical parameter of the medium to be measured, and k (μ_a, μ_s') = (2μ_a+ μ_s') / μ_s'
Where μ_aIs the absorption coefficient of the background or reference medium, μ_s'Is the equivalent scattering coefficient of the background or reference medium. w ′ may represent the relative change in the scattering coefficient.
  If the background medium or the reference medium used for modeling is the same as the background medium or the reference medium when predicted (the composition of the components is the same, and the concentration of the specific component of the reference medium may be different), the scattering is performed. The relative change in coefficient can be directly adopted, and a prediction model is constructed together with the concentration of the substance. If the background medium or the reference medium used for modeling is different from the background medium or the reference medium to be predicted (besides the concentration of the specific component is different, the background media of each other is different, for example, the component composition is different), For example, model transplantation can be performed as follows. For example, when modeling, the absolute change in the scattering coefficient may be employed; when predicting, the absolute change in the scattering coefficient is obtained indirectly based on the relative change in the scattering coefficient and input to the model. Prediction of the concentration may be performed. Alternatively, when modeling, the relative change in scattering coefficient may be employed; when predicting, the relative change in luminous intensity may be multiplied by a factor h and input to the prediction model, where h is the two media. Is the ratio of the scattering coefficients of
h =

,

Indicates the equivalent scattering coefficient of the background or reference medium used for modeling,

Indicates an equivalent scattering coefficient of the background medium or the reference medium at the time of prediction.
Here, the relative change amount of the scattering coefficient will be described as an example, but the present invention is not limited to this. For example, the other signal formats described above can be employed because these signals can be converted to each other. For specific conversion and pre-processing, reference can be made to the description for each signal format at the above-mentioned scattering insensitive point, and they are similar except that the scattering coefficient switches the absorption coefficient.
The above embodiment can be understood, for example, as follows.
  By substituting equation (8) into equation (3), one can obtain the relative change in luminous intensity at the absorption-insensitive point (ie, pure scattering information):

As shown in equation (21), the signal S measured at the non-absorption sensitive point reflects only the effect of the scattering action. And the point is always adjacent to the light source position and can be simplified to the light source position. In particular, at wavelengths where absorption is weak, μ_aValue is small, or the absorption coefficient is much smaller than the scattering coefficient, i.e., μ_s'>> μ_a, The relative change in luminous intensity at the absorption-insensitive point is the relative change Δμ in the scattering coefficient or equivalent scattering coefficient._s'/ μ_s'Can be reflected. The information can be applied to measuring the relative and absolute changes in the scattering coefficient after a change in the concentration of a substance.
  Here, the following should be understood. The description for performing modeling / prediction using diffusion spectrum data at the absorption-insensitive point can be similarly applied to performing modeling / prediction using diffusion spectrum data at other points of the scattering action line. The reason is that, in the scattering action line, the diffusion spectrum data at all points are basically due to the change in the scattering characteristics of the medium (as described above, the diffusion spectrum data at the non-absorption sensitive point is easier to extract. Only).
  As described above, the scattered signal and the absorption signal have their respective advantages. Therefore, if the concentration is predicted by comprehensively using the scattered signal and the absorption signal, more accurate detection of the substance component can be realized. In particular, if the absorption of some specific components (e.g., glucose) is weak and glucose is directly predicted according to the absorption signal extracted by the above method (using a pre-established prediction model for glucose), the machine Is required to have a very high measurement accuracy, and at the same time, when measuring a living body, a random error greatly affects the measurement. If the scatter signal is also used, the measurement result obtained by the absorption signal can be assisted to a certain extent and further corrected. This is because the signal scattered by these specific components (eg, glucose) is usually larger than the absorption signal. Thus, while the demands on machine accuracy are reduced, the ability to withstand random errors in biometric measurements is increased.
  According to the embodiment of the present invention, for example, the concentration can be predicted as follows.
Specifically, for an interference component (for example, hemoglobin) other than a specific component (for example, glucose) of the medium to be measured, a scattered signal with a change amount of the unit concentration may be acquired (in advance). For example, the concentration of the interference component may be changed alone (for a background medium that does not contain the interference component or for a background medium that contains the interference component at an initial concentration; That is, at this time, the “interference component” is a “specific component”), its spread spectrum data is measured, and the scattered signal is separated and divided by the density change value as described above. In addition, a scattering signal of a unit concentration change amount can be obtained.
  For the medium to be measured (the concentration of the specific component and the interference component may both change), the data at the scattering non-sensitive point (reflects the total absorption information of the measured component and the interference component; absorption of the interference component) Is strong, for example, if the absorption is much larger than the absorption of a specific component, mainly represents the absorption of the interference component), and a concentration prediction model of the interference component (for example, constructed as described above. For example, scattering-insensitive) (Constructed from the data at the points) to predict the concentration of the interference component. Here, the prediction is made based on the data at the scattering non-sensitive point, but as described above, the prediction may be made based on the data at other points of the absorption action line.
  The scattered signal of the interference component of the medium to be measured can be obtained by applying the predicted concentration of the interference component to the scattered signal of the unit density change amount.
  The obtained scattered signal of the interference component is subtracted from the spread spectrum data of the medium to be measured (for example, a comprehensive action line). The above operation can be performed on all the interference components, and their effects can be subtracted.
  The concentration of the component to be measured can be predicted based on the spread spectrum data processed as described above (for example, input to the prediction model constructed for the specific component as described above). Here, data at an absorption insensitive point can be adopted, or data at a position other than the scattering insensitive point can be directly adopted for a wavelength at which absorption is weak. In this case, the concentration is predicted by the scattering effect of the specific component. Since the scattering information is strong and a high SNR measurement can be easily realized, the accuracy of the concentration prediction is improved.
  FIG. 16 shows an exemplary overall action line, with the absorption and scattering lines separated therefrom. Specifically, glucose having a concentration of 10,000 mg / dL is added to a 3% intralipid solution, and the spectrum is measured. The signal was separated from the measured spectrum, and the result of FIG. 16 was obtained using the wavelength of 1160 nm as an example.
  Therefore, after signal separation is performed for all wavelengths, pure absorption lines and pure scattering lines can be obtained. In particular, pure absorption information can be obtained at the scattering insensitive point, which is logically a relative change in the absorption coefficient. FIG. 17 shows the pure absorption information extracted from the 1100-1350 band after adding glucose at concentrations of 1800 mg / dL, 5000 mg / dL, and 10,000 mg / dL respectively to a 3% intralipid solution (ie, (The relative change in the absorption coefficient).
  FIG. 18 shows the ideal absorption coefficient change by 50 mM glucose, and FIG. 19 shows the absorption coefficient of 3% intralipid. The relative change in the absorption coefficient due to ideal glucose is as shown in FIG.
  As can be seen by comparing FIGS. 17 and 20, in the 1100-1350 nm band, the pure absorption information obtained by separating the scattering medium is similar to the absorption information of the transmission spectrum in the ideal pure absorption medium. And their spectral models are portable to each other.
  According to another illustration, Monte Carlo simulates the diffusion spectrum of a semi-infinite medium at different glucose concentrations of a 2%, 3%, 4% intralipid solution. Among them, the optical parameters used for the simulation include an absorption coefficient, a scattering coefficient, and an anisotropic factor sum scattering coefficient, the wavelength range is 1000-1700 nm, the glucose concentration is 0-100 mM, respectively, Is 10 mM and the number of photons is 10⁸It is.
  First, at all wavelengths, if the change in the concentration of glucose does not cause a change in the absorption coefficient, that is, if only the scattering coefficient is affected, the difference in the simulation results of the light intensity at different concentrations does not change the light intensity. The position can be obtained and described at the scattering insensitive point position at the wavelength. The scattering insensitive positions of the three 2%, 3%, 4% intralipid solutions are as shown in FIG.
  Here, it should be understood that the results for the 3% intralipid solution of FIGS. 6 and 21 are different. This is due to the following reasons. The results in FIG. 6 are obtained according to the experimental data of an infinite medium. Among them, there is an error in the arrangement of the 3% intralipid solution, and the optical parameters thereof do not always agree with the theoretical values. FIG. 21 shows the result of adopting a theoretical optical parameter value of intralipid, inputting to a Monte Carlo simulation program, and simulating a semi-infinite medium. Among them, there is a distinction between actual experiments and computer simulations, and there is also the reason that infinity and semi-infinity are different.
  When the glucose concentration is changed, both the absorption coefficient and the scattering coefficient change, simulating a true change in luminous intensity. When simulating, the rules for changing the absorption coefficient and the scattering coefficient according to the concentration of glucose in the unit of mM (1 mM) are as shown in FIG. 22, and the amounts of change in the absorption coefficient and the scattering coefficient at other concentrations are shown in FIG. May be applied to the density.
When the concentration of glucose is 0, the initial spectrum is used. Difference processing is performed on the spectra of glucose having different concentrations to obtain the relative change in luminous intensity due to glucose, and the signal is separated therefrom. At 21 scattering insensitive positions, pure absorption information by glucose is acquired. As shown in FIG. 23, the pure glucose absorption information extracted for each of the three media is compared.
  As can be seen from FIG. 23, when measuring a semi-infinite medium, the detection distance from the light source can obtain similar measurement information for a different scattering medium at the scattering insensitive position, and the shape of the pure absorbing medium can be obtained. Similar to the relative change in absorption coefficient, both spectral models can be ported to each other by a simple linear change.
  According to an embodiment of the present invention, the scattered signal and the absorption effect are extracted from the spectral data and used for modeling and prediction, respectively. In particular, the absorption signal can remove the influence of the scattering particles on the measurement of the scattering medium, and improve the measurement accuracy. Also, the concentration prediction model constructed for these absorption signals does not depend on the scattering characteristics of the medium and changes in the scattering characteristics. Therefore, these models can be transplanted with each other, and can be used as a general-purpose model constructed with a pure absorption medium. can do.
  According to an embodiment of the present invention, there is provided a processing apparatus. Referring to FIG. 24, the processing apparatus includes a detector 2401 (e.g., a luminosity detector) arranged to detect a spectrum (e.g., luminous intensity along a radial position) of the medium to be measured. Detector 2401 may be fixed at one or more radial locations and include one or more appropriate detectors for measuring the spectrum of the one or more radial locations, or along a radial location. And a detector for measuring the spectrum at one or more radial locations.
The processing unit further includes a processor 2403. The processor 2403 may substantially determine the medium under test at one or more second radial locations in response to the spectrum detected by the detector 2401 (eg, spread spectrum data at one or more first radial locations). It can be arranged to determine optical information solely due to changes in scattering properties and / or optical information substantially solely due to changes in absorption properties of the medium to be measured. The one or more second radial positions and the one or more first radial positions may be different, may be the same, or may be partially the same.
  The processor 2403 includes various types of computing equipment such as, for example, a general-purpose computer, a dedicated integrated circuit (ASIC), and an FPGA. The processor 2403 operates according to each method and flow as described above by loading a program, a code segment, and the like stored in the storage device, and realizes extraction of a scatter / absorption signal, creation of a model, and concentration prediction. be able to.
  The processing device includes, for example, an input device 2405 for inputting user commands, data, and the like such as a mouse and a keyboard, and a processing result of the processor 2403 such as a display (for example, a separated scattered / absorbed signal, a prediction signal, and the like). Output device 2407 for outputting a result or the like. The input device 2405 and the output device 2407 can be combined to be realized as a touch panel.
  The technology of the present invention can be implemented to include an algorithm program that can be executed by a data processing device, or can be provided by being stored in a non-transitory computer-readable medium.
  The techniques of the present invention may be implemented as computer readable code on a computer readable medium. The computer-readable medium includes a computer-readable recording medium and a computer-readable transmission medium. A computer-readable storage medium is any data storage device that stores data as a program that can thereafter be read by a computer system. Examples of the computer-readable recording medium include a read-only memory (ROM), a random access memory (RAM), a seed ROM (CD-ROM), a tape, a disk, and a storage device for optical data. The computer readable storage medium may be distributed in a computer system connected to the Internet, so that the computer readable code is stored and executed in a distributed format. Computer readable transmission media can be transmitted by carrier waves or signals (eg, wired or wireless data transmission over the Internet). Also, the functional programs, codes, and code segments that implement the technology of the present invention can be easily interpreted by a programmer in the field of the present invention with the overall concept of the present invention.
  As described above, a plurality of embodiments each describe a plurality of features of the present invention. However, this does not mean that these features are advantageously combined and cannot be used.
The embodiments of the present invention have been described above. However, these examples are illustrative and do not limit the scope of the invention. The scope of the invention is defined by the appended claims and their equivalents. Those skilled in the art can make a plurality of substitutions and corrections without departing from the scope of the present invention, and all these substitutions and corrections should be included in the scope of the present invention.

ただし、ρ_mとρ_nは任意の異なる径方向位置、例えばρ_I、ρ_Oとρ_Rのうち任意の２つを示す；ΔI(ρ_m, C, ΔN)は特定成分濃度Cが固定の場合にρ_mでの干渉要因ΔNによる光強度の変化を示し、ΔI(ρ_n, C, ΔN)は特定成分濃度Cが固定の場合にρ_nでのΔNによる光強度の変化を示す。
実際の測定過程では、測定する成分の濃度変化以外、拡散反射光の変化を引き起こす干渉要因の変化もある。測定する成分の濃度がΔC変化し、干渉要因がΔN変化するとき、以下のようになる。

ただし、ρ_iは任意の径方向位置、例えばρ_I、ρ_Oおよびρ_Rのいずれか一つを示す；ΔI(ρ_i, ΔC, ΔN)はρ_iでの濃度変化ΔCおよび干渉要因ΔNによる光強度変化を示し、ΔI(ρ_i, C, ΔN)はρ_iでの干渉要因ΔNによる光強度変化を示し、ΔI(ρ_i, ΔC, N)はρ_iでの濃度変化ΔCによる光強度変化を示す。
式（22）によって、任意の二つ径方向位置（例えば、ρ_I、ρ_Oおよびρ_Rのいずれか二つ）でのスペクトルデータを以下の差分処理を行うことができる。

式（24）から分かるように、このような差分処理によって、コモンモード干渉によるノイズ信号を効果的に減少又は差し引くことができ、測定する成分濃度（ΔC）だけに関する有用な信号（ΔI(ΔC)）を得る。
以下の説明においては主としてρ_I、ρ_Oおよびρ_Rのいずれか二つに対して説明するが、ここで、式（24）から分かるように、このような差分処理は任意の二つ径方向位置ρ_mおよびρ_nに適用できることを留意すべきである。
また、任意の二つ径方向位置ρ_mおよびρ_nで、コモンモード干渉によるノイズ信号の間の比例定数ηはあらかじめ推定できるものである。実際の測定では、この比例定数を直接に採用して両位置での光強度絶対変化量に対して差分処理を行うことができ、即ち、測定する成分の濃度（ΔC）だけに関する有用な信号（ΔI(ΔC)）を得ることができる。
以下、無限媒体における拡散方程式の定常解でηの表現式を推定し、この理論に基づいて比例定数ηのサンプル推定方法を与える。
無限媒体において一つ点光源の場合に対する光束Φの解は下記である。 ・

ただし、ρは検出器と光源との間の径方向距離である；λは光源から発されるプローブ光の波長である；μ_aは吸収係数である；μ_s'は等価散乱係数であり、 (1-g)μ_sと定義され、gは異方性因子である；μ_sは散乱係数である；Dは光子の拡散係数であり、

；μ_effは有効減衰係数であり、

。したがって、式（２５）は下記のように記述することができる。

入射光が媒体に入った後に、光子が媒体における粒子と相互作用を発生した後に出射されて拡散反射光を得ており、一般に拡散反射エネルギー変化を引き起こす要因は主で下記の三種類に分けることができる：（１）被測定媒体の光学特性の変化；（２）入射光源のドリフト；（３）検出器状態のドリフトなど。そのうち、入射光が媒体に入った後に、光子が媒体における粒子と衝突し、一部の光子が粒子に吸収されて損失し、他の部分の光子が散乱され、被測定媒体の光学特性の変化は吸収効果と散乱効果の総合的な作用の結果である。被測定媒体の吸収係数及び散乱係数などの光学特性の変化を引き起こす要因は、主で被測定媒体における測定する成分の濃度変化、干渉成分濃度の変化及び温度の変化などを含む。上記の拡散反射エネルギーの変化を引き起こす要因に、被測定媒体における測定する成分の濃度変化の測定だけが希望されるものであり、他の影響要因による拡散反射光エネルギー変化は減少又は差し引きすべきである。
人体組織中のブドウ糖濃度変化を例として、無限媒体における拡散方程式の定常解によって、血糖濃度が変化ΔC_gするの場合に、同一径方向位置で血糖濃度変化による光束Φ(ρ)の変化量ΔΦ(ρ, ΔC_g)は以下である：

ただし、

式（６）から分かるように、ある一つの波長で、光束の変化量ΔΦ(ρ, ΔC_g)は径方向距離ρの関数である。
浮動基準位置の定義によって、被測定物による被測定媒体における光源から離れた異なる位置の光強度の変化率が最も小さい受光点、即ち特定成分例えば血糖の濃度変化に対して敏感ではない径方向位置が、浮動基準位置である。そのために、理想的な場合に、血糖の濃度変化ΔC_gだけがあっていかなる干渉要因がないとき、ある一つの波長で、無限媒体における拡散方程式の定常解によって、血糖濃度変化の浮動基準位置ρ_Rに下記の感度Sen_g(ρ_R)がある：

式（２８）と式（２９）を（３０）に代入して得られる浮動基準位置は以下である：

この位置で、血糖濃度変化による光束Φ(ρ_R)の変化量ΔΦ(ρ_R, ΔC_g)は０（ゼロ）である。そして、実際の測定過程では、浮動基準位置ρ_Rでの拡散反射光の変化が背景干渉変化によるものであり、血糖濃度変化に関連しない、つまり、

通常∂μ_a/∂C_gは∂μ_s'/∂C_gに比べて１〜２オーダー低くなるため、式（２９）を式（２７）に代入して近似的に得ることができる：

これによって得られる拡散反射光の変化率は下記である：

式において、∂μ_s'/∂C_gはブドウ糖濃度変化による等価散乱係数の変化率である。通常、ある一つの固定の母液モデルに対して、等価散乱係数に対するブドウ糖濃度の変化の影響が定数である。例えば、異なる濃度のIntralipid溶液モデルに対して、∂μ_s'/∂C_gは下記のように表すことができる：

皮膚（水＋ポリスチレン）モデルに対して、∂μ_s'/∂C_gは下記のように表すことができる：

ただし、ｍ値は、図３３に示すように（Matthias Kohl, Matthias Essenpreis and Mark Cope, The influence of glucose concentration upon the transport of light in tissue-simulating phantoms）、Mie理論によって計算された波長変化による散乱係数の変化率である。図中の２つ実線曲線はそれぞれ皮膚（水＋ポリスチレン）モデルにおいて、ブドウ糖濃度が85mM/Lと144mM/Lときの散乱係数μ_s変化の曲線を示しており、それを直線にフィッティングする傾きがそれぞれ-1.569*10^-7及び-1.5*10^-7であり、後のシミュレーションは50、100、150mMの三つの異なる勾配を採用して行われるものであるため、それぞれ近似的な傾きを選択して計算を行う。
これによって、図５０に示すように、ブドウ糖濃度変化による拡散反射光の変化率dΦ/Φは径方向距離ρの（略線形）関数であると近似的に考えられる。
実際の測定では、光強度Iと光のエネルギー束密度Φの関係は固定倍数の関係であり、光のエネルギー束密度の相対変化量は光強度の相対変化量に近似的に等価し、即ち、

。そのために、測定位置の変化による

の変化も線形に近似される。
したがって、以下のように異なる位置間の比例定数ηを推定することができる。
同一影響要因ΔXで、ΔI(ρ)/I(ρ)がρの線形関数を利用し、先に第一の径方向位置における光強度相対変化量ΔI(ρ_m, ΔX)/I(ρ_m)によって、第二の径方向位置における光強度相対変化量ΔI(ρ_n, ΔX)/I(ρ_n)を推定するようにして、両者の比率をξと記し、それが径方向位置の選択に関するものであり、下記の式（Ｓ−１）で示される。

(S-1)

式（Ｓ−１）において、
ρ_Rはこの要因作用の非敏感位置である。例えばブドウ糖が変化する場合、この位置がブドウ糖測定の浮動基準位置である。特定の被測定物および特定の被測定媒体に対して、
ξが相対的な固定の位置であることが証明されている。そのために、二つの測定位置
ρｍ及びρnが固定された後、ξの値が１つの固定定数値である。これから分かるように、ξの値はあらかじめ実験によって推定することができる。
式（Ｓ−１）を変形した後、下記の式（Ｓ−２）を得ることができる。

(S-2)
そして、

(S-3)
式（Ｓ−２）及び（Ｓ−３）から分かるように、あらかじめξの値を推定した後に、式（Ｓ−３）に代入した後、比例定数ηの値を得ることができ、ηを式（３）に代入して測定する成分濃度（ΔC）に関する有用な信号（ΔI(ΔC)）を得ることができる。
実際の測定過程に拡散反射光エネルギーの変化を引き起こす影響要因ΔNを大きく２種類に分けて討論を行う：一種類は、被測定媒体において干渉成分濃度又は測定温度による光学特性の変化である；もう一種類は、測定システムにおいて光源ドリフト又は検出器状態ドリフトなどである。
（１）被測定媒体において干渉成分濃度又は測定温度による光学特性の変化
干渉成分濃度又は測定温度が変化する場合、被測定媒体の光学特性の変化を引き起こすことになる。温度変化を例として、温度の変化が分子の振動・回転状態及びエネルギー遷移確率を変化させるため、異なる温度下で物質のモル吸光係数が若干異なることになる。同時に、温度の変化は、吸収物質の濃度がそれに伴って変化することを引き起こすことになり、これは以下のためである：温度上昇が分子間の化学結合の結合程度を増加することになって、同一分子の隣接分子数が増加するようになり、物質の密度が大きくなる；しかしながら、温度の上昇も分子間の距離を大きく増加させ、物質の密度を小さくすることになる。両者の総合効果は、温度による物質濃度の変化規則を決めている。血糖濃度を相対的に一定C_gに保持し、温度変化ΔTだけある場合、同一径方向位置で引き起こされる光束Φ(ρ)の変化量ΔΦ(ρ, C_g, ΔT)は、下記の通りである。

式（２８）及び式（２９）を式（３７）に代入して下記の式（３８）を得ることができる。

ただし、

と記される。
光源から離れた径方向距離がρ_I及びρ_Oの二つの位置をそれぞれ浮動基準内側測定位置及び外側測定位置として取得し、式（３８）によって、浮動基準内側測定位置ρ_Iと浮動基準位置ρ_Rでの温度変化による光束変化量の比率、及び浮動基準外側測定位置ρ_Oと浮動基準位置ρ_Rでの温度変化による光束変化量の比率は、それぞれ下記の通りである。

生体組織中に７０％程度の水を含むため、生体組織近赤外スペクトルに対する温度はかなりの程度水のスペクトルの温度特性に関連する。図３４に示すのは、Jensenたちが実験によって得られた３２℃〜４２℃下での水モル吸光係数ε_w(λ)と３０℃下でのε_w(λ)の間の差曲線図（Peter Snor Jensen, Jimmy Bak, Stenfan Andersson-Engels, Influence of temperature on water and aqueous glucose absorption spectra in the near- and mid-infrared regions at physiologically relevant temperatures, Applied Spectroscopy, 2003, 57(1):28-36）である。１４４０ｎｍ、１７８０ｎｍ、２１８０ｎｍ、２７５０ｎｍ、４９００ｎｍ、５３００ｎｍ、および６３００ｎｍで温度の変化に敏感ではないこと以外、他の波長でε_w(λ)が温度の変化に伴って規則的に変化する。そのために、人体体温変化の範囲内（約３５℃〜４０℃）の各波長下で、温度によるモル吸光係数の変化率∂ε_w(λ)/ ∂Tは定数であるが、異なる波長に対してこの定数が異なる値を取ると近似的に考えられる。これによって、各波長下での温度による吸光係数の変化率∂μ_a(λ)/ ∂Tも定数に近似される。類似的に、陳韻たちは、２℃を間隔にして、温度範囲が３０℃〜４０℃の水サンプルをスペクトル測定実験を行うことによって、図３５に示す異なる温度下での水と３０℃下での水の間の吸光度変化値曲線を得ており、１５２５、１８３２、および２０６０ｎｍでの吸光度変化量と温度の間の線形関係式（陳韻,近赤外非侵襲的血糖測定−基準波長浮動基準法の研究：「博士学位論文」,天津,天津大学,２００９）を得ている。図からも分かるように、各波長下で、吸光度の変化量と温度の間は線形関係に近似する。水は純粋な吸収媒体であるため、同じ結論、即ち各波長下での温度による吸光係数の変化率∂μ_a(λ)/ ∂Tが定数に近似すると考えることを得ることができる。
Lauferたちは、インビトロ皮膚サンプル実験を採用し、２５℃〜４０℃の範囲内に人体真皮層及び皮下組織と温度影響の関係を研究していた（Jan Laufer, et al., Effect of temperature on the optical properties of ex vivo human dermis and subdermis, Phys. Med. Biol.,1998, 43: 2479-2489）。実験結果は、温度変化による真皮層の等価散乱係数の変化率が(4.7±0.5)×10^-3℃^-1であり、温度変化による皮下組織の等価散乱係数の変化が(-1.4±0.28) ×10^-3℃^-1であることを示している。そのために、人体体温変化の範囲内（約３５℃〜４０℃）で、温度変化による等価散乱係数の変化率∂μ_s'/ ∂Tが定数に近似する。
従って、式（３９）及び式（４０）から分かるように、浮動基準内側測定位置ρ_I、
浮動基準位置ρ_R及び浮動基準外側測定位置ρ_Oが確定した場合、同一波長下で温度変化による光束の変化量の比率ΔΦ(ρ_I, C_g, ΔT)/ΔΦ(ρ_R, C_g, ΔT)及びΔΦ(ρ_O, C_g, ΔT)/ΔΦ(ρ_R, C_g, ΔT)はいずれも定数であり、それぞれη₁とη₂を記述する。即ち：

そのために温度変化による拡散反射光強度の変化量はコモンモード干渉とすることができる。そのうち、光学パラメータが既知の被測定媒体に対して、式（３９）及び式（４０）によって定数η₁とη₂を計算することができる；光学パラメータが未知の被測定媒体に対して、測定して得られる拡散反射スペクトルを採用して、光学パラメータを再構成する方法によって、被測定媒体の光学パラメータを算出することができ、さらに式（３９）及び式（４０）によって定数η₁とη₂を計算し、或は血糖濃度が相対的に一定に保持される場合で、温度変化時の拡散反射光の変化量を繰り返し測定し、式（４１）及び式（４２）によって定数η₁とη₂の値を計算する（例えば、複数回の測定の平均値を取る）。
実際の測定過程では、ブドウ糖濃度がΔC_g変化する同時に測定温度がΔT変化する場合、同一の径方向位置でこの二つ要因による光束Φ(ρ)の変化量ΔΦ(ρ, ΔC_g, ΔT)は下記の通りである。

ただし、ΔΦ(ρ, ΔC_g, T)は関心のある測定待ちの有用な信号であり、ΔΦ(ρ, C_g, ΔT)は径方向位置に関するコモンモード干渉信号である。
次に式（３２）及び（４３）によって、浮動基準内側測定位置ρ_I、浮動基準位置ρ_R及び浮動基準外側測定位置ρ_OでΔC_gとΔTとによる光束Φ(ρ)の変化量ΔΦ(ρ_I, ΔC_g, ΔT)、ΔΦ(ρ_R, ΔC_g, ΔT)及びΔΦ(ρ_O, ΔC_g, ΔT)は、それぞれ下記の通りである。

式（４１）で式（４４）と（４５）を重み付け差分演算して下記の式を得ることができる。

式（４７）から分かるように、温度変化による拡散反射光変化のコモンモード干渉量は、浮動基準内側測定位置ρ_I及び浮動基準位置ρ_Rでの拡散反射光変化量の差分演算によって除去され、血糖濃度の変化のみに関する有用な信号を得ることができる。
類似的に、式（４２）、（４５）及び（４６）によって、浮動基準外側測定位置ρ_O及び浮動基準位置ρ_Rでの拡散反射光変化量の差分演算で同様に温度変化による拡散反射光変化のコモンモード干渉量を除去することができる：

式（４７）及び（４８）は、それぞれ浮動基準内側測定位置ρ_Iでの信号と浮動基準外側測定位置ρ_Oでの信号を採用して浮動基準位置ρ_Rでの信号を結合し、血糖濃度の変化情報のみに関する有用な信号を効果的に得ており、コモンモードノイズの干渉を差し引いている。
式（４１）及び（４２）から分かるように、浮動基準内側測定位置ρ_Iと浮動基準外側測定位置ρ_Oが確定した場合、同一波長下で温度変化による二つの測定位置での光束の変化量の比率ΔΦ(ρ_I, C_g, ΔT)/ΔΦ(ρ_O, C_g, ΔT)も定数であり、η₃と記する。

即ち：

そして、式（４４）、（４６）及び（５０）によって、浮動基準内側測定位置と外側測定位置での測定信号を差分演算して下記の式を得る。

式（５１）から分かるように、浮動基準内側測定位置ρ_Iと外側測定位置ρ_Oでの拡散反射光変化量の差分演算によって、同様に温度変化による拡散反射光変化のコモンモード干渉量を除去し、血糖濃度変化のみに関する有用な信号を得るという目的を達成することができる。なお、図３１から分かるように、血糖濃度変化による浮動基準内側測定位置ρ_Iと外側測定位置ρ_Oでの拡散反射光の変化量の方向は反対になり、式（５１）における差分演算方法を採用することは、微弱な有用な信号の絶対値も増加して、測定待ち信号の特異性を向上し、より正確な測定結果を得ている。
被測定媒体に干渉成分濃度変化によるコモンモード干渉信号は、類似的な方法を採用して差し引くことができる。
（２）測定システムにおいて光源ドリフト又は検出器状態ドリフト
入射光源の光強度がドリフトする、または拡散反射光を検出するための検出器状態がドリフトする場合は、いずれも拡散反射光強度値の変化を引き起こすことになる。入射光源の光強度がドリフトすることを例として、血糖濃度を相対的に一定C_gに保持し、入射光源の光強度がΔF倍変化する場合、同一径方向位置に対して引き起こされる光束Φ(ρ)の変化量ΔΦ(ρ, C_g, ΔF)は下記の通りである。

ただし、Φ₀(ρ)はこの測定位置での拡散反射光強度の初期値を示す。光源から離れた径方向距離がρ_Iとρ_Oの二つの位置をそれぞれ浮動基準内側測定位置及び外側測定位置として取り、式（５２）によって、浮動基準内側測定位置ρ_Iと浮動基準位置ρ_Rで入射光源の光強度のドリフトによる光束変化量の比率、及び浮動基準外側測定位置ρ_Oと浮動基準位置ρ_Rで入射光源の光強度のドリフトによる光束変化量の比率は、それぞれ下記の通りである。

式（５３）と式（５４）も任意の二つの測定位置に拡張することができる。式を変形し
て分かるように、任意の測定位置での光強度相対変化量

は全部同じであり、１つの固定値と見なすことができ、即ち図５０において、光源ドリフト干渉だけある場合、その作用線は１つ横軸に平行な直線であり、このとき式（Ｓ−３）におけるξの値は約１になって、式（Ｓ−３）を式（Ｓ−４）に簡略化する。即ち、

(S-4)
図５１は、ｉｎｔｒａｌｉｐｉｄ ３％溶液に対して拡散反射光を測定する結果である。拡散光の出力電力を変更して光源のドリフトをシミュレーションし、五回連続して変更した後に、三つの異なる測定位置を見つけることができ、その拡散反射光強度の相対変化量が一貫性のある現象を呈し、即ちこのときξの値は約１と記することができる。
浮動基準内側測定位置ρ_I、浮動基準位置ρ_R及び浮動基準外側測定位置ρ_Oが確定した場合、各測定位置での拡散反射光強度の初期値が既知で確定であるため、同一波長下で入射光源の光強度のドリフトによる光束の変化量の比率ΔΦ(ρ_I, C_g, ΔF)/ΔΦ(ρ_R, C_g, ΔF)及びΔΦ(ρ_O, C_g, ΔF)/ΔΦ(ρ_R, C_g, ΔF)は、いずれも定数であり、それぞれη₄とη₅を記し、即ち下記の式がある。

そのために、入射光源の光強度のドリフトによる拡散反射光強度の変化量は、コモンモード干渉とすることができる。ただし、η₄およびη₅の値は、血糖濃度が相対的に一定に保持されるときに、温度が変化するときの拡散反射光の変化量を繰り返し測定し、式（５５）と（５６）によって計算して得られる。
実際の測定過程においては、ブドウ糖濃度がΔC_g変化すると同時に入射光源の光強度値がΔF倍ドリフトする場合、同一の径方向位置でこの二つ要因による光束Φ(ρ)の変化量ΔΦ(ρ, ΔC_g, ΔF)が下記の通りである。

実際の測定過程では、ΔFが10^-3〜10^-2オーダーであり、乗積

は無視可能である。式（５７）は下記のように記することができる。

ただし、ΔΦ(ρ, C_g, ΔF)は径方向測定位置に関するコモンモード干渉信号であり、ΔΦ(ρ, ΔC_g, F)は関心のある測定待ちの有用な信号である。
そして式（３２）及び（５８）によって、浮動基準内側測定位置ρ_I、浮動基準位置ρ_R及び浮動基準外側測定位置ρ_OでΔC_gとΔFとによる光束Φ(ρ)の変化量ΔΦ(ρ_I, ΔC_g, ΔF)、ΔΦ(ρ_R, ΔC_g, ΔF)及びΔΦ(ρ_O, ΔC_g, ΔF)は、それぞれ下記の通りである。

式（５５）で式（５９）と（６０）を差分演算して、下記の式を得ることができる。

式（５９）から分かるように、入射光源の光強度のドリフトによる拡散反射光変化のコモンモード干渉量は、浮動基準内側測定位置ρ_Iと浮動基準位置ρ_Rでの拡散反射光変化量の差分演算によって除去され、血糖濃度変化のみに関する有用な信号を得ることができる。
類似的に、式（５６）、（６０）及び（６１）によって、浮動基準外側測定位置ρ_O和と浮動基準位置ρ_Rでの拡散反射光変化量の差分演算で同様に入射光源の光強度のドリフトによる拡散反射光変化のコモンモード干渉量を除去することができる。

式（６２）及び（６３）は、それぞれ浮動基準内側測定位置ρ_Iでの信号と浮動基準外側測定位置ρ_Oでの信号を採用して浮動基準位置ρ_Rでの信号を結合して、血糖濃度変化情報のみに関する有用な除法を効果的に得ており、コモンモードノイズの干渉を差し引いている。
式（５５）及び（５６）から分かるように、浮動基準内側測定位置ρ_Iと浮動基準外側測定位置ρ_Oが確定した場合、同一波長下で入射光源の光強度のドリフトによる二つの測定位置での光束の変化量の比率ΔΦ(ρ_I, C_g, ΔF)/ΔΦ(ρ_O, C_g, ΔF)も定数であり、η₆と記する。

即ち：

そして、式（５９）、（６１）及び（６５）によって、浮動基準内側測定位置と外側測定位置での測定信号を差分演算して下記の式を得る。

式（６６）から分かるように、浮動基準内側測定位置ρ_Iと外側測定位置ρ_Oでの拡散反射光変化量の差分演算によって、入射光源の光強度のドリフトによる拡散反射光の変化のコモンモード干渉量を除去し、血糖濃度変化のみに関する有用な信号を得るという目的を同様に達成することができ、かつ、浮動基準測定方法の普遍性を向上し、微弱な有用な信号の絶対値を増加している。
拡散反射光強度を検出するための検出器状態ドリフトによるコモンモード干渉信号は、類似的な方法を採用して差し引くことができる。
これから分かるように、操作５０３においては、第一と第二の径方向位置でのスペクトルデータを差分処理しており、２種類の異なる干渉要因が式（２４）に示すような重み付け差分によってコモンモード干渉信号を除去することができる。ほかの異なる波長下で測定された拡散反射光信号を類似的な方法で修正して、重み付け差分処理された各波長下での有効信号ΔΦ(λ_i, C_g)を得ることができる。
本開示の実施例によれば、異なる受信方式を採用して異なる位置でのスペクトル信号を検出することができる。
同一被測定媒体の異なる被測定部位、異なる測定波長または異なる被測定媒体の変化に伴って浮動基準位置のオフセットがあまり大きくない場合、以下のように異なる位置での拡散反射スペクトルを抽出することができる。
１）図３６（ａ）に示すように、光源からの浮動基準内側の位置（図３１中のエリアＡ）でのスペクトル信号を測定点として受信し、浮動基準位置（図３１中のエリアＢ）でのスペクトル信号を参考点として受信する；
２）図３６（ｂ）に示すように、絶対変化率が最も小さい受光点、即ちＢ点を浮動基準位置として選択し、変化率の局部的な極大値の受光点、即ちＣ点を測定点として選択する；
３）図３６（ｃ）に示すように、光源からの浮動基準内側の位置（図３１中のエリアＡ）、浮動基準位置（図３１中のエリアＢ）及び光源からの浮動基準外側の位置（図３１中のエリアＣ）でのスペクトル信号を同時に受信し、浮動基準内側と外側のスペクトル信号を重み付け差分処理する。
同一被測定媒体の異なる被測定部位、異なる測定波長または異なる被測定媒体の変化に伴って浮動基準位置のオフセットが大きくて浮動基準位置を確定しにくい場合、以下のように異なる位置での拡散反射スペクトルを抽出することができる。具体的に，同一測定個体の異なる測定部位、異なる波長又は異なる測定個体に対して、光学パラメータの相違が浮動基準位置の確定に大きく影響するため、図３０に示すように、測定部位、測定波長の変化に伴って，浮動基準位置が相応的に変化する。これによって、図 ３６（ｄ）に示すように、光源からの浮動基準内側と外側とが同じノイズ情報を含む特征を利用して，浮動基準内側の受信半径を適当に縮小し、浮動基準外側の受信半径を増大して、各波長或は各部位での浮動基準位置がいずれも含まれないことを保証して、径向半径が浮動基準位置より小さい（図 ３１におけるエリアA）及び浮動基準位置より大きい（図 ３１におけるエリアC）拡散反射光をそれぞれ受信することによって，浮動基準位置の内外両側のスペクトルに対して重み付け差分分析計算をする。
図３７(ａ)には本開示の実施例による光ファイバプローブ構造を模式的に示している。図３７に示すように、この光ファイバプローブ１０００はクラッドに被覆された複数の光ファイバ束１００１、１００３、１００５及び１００７を含むことができる。光ファイバ束毎に1本又は複数本のファイバを含むことができる。その中、光ファイバ束１００１が光源からの入射光を案内するために用いられ、光ファイバ束１００３、１００５及び１００７が被測定媒体からの拡散反射光を案内するために用いられる。より具体的に、光ファイバ束１００３が浮動基準位置内側の径向位置からの拡散反射光を案内するために用いられ、光ファイバ束１００５が浮動基準位置からの拡散反射光を案内するために用いられ、光ファイバ束１００７が浮動基準位置外側の径向位置からの拡散反射光を案内するために用いられ、これらの光ファイバ束はN端から集束する。光ファイバ束１００１に案内された入射光はM端から出射することができ、かつ、光ファイバ束１００３、１００５及び１００７はM端から拡散反射光を受信することができる。これによって，M端は光ファイバプローブ１０００の検知端面と呼ぶことができる。
ここで留意されたいことは、ここに記載の”光ファイバ束”はこれらの機能による論理的な区画である。物理的には、すべてのファイバが混在して、明確なグループ分けがない可能性がある。
なお，図３７（ａ）には四つの光ファイバ束が示されているが，本開示がこれに限定されない。例えば、より多い、又はより少ない光ファイバ束を含んでもいい。そして，これらの光ファイバ束の配列も図３７（ａ）に示すレイアウトに限定されない。例えば、各光ファイバ束中の光学がクラッド内に絡み合うことまでできる。
図３７（ｂ）−３７（ｅ）は本開示の異なる実施例の光ファイバプローブのM端での断面図をそれぞれ模式的に示している。図の中、各円形パターンは光ファイバ束におけるファイバの端面を示すことができる。
図３７（ｂ）に示すように、入射光を案内するための光ファイバ束１００１は、ほぼ中心に位置することができる。光ファイバ束１００３は光ファイバ束１００１を回ってその周囲に設置することができ、光ファイバ束１００７は光ファイバ束１００１を回って、相対的に光ファイバ束１００１から離れるように設置することができる。また、光ファイバ束１００５は光ファイバ束１００１を回って、光ファイバ束１００３と１００７との間に設置することができる。異なる被測定物の浮動基準位置の差異によって、異なるサイズの光ファイバプローブを設計することができる。
実際に測定する場合には、光ファイバ束１００５の端面が浮動基準位置（もし存在し且つ確定する、或はそのおおよその範囲を分かる）にほぼ合わせ、光ファイバ束１００３、１００５和１００７における拡散反射光信号（即ち、浮動基準位置及び浮動基準位置内側と外側位置でのスペクトル信号）を抽出することができるように、光ファイバプローブ１０００を放置する。或は、光ファイバ束１００３及び１００７における拡散反射光信号（即ち、浮動基準内側と外側のスペクトル信号；例えば、浮動基準位置が正確に確定されていない場合或は光ファイバ束１００５の端面が浮動基準位置のおおよそのエリアに大略に合わせられて浮動基準位置に正確に合わせられていない場合）、又は光ファイバ束１００３及び１００５における拡散反射光信号（即ち、浮動基準内側と浮動基準位置でのスペクトル信号）、又は光ファイバ束１００５及び１００７における拡散反射光信号（即ち、浮動基準位置と浮動基準外側のスペクトル信号）だけを抽出しても良い。
図３７（Ｃ）は光ファイバ束１００７を含めず、光ファイバ束１００１、１００３及び１００５を含む配置を示している。このような配置で、浮動基準位置内側と浮動基準位置のスペクトル信号を受信することができる。
図３７（ｄ）は光ファイバ束１００５を含めず、光ファイバ束１００１、１００３及び１００７を含む配置を示している。このような配置で、浮動基準位置内側と浮動基準位置外側のスペクトル信号を受信することができる。
図３７（ｅ）は光ファイバ束１００３を含めず、光ファイバ束１００１、１００５及び１００７を含む配置を示している。このような配置で、浮動基準位置と浮動基準位置外側のスペクトル信号を受信することができる。
通常、浮動基準位置に対する光ファイバ束１００５の端面と光ファイバ束１００１の端面の間の距離は大体確定的な数値（上記の配置に、光ファイバ束１００５の端面は光ファイバ束１００１の端面を回る所定半径の円形状に現れる）である；ほかの光ファイバ束１００３／１００７の端面と光ファイバ束１００１の端面の間の距離は一定の範囲（上記の配置に、光ファイバ束１００３／１００７の端面は光ファイバ束１００１の端面を回るリング形状に現れる）を覆うことができる。
ここで留意されたいことは、図３７（ｂ）〜３７（ｅ）において、光ファイバ束１００３、１００５及び１００７における各光ファイバの端面を、光ファイバ束１００１を回って略円形状又はリング形状に緊密に配列するように示しているが、本開示はこれに限られない。例えば、これらは緊密に配列されなく、まばらに配列されても良い；或はこれらは完全な円形状又はリング形状パターンを構成しなく、このようなパターンの一部だけ構成しても良い。
実際の測定環境において、測定位置及び基準位置は物理的に実現可能な点からなる可能であるが、入射や出射にかかわらず、点以外、同じ特性の複数の点の集合からなる幾何図形であっても良く、円形状、リング形状、矩形状などを含む。
本開示の実施例によれば、光強度の相対変化量をスペクトルデータとして採用して差分して、濃度変化に関する測定情報のみを保留する。
発明者は、径方向位置ρに沿って光強度の相対変化量も線形又は線形近似を呈することを既に発見していた。以上の論述を参照し、例えば図５０の説明を結合して分かるように、上記の差分処理は同様に光強度相対変化量に適用する。例えば、二つの径方向位置での光強度相対変化量を直接差分処理することによって、乗法性ノイズを除去することができる；二つの径方向位置での光強度相対変化量を上記のように因数ηを利用して重み付け差分処理することで、加法性ノイズを除去することができる。
図３８はスペクトルデータを利用して濃度予測を行う一般的な原理を示している。図３８に示すように、背景媒体又は基準媒体（背景媒体及び初期濃度の特定成分を含み）に一連の既知濃度{C_i}の特定成分を入れ、それに応じたスペクトルデータ{I(ρ)}をそれぞれ取得する。これらの既知濃度のデータ集合Ｘ⌒と相応的なスペクトルデータの集合Ｙ⌒
によって、予測モデルを構築することができる。そして、背景媒体又は基準媒体に特定成分の未知濃度（或は濃度変化）C'_iに対して、それに応じたスペクトルデータI'(ρ)（“Y”）を取得することができる。I'(ρ)と予測モデルＭによって、濃度（“X”）を予測することができる。
上記のように、スペクトルデータは、各種の適合なデータ、例えば拡散反射及び／又は拡散散乱光の光強度変化や相対変化を含むことができる。
モデリングするときには、背景媒体又は基準媒体のスペクトルを初期スペクトルとして測定することができ、既知濃度{C_i}の特性成分が入れられた後のスペクトルを測定スペクトルとして測定することができ、これで光強度変化情報を取得することができる。予測するときには、同様に背景媒体又は基準媒体（基準媒体に特定成分の初期濃度がモデリングするとき基準媒体に特定成分の初期濃度と同じでも異なっても良く）のスペクトルを初期スペクトルとして測定することができ、特定成分濃度変化後のスペクトルを測定スペクトルとして測定することができ、これで光強度変化情報を取得することができる。予測されたものは濃度相対値（即ち、濃度変化量）であってもよく、初期値（背景媒体の場合は０；基準媒体の場合は上記初期濃度）を加えて濃度予測値を得ても良い。
本開示の実施例によれば、これらのスペクトルデータに対して上記の差分処理を行って、干渉要因の影響を効果的に除去することができる。例えば、計量化学方法を採用して予測モデルＭを構築する。具体的に、差分処理が行われた後のデータに対して最小二乗法を採用してモデリングすることができ、さらに正味信号モデルを構築することができる。
予測モデルＭは背景媒体／基準媒体と特定成分に対して予め構築され、例えばデータベース又はサーバに保存されることができる。必要の場合にデータベース又はサーバから予測モデルＭを取得することができる。
ここで、このようなモデリング及び／又は濃度予測方法を提出している。図３９を参照して、操作Ｓ１２０１において、スペクトルデータを取得することができる。例えば、モデリングするときには、既知濃度{C_i}の特定成分が入れられた後の背景媒体又は基準媒体に対して、スペクトルデータ（例えば、特定成分を入れる前に対しての光強度変化情報）を取得することができる；予測するときには、そのうち特定成分濃度が変化した背景媒体又は基準媒体に対して、スペクトルデータ（例えば、特定成分濃度変化前に対しての光強度変化情報）を取得することができる。続いて、操作Ｓ１２０３において、スペクトルデータに対して差分処理を行うことができ、例えば、光強度変化率の符号が異なる二つの位置でのスペクトルデータに対して差分処理を行う。そして、操作Ｓ１２０５において、処理された後の差分信号を利用してモデリング又は予測することができる。図３９の処理は、モデリングに応用されると予測に応用されるときに基本的に同じであり、その区別は以下にある：モデリングするときには、特定成分の濃度が既知であり、濃度（Ｘ⌒）とスペクトルデータ（Ｙ⌒）によって予測モデル（Ｍ）を得ることである；予測するときには、特定成分の濃度（或は濃度変化）が未知であり、スペクトルデータ（Ｙ）と予測モデル（Ｍ）によって予測濃度（或は濃度変化）（Ｘ）を得ることである。
本開示の実施例によれば、このようなモデリング／予測方法は人体非侵襲的血糖濃度測定に応用することができる。この場合、プローブ光の波長は約１．０〜２．４μmの範囲内にあって良い。
一例によれば、モンテカルロシミュレーションの方法によって５％ ｉｎｔｒａｌｉｐｉｄ溶液の浮動基準位置を確定することができ、入射光子数の変化によって光源のドリフトをシミュレーションすることができる。
図４０は濃度が５％であるｉｎｔｒａｌｉｐｉｄ溶液に対するモンテカルロシミュレーションの浮動基準位置計算結果である。シミュレーションに用いられる、吸収係数、散乱係数、各異方性因子及び散乱係数を含む光学パラメータは、Tamara L. Troy & Suresh N. Thennadil, Optical properties of human skin in the near infrared wavelength range of 1000 to 2200 nm, Journal of Biomedical Optical, 2001, 6(2):167-176.からのものであり、シミュレーションの波長範囲は１１００〜１６００ｎｍである。ブドウ糖濃度はそれぞれ０〜１００ｍＭであり、間隔が１０ｍＭであり、光子数が１０^９である。異なるブドウ糖濃度下でのｉｎｔｒａｌｉｐｉｄ溶液による拡散反射光とブドウ糖が含まれない純粋なｉｎｔｒａｌｉｐｉｄ溶液による拡散反射光の差を算出して、波長範囲が１１００〜１６００ｎｍで、浮動基準位置が約０．９〜２ｍｍの範囲内に変化することを分かることができる。同一被測定個体又はサンプルの基準位置は異なる波長下で大きな差があることを示している。
したがって、図３６（ｄ）に示す拡散反射光受信方案を採用することができる。具体的に、光源からの浮動基準内側、外側の両位置でのスペクトルを同時に受信する。図41は入射光子数が１０^９の場合に、１３００ｎｍ波長下でブドウ糖濃度が５０ｍＭと１００ｍＭ変化するときの拡散反射光光子数変化量の図。
通常、測定された信号をブドウ糖濃度変化による有用な信号I_S及び人体生理背景又は外部環境変化に関するノイズ信号I_Nに分ける、即ち、

ただし、I_Sはブドウ糖濃度C_gに関連しており、I_Nは主に光源ドリフト、温度、圧力、変位などの物理的要因によって影響される。ここで、光源ドリフトによるノイズ干渉のみを考えるようにする。これによって、光源ドリフトと血糖濃度変化とによる光強度測定値Iの変化は下記の通りである。

ただし、ρは検出器と光源の径方向距離（モンテカルロシミュレーションに球座標の径方向半径位置）であり、ΔC_gは血糖濃度の変化量であり、ΔNは背景の変化量である。ΔI_S(ρ, ΔC_g, N)は有効なブドウ糖濃度情報であり、この部分の情報が必要である。背景干渉信号であるΔI_N(ρ, C_g, ΔN)はブドウ糖濃度情報に関連しなく、かつ、通常不規則に変化して、ΔI(ρ, ΔC_g, ΔN)からブドウ糖濃度変化情報を抽出し難しいことに至る主な理由である。
基準位置ρ_Rで、拡散反射光強度はブドウ糖濃度変化に敏感でなく又はブドウ糖濃度変化に関連しなくて、下記がある：

基準位置での光強度変化は完全に背景干渉によって引き起こされて、下記がある：

相応的に、浮動基準内側と外側測定位置での拡散反射光強度変化は、それぞれ下記の通りである。

基準位置ρ_Rでの背景干渉変化ΔI_N(ρ_R, C_g, ΔN)、と測定位置での背景干渉変化との間の内因性関係は、固定的なものであるので、

ただし、η₁及びη₂は比例係数である。留意されたいことは、異なる径方向位置又は異なる測定半径を測定位置として選択する場合、得られる倍数関係が異なり、即ち適当な重み付け係数を選択すべきである。実際の測定過程においては、ブドウ糖濃度が相対的に一定に保持されるときに繰り返し測定することによって得られることができる。式（70）〜（７４）によって差分演算で下記の有効なブドウ糖信号表現式を求めることができる。

式（７５）によって、浮動基準内側及び浮動基準測定位置の情報だけを採用して、さらに計量化学モデリング分析を行うことができる；式（７６）によって、浮動基準外側及び浮動基準位置の情報だけを採用して計量化学モデリング分析を行うことができる。浮動基準位置の情報を完全に採用しない場合、式（７３）と（７４）を除算して下記の式を得ている。

これによって、浮動基準内−外側受信方案を採用して、有効な測定信号ΔI_I-O(ΔC_g)を得ることができる。

浮動基準位置に基づく拡散反射信号を差分処理して得られた血糖情報は、直接測定して得られた拡散反射光強度変化情報に比べて、より高い特異性を有しており、実際の測定における背景干渉を効果的に差し引いている。
本実施例は、入射光子数を変更することによって光源のドリフトをシミュレーションしており、変化範囲が±２０％である。図４０から分かるように、波長１３００ｎｍで、ブドウ糖の浮動基準位置が約１．３ｍｍ付近であるので、図４１中のエリアＡのように、径方向位置が０．７〜０．９ｍｍの位置を浮動基準内側測定位置として選択することができて、測定されたスペクトルがI(ρ_I)である；図４１中のエリアＢのように、径方向位置が１．３ｍｍの位置を浮動基準位置として選択して、測定されたスペクトルがI(ρ_R)である；図４１中のエリアＣのように、径方向位置が１．８ｍｍ〜２．０ｍｍの位置を浮動基準外側測定位置として選択して、測定されたスペクトルがI(ρ_O)である。
溶液中にブドウ糖が含まれず、即ち光源ドリフトのノイズ信号のみが含まれる場合には、同一測定位置が光源ドリフトで相応的なノイズ信号を発することになる。モンテカルロシミュレーションの結果によって得られる、異なる入射光子数で異なる測定位置での拡散反射光子数を表１に示す。入射光子数が１０^９から±２０％変化する場合には、相応的な測定位置で拡散反射光子数の変化量を表２に示す。なお、拡散反射光子数の相対変化量は表２−１に示される。これから分かるように、三つの測定位置で、拡散反射光子数の相対変化量は基本的に一致している。したがって、任意の二つ位置の拡散光子数の相対変化量の比率ξは約１である。

このときブドウ糖濃度が変わらないため，測定された信号変化量は完全に光源ドリフトの変化によって引き起こされるものであり、即ち、このとき測定された信号変化量はノイズ信号であると考えられる。したがって、表３に示すように、異なる測定位置でのノイズ干渉の比率を計算することができる。

表３における任意の二つの位置でのノイズ干渉の絶対変化量の比率も、以下の方法によって直接取得される。ξはもう１と確定されるため，表３−１に示すように、式（Ｓ−３）を利用して直接にηの値を取得することができる。

表３と表３−１とを比較して、実際に得られたηの値は式（Ｓ−３）を採用して推定されたηの値と基本的に一致している。
表３と３−１から分かるように、ブドウ糖濃度が変化せず、光源のみドリフトする場合には、下記の通りである：
浮動基準内側測定位置信号の変化量ΔI_N(ρ_I, ΔC_g, ΔN)は、浮動基準測定位置信号の変化量ΔI_N(ρ_R, ΔC_g, ΔN)の約７．０倍であり、即ち、ΔI_N(ρ_I, ΔC_g, ΔN)＝７．０ΔI_N(ρ_R, ΔC_g, ΔN)；
浮動基準外側測定位置信号の変化量ΔI_N(ρ_O, ΔC_g, ΔN)は、浮動基準測定位置信号の変化量の約１．０６倍であり、即ち、ΔI_N(ρ_o, ΔC_g, ΔN)＝１．０６ΔI_N(ρ_R, ΔC_g, ΔN)；
浮動基準内側測定位置信号の変化量ΔI_N(ρ_I, ΔC_g, ΔN)は、浮動基準外側測定位置信号の変化量ΔI_N(ρ_O, ΔC_g, ΔN)の６．６倍であり、即ち、ΔI_N(ρ_I, ΔC_g, ΔN)＝６．６ΔI_N(ρ_O, ΔC_g, ΔN)。
ブドウ糖濃度と光源は何れも変化する場合には、浮動基準位置での光強度変化がブドウ糖濃度変化に関連せず、即ち、この位置での光強度変化が完全に光源ドリフトによって引き起こされるものであるため、式（７５）と式（７６）によって得られる浮動基準内側と外側のブドウ糖濃度変化による有用な信号はそれぞれ下記の通りである。

それぞれ六つの異なる濃度のブドウ糖拡散反射スペクトルを選択して、対応するブドウ糖濃度と入射光子数を表４に示す。

光源ドリフトに対して修正しない場合に、図４２に示すように、ブドウ糖濃度がそれぞれ２０、４０、６０、８０及び１００ｍＭ変化する場合、光源から離れた異なる径方向位置での拡散反射光子数変化曲線が得られており、即ち、拡散反射光強度を測定する曲線は、ブドウ糖濃度によって規則的な逓増又は逓減変化を呈することがない。つまり、光源ドリフトによる信号変化はブドウ糖濃度変化の特徴信号を覆っている。
同様に浮動基準内側測定位置を０．７〜０．９ｍｍに、基準位置を１．３ｍｍ、外側測定位置を１．８〜２ｍｍに取る。光源ドリフトに対して修正する前に、表５に示すように、ブドウ糖濃度変化下で各測定位置での拡散反射光子数変化値が得られる。

式（７９）と（８０）を採用して浮動基準位置の情報を結合して浮動基準内側と外側測定位置拡散反射光子数変化量に対してそれぞれ光源ドリフトの修正を行っており、計算結果を表６に示す。

図１６から分かるように、浮動基準内側測定位置で、ブドウ糖濃度変化の増大に伴い、拡散反射光子数は順に逓減するように変化し、変化量が負値である；浮動基準外側測定位置で、ブドウ糖濃度変化の増大に伴い、拡散反射光子数は順に逓増するように変化し、変化量が正値である。すなわち、光源ドリフトの影響を効果的に除去している。
完全に浮動基準位置での測定情報を採用しないと、上記の計算から分かるように、浮動基準内側測定位置信号の変化量ΔI_N(ρ_I, ΔC_g, ΔN)が浮動基準外側測定位置信号の変化量ΔI_N(ρ_O, ΔC_g, ΔN)の約６．６倍であり、即ち、ΔI_N(ρ_I, ΔC_g, ΔN)＝６．６ΔI_N(ρ_O, ΔC_g, ΔN)、式（７８）によって測定された浮動基準内側と外側測定信号に対して重み付け差分演算を行って下記になる。

即ち、得られた信号は浮動基準内側と外側有効信号の加重和であり、完全に光源ドリフトによるノイズを除去している。
式（８１）を採用し、完全に浮動基準位置情報を採用せず、浮動基準位置内側と外側測定信号のみを採用して上記のブドウ糖濃度変化だけでなく光源ドリフトも存在する情況に対して修正して、算出された異なるブドウ糖濃度変化でのΔI_I-O(ΔC_g)結果を表７に示す。結果に表われることは、ブドウ糖濃度変化量の逓増に伴い、浮動基準内側と外側測定信号に対する重み付け差分処理によって得られた有効信号ΔI_I-O(ΔC_g)が順に逓増する傾向を呈し、光源ドリフトによるコモンモード干渉の影響を効果的に除去していることである。

その他の異なる波長下で測定されたスペクトル信号に対して類似的な方法を採用して光源ドリフトの修正を行い、さらに重み付け差分処理を行って得られた各波長下での有効信号ΔI_S(λ_i)をそれに対応する一系列の参考濃度パラメタと結合して、部分最小二乗数理モデルを構築し、未知濃度スペクトル濃度の予測を行うことができる。
別の一例によれば、モンテカルロシミュレーションの方法によって、光源からの浮動基準内側−外側を受信方案として測定待ち対象温度が変化するときの情況を分析することができる。
２％のｉｎｔｒａｌｉｐｉｄ溶液に対して、波長が１４００ｎｍより大きいの場合、浮動基準位置がなくなり、つまり、波長が１４００より大きいの場合、浮動基準測定方法の理論が適用されなくなることを発見した。そのために、ここで濃度が２％のｉｎｔｒａｌｉｐｉｄ溶液をモデルとして、波長１６００ｎｍ下でのブドウ糖濃度と温度とによる拡散反射光の変化情況に対してモンテカルロシミュレーションを行う。ブドウ糖濃度変化範囲が０〜１００ｍＭであり、間隔が２０ｍＭである；温度変化範囲が３２℃〜４０℃であり、間隔が０．５℃である；入射光子数が10¹¹であり、サンプルを経過して拡散反射された絶対光子数を出射光とする。温度変化する場合には、吸収係数と散乱係数の変化量がそれぞれ下記の通りである。

１６００ｎｍを例として、温度のみを変化させて、３２度の出射光を基準として、得られる温度による拡散光の相対変化量を図５２に示す。
これから分かるように、光源−探触子距離が２ｍｍの付近に、温度変化に敏感でない位置があり、それを「温度基準位置」と呼ぶすることができる。それに、光源から一定の距離を離れた後、一定の範囲に、異なる位置の間の光強度相対変化量が線形に近似した変化規則を呈する。注意されることは、光源からあまり離れすぎた後、出射光が急に下がるため、ノイズ影響が大きくなり、このとき測定が大きな影響を受けることになる。ここで、ノイズが大きすぎるの情況を考えないようにする。二つの測定位置を固定すると、図５２によって、ξの値を推定することができる。また式（Ｓ−３）を利用して、ηの値を直接取得することができる。
ηの値を精確に取得するために、以下、温度変化した後で実際に生じられたノイズ量によって計算する。
温度が３２℃、３５℃、３８℃及び４０℃でブドウ糖濃度が６０ｍＭ及び１００ｍＭ変化するとき異なる位置での拡散反射光変化量をそれぞれ取って、図４４に示す分布図が得られる。図から分かるように、この波長で、私たちは浮動基準位置がないと考えることは、ブドウ糖濃度の変化による感度がほぼゼロに常に保持されるある一つの径方向位置が実際にないことである。しかしながら、いかなる一つの温度で、ブドウ糖濃度の変化による拡散反射光の変化量が常に負値になる径方向位置があり、それにこのエリア内の拡散反射光の変化量はより高い絶対値と安定性を有する。そのため、このエリアで二つの径方向位置を二つの測定位置として選択し、浮動基準位置がない場合のコモンモード干渉ノイズを除去するために用いることができる。
径方向位置０．６〜１ｍｍを測定位置１として、径方向位置１〜２ｍｍを測定位置２として選択する。溶液にブドウ糖が含まれない場合、即ち温度による変化しかない場合、異なる径方向位置は温度の変化に伴って相応的なノイズ信号を生じることになる。モンテカルロシミュレーションによって、異なる温度で異なる径方向測定位置での拡散反射光子数を得ることができる。３６℃を基準として、温度が３２℃から４０℃まで変化する場合、即ち、温度が±４℃変化する場合、二つの測定位置で検出された拡散反射光子数の変化量を表８に示す。

このときブドウ糖濃度が変わらないため、測定された信号変化量が完全に温度変化によって引き起こされるものであり、即ち、このとき測定された信号変化量がノイズ信号と考えられる。そのため、二つの測定位置でノイズ干渉の比率を計算することができ、温度変化で、測定位置２の拡散反射光子数変化量と測定位置１の拡散反射光子数変化量の比率が約０．１７である。即ち、下記のように記することができる。

したがって、ブドウ糖濃度と温度が全部変化する場合、式（８４）によってρ₁とρ₂での拡散反射光の変化量に対して差分演算を行って、得られるブドウ糖濃度変化による、温度によるコモンモード干渉を除去する有効信号は、下記の通りである。

ランダムで六つの異なる温度で異なる濃度のブドウ糖拡散反射光を選択して、ブドウ糖濃度と温度の間の相関係数が−０．０１９１８であるため、両者の間に関係がないと考えられ、これで実際の測定過程においてブドウ糖濃度が変化すると同時に温度が不規則的なドリフトを発生する情況をシミュレーションしており、対応するブドウ糖濃度及び温度の情況は表９に示すとおりである。

第一グループのデータを測定開始時刻の状態として、温度変化による干渉信号に対して修正しない場合に、図４５に示すように、ブドウ糖濃度がそれぞれ２０、４０、６０、８０及び１００ｍＭ変化する場合、同じの二つの測定位置での拡散反射光子数の変化曲線が得られる。図の中で拡散反射光強度変化量を測定する曲線は、ブドウ糖濃度の変化によって規則的な逓増又は逓減変化を呈することがなく、温度変化による信号変化はブドウ糖濃度変化の特徴信号を覆っている。
式（８５）を採用して二つの測定位置での拡散反射光子数変化量に対して温度変化の修正を行って、計算結果は図４５における曲線に示す通りである。図から分かるように、二つの測定位置での信号の重み付けと修正後の信号を採用して、その絶対値が修正前の二つの測定位置での信号値より小さくなるが、曲線の絶対値がブドウ糖濃度の変化に伴って規則的な逓増変化を呈して、温度ドリフトによるコモンモード干渉を除去するという目的を達成している。
別の一例によれば、ＳＬＤ光源に基づく多環式光ファイバ測定システムを採用して、濃度が３％のｉｎｔｒａｌｉｐｉｄ溶液を測定待ち対象として、光源がドリフトする場合の情況を分析する。
実験分析によって測定されることは、波長が１２１９ｎｍである場合、濃度が３％のｉｎｔｒａｌｉｐｉｄ溶液のブドウ糖の浮動基準位置がおよそ３．０〜３．２ｍｍのところにあることである。これによって、この位置を多環式光ファイバプローブに浮動基準位置信号検出リングとして選択する。加工工程に対する考慮から、径方向位置が０．２４〜０．９６ｍｍの位置を内側測定位置信号検出リングとし、３．２〜４．１ｍｍの位置を外側測定位置信号検出リングとして、図３７（ａ）に示すような構造の多環式光ファイバプローブが作製された。
実験過程では、ランダムでＳＬＤの電力を変更して光源の不規則的なドリフト現象をシミュレーションして、波長が１２１９ｎｍになるときに、異なる時刻での三つの径方向位置での拡散反射光強度を測定し、一回目の測定値を測定の初期状態と仮定して、光源がドリフトを発生する場合、拡散反射光の変化量は当時状態の光強度測定値と初期状態ときの光強度値で差分計算を行って得られる。これによって、光源ドリフトによる三つの測定位置での拡散反射光信号値の変化量の比率を算出することができる。計算によって得られることは、浮動基準外側測定位置での光源ドリフトによる拡散反射光信号値の変化量が浮動基準位置での信号変化量の約０．８４場合であり、浮動基準位置での信号の変化量が浮動基準内側測定位置での信号変化量の約０．７倍であり、浮動基準外側測定位置での信号の変化量が内側測定位置での信号の変化量の約０．５８倍である。これらを光源状態とブドウ糖濃度が同時に変化するときの差分比例係数として信号の修正を行うために用いており、即ち、下記のように近似的に考えられる。

次いで、濃度が３％のｉｎｔｒａｌｉｐｉｄ溶液を母液として、ブドウ糖濃度範囲が１０００〜６０００ｍｇ／ｄＬ、間隔が１０００ｍｇ／ｄＬの六つのサンプルを配置して、ランダム順に六つのブドウ糖ｉｎｔｒａｌｉｐｉｄ溶液を測定し、測定過程中に同時にＳＬＤの電力を変更して光源の不規則的なドリフト現象をシミュレーションして、異なる時刻での三つの径方向位置での拡散反射光強度を測定し、サンプル溶液の拡散反射光強度と初期状態時の拡散反射光強度に対して差演算を行って、光源ドリフトとブドウ糖濃度が同時に変化するときに三つの測定位置での拡散反射光の変化量を算出しており、結果は図４６に示すとおりである。結果から分かるように、光源ドリフトがブドウ糖濃度の検出に大きな影響を与え、光源ドリフトのランダム性によって、三つの位置で測定された信号はいずれもブドウ糖変化との間の線形関係を失ってしまい、即ち、光源ドリフトによる拡散反射光強度信号の変化量はもう完全にブドウ糖濃度変化の有効情報を覆っているため、測定された光強度信号を修正する必要がある。
式（８６）、（８７）及び（８８）の比例関係によって、式（７５）、（７６）及び（７８）を採用してブドウ糖濃度変化と光源ドリフトとによって共同で引き起こされた拡散反射光強度信号を修正しており、結果は図４６に示すとおりである。結果から分かるように、任意の二つの位置の信号を採用して重み付け差分処理を行い、修正後の光強度信号はいずれもブドウ糖濃度変化と明らかな線形関係を呈し、ブドウ糖濃度検出に対する光源ドリフトの影響が減少又は除去され、さらにブドウ糖濃度変化の有効情報を効果的に抽出することができる。なお、結果からも分かるように、内リングと基準リング測定位置での信号、および外リングと内リング測定位置での信号を採用して修正された有効信号は、外リングと基準リング測定位置での信号を採用して修正された有効信号より明らかに大きくなっており、これは、光源からの径方向距離の増大に伴い、拡散反射光強度値は式指数的に減衰する。それに内リング及び外リングを採用する修正効果と内リング及び基準リングを採用する効果が伯仲しているが、内リング及び外リングを採用して信号検出と修正を行う場合、基準リングでの測定信号を採用しなくなり、浮動基準位置に対する測定波長、被測定対象自身状態などの変化の影響を受けなくても良く、当該信号修正方法の普遍性を効果的に強めている。
上記の分析において、濃度が３％の純粋なｉｎｔｒａｌｉｐｉｄ溶液で光源ドリフトによる比例係数を算出し、それを測定の初期状態として後続の信号処理を行う。同様に、類似的なステップに従って、異なる濃度を含むブドウ糖溶液サンプルで、最初に光源のランダムのドリフト下で相応的な比例係数を計算して、さらにこの濃度サンプルを測定の初期状態として後続の信号処理を行うことができる。ブドウ糖濃度が３０００と６０００ｍｇ／ｄＬのサンプルをそれぞれ採用してスペクトル修正に用いられる比例係数を算出し、それを測定の初期状態としてスペクトル信号の修正を行い、図４７と図４８に示すようなブドウ糖濃度が３０００と６０００ｍｇ／ｄＬのサンプルをそれぞれ初期状態として信号修正を行った結果を得ており、図から分かるように、異なる濃度のブドウ糖溶液を初期状態として、光源ドリフトによるコモンモード干渉を減少又は除去するという目的を同様に達成することができ、それに内側と外側測定位置での信号、及び内側と浮動基準位置での信号を採用して修正された効果が、外側と浮動基準位置での信号を採用して修正された効果より優れるように同様に現れており、得られた結論は純粋なｉｎｔｒａｌｉｐｉｄ溶液を初期サンプルとして信号修正を行う場合と一致している。また注意されたいことは、どのようなブドウ糖濃度のサンプルを初期状態として信号修正を行う場合でも、得られた修正後の結果は全部初期状態でのブドウ糖濃度情報に対する変化量であるため、異なる測定時刻でのブドウ糖濃度測定値がこの変化量と初期状態でのブドウ糖濃度値の和になるべきである。
図４９は本開示実施例による測定システムの配置例を示している。
図４９に示すように、当該測定システムは、光源２２０１、光源２２０１からの光を光ファイバに結合されるように適合するための結合システム２２０３、光ファイバプローブ２２０５、及び処理装置２２０９を含むことができる。
光源２２０１は、必要な波長の光を発射可能な各種の適切な光源を含むことができる。例えば、近赤外範囲で、ハロゲンランプを連続光源として使用することができる。或は、光源２２０１はスーパーコンティニウムパルスレーザ光源も含むことができる。
結合システム２２０３は、光源２２０１からの光を直線偏光に変換するためのグランプリズム２２０３−１、グランプリズム２２０３−１からの直線偏光を偏光状態が０次光と直交する＋１次光（或は−１次光）に分光（回折）するための音響光学チューナブルフィルタ（ＡＯＴＦ）２２０３−２、グランプリズム２２０３−１と直交して設けられて０次光を除去するためのグランプリズム２２０３−３、およびグランプリズム２２０３−３からの＋１次光（或は−１次光）を後継デバイスに結合するためのカプラ２２０３−４を含むことができる。
ここで留意されたいことは、図４９は結合システムの１つ具体的な例を示しているが、本開示がこれに限らない。業業者は、複数の結合システムを知っており、光源からの光を光ファイバシステムに結合することができる。
光ファイバプローブ２２０５は例えば前に図３７を参照して説明した構造を含むことができる。具体的に、結合システム２２０３は光源からの光を光ファイバプローブ２２０５の入射光ファイバ束（例えば、図３７中の１００１）に結合することができ、入射光ファイバ束は、光を被測定媒体２２０７に案内することができる。そして、光ファイバプローブ２２０５中のプローブ光ファイバ束（例えば、図３７中の１００３、１００５及び１００７の二つ以上）は被測定媒体２００７の拡散反射光を処理装置２２０９に案内することができる。
処理装置２２０９は、探触子２２０９−１（例えば、光電探触子）を含むことができ、光ファイバプローブからの光信号を探知するために用いられ、それを電信号に変換してさらなる処理に供することができる。光ファイバプローブの配置によって、探触子２２０９−１は、複数の径方向位置（例えば、浮動基準位置内側、浮動基準位置及び／又は浮動基準外側）でのスペクトルデータを探知することができる。
処理装置２２０９はプロセッサ２２０９−２を更に含める。プロセッサ２２０９−２は、探触子２４０１に探知されたスペクトルデータに対して上記のような差分処理を行うように配置されることができる。具体的に、プロセッサ２２０９−２は、被測定媒体における特定成分の濃度変化の伴って拡散反射光の光強度が異なる符号の変化率を有する二つの径方向位置を選択し、この二つの径方向位置でのスペクトルデータに対して重み付け差分処理を行うことができる。
プロセッサ２２０９−２は、例えば汎用コンピューター、専用集積回路（ＡＳＩＣ）、ＦＰＧＡなどの各形式の計算設備を含むことができる。プロセッサ２４０３は、記憶装置に記憶されるプログラム、コードセグメントなどをロードすることによって、上記のような各方法、プロセスに従って動作して、スペクトルデータ差分処理、モデルの構築及び濃度予測を実現することができる。
該処理装置２２０９は、例えばマウス、キーボードなどの、ユーザの命令、データなどを入力するための入力装置２２０９−３と、例えばディスプレイなどの、プロセッサ２４０３の処理結果（例えば、分離した散乱信号／吸収信号、予測結果など）を出力するための出力装置２２０９−４と、をさらに含める。入力装置２２０９−３及び出力装置２２０９−４は組み合ってタッチパネルとして実現されることができる。
本開示の技術は、データ処理装置で実行できるアルゴリズムのプログラムを含むように実現でき、あるいは、非一時的なコンピューター読み取り可能な媒体に記憶されて提供されることができる。
本開示の技術はコンピューターの読み取り可能な媒体におけるコンピューター読み取り可能なコードとして実現されることができる。コンピューター読み取り可能な媒体は、コンピューターの読み取り可能な記録媒体及びコンピューター読み取り可能な伝送媒体を含む。コンピューター読み取り可能な記録媒体は、データをその後コンピューターシステムにより読み取る可能なプログラムとして記憶する任意のデータ記憶装置である。コンピューター読み取り可能な記録媒体の例示は、リードオンリーメモリ（ＲＯＭ）、ランダムアクセスメモリ（ＲＡＭ）、シーディーＲＯＭ（ＣＤ-ＲＯＭ）、テープ、ディスク及び光データの記憶装置を含む。コンピューター読み取り可能な記録媒体はインターネットに接続されるコンピューターシステムにおいて分布されてもよく、これにより、分散的な形式によってコンピューター読み取り可能なコードを記憶して実行する。コンピューター読み取り可能な伝送媒体は、搬送波又は信号によって伝送されることができる（例えば、インターネットを介する有線又は無線データ伝送）。また、本開示技術を実現する機能プログラム、コード及びコードセグメントは、本発明の全体構想の本分野のプログラマーにより容易に解釈されることができる。
以上、複数の実施例に本開示の複数の特徴をそれぞれ説明している。しかしながら、これは、これらの特徴が有利に結合されて使用できないことを意味しない。
以上、本開示の実施例を説明している。しかしながら、これらの実施例は説明するためものであり、本開示の範囲を限定しない。本開示の範囲は権利請求項及びその等価物により限定される。本開示の範囲を逸脱しない限り、当業者は複数の置換及び補正を行え、これらの置換及び補正は全て本開示の範囲に含まれるべきである。



(Example 2)
Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. However, it should be understood that these descriptions are merely exemplary, and do not limit the scope of the present disclosure. In the following description, descriptions of known structures and techniques may be omitted in order to avoid unnecessarily confusing the concepts of the present disclosure.
According to the embodiment of the present disclosure, the first radial position and the second radial position at different positions apart from the light source can be arbitrarily selected, and the spectral data of the two radial positions can be obtained. Is subjected to difference processing. The inventor has discovered that such difference processing can achieve equally effective removal of multiple types of interference, especially common mode interference. Compared with the technology disclosed in Chinese Patent Application CN1699973A, the trouble of determining the floating reference point can be avoided.
To achieve better processing effects (eg, interference suppression, effective signal enhancement), such first radial position and second radial position can be selected as follows. For example, depending on the concentration of a specific component (a component of interest, for example, blood glucose) in the medium to be measured, depending on the rate of change of diffuse reflection and / or diffuse scattering at different positions away from the light source of the medium to be measured, necessary for the measurement. A radial position (selectable, floating reference position can also be determined) can be obtained. Specifically, the floating reference position may be defined as a light receiving point having the smallest absolute change rate (for example, almost zero), that is, a radial position that is basically insensitive to a change in the density of this specific component. it can. For example, as can be seen from the Monte Carlo simulation result of a typical three-layer structure model of the human skin, the floating reference position for measuring the blood glucose concentration is approximately 1.7 to 3.2 mm away from the light source, and the change range is large. At the same probe light wavelength, the glucose concentration increases with the floating reference position as a critical point, and the diffuse reflection and / or diffuse scattered light intensity gradually decreases at the radial position inside the floating reference, and the diameter outside the floating reference becomes smaller. In the direction position, the diffuse reflection and / or diffuse scattered light intensity is gradually increased, so that the diffuse reflected and / or diffuse scattered light intensity is negative inside the floating reference as shown in FIG. It is a positive value outside the standard. Furthermore, the order of the diffuse reflection and / or diffuse scattered light intensity is close to the position inside the floating reference and close to the floating reference position, and it is considered that the sensitivity of these two positions to changes in glucose concentration is excellent. As the radial distance decreases, that is, as the light source position gets closer, the absolute value of the diffuse reflection and / or diffuse scattered light intensity change increases, and the diffuse reflection and / or diffuse scattered light intensity change outside the floating reference. As compared with the largest part, the closer to the light source, the absolute value of the amount of change of the diffuse reflection and / or diffuse scattered light intensity is about 100 times outside, and the diffuse reflection and / or diffusion emitted from the epidermis The scattered light intensity value also increases.
According to the above characteristics, the present disclosure provides a spectrum detection method. As shown in FIG. 32, the method includes, in operation S501, measuring first spectral data at a first radial position and second spectral data at a second radial position of a medium to be measured. including. As described above, the first radial position and the second radial position can be arbitrarily selected. That is, the first radial position and the second radial position can be determined at random. The medium to be measured can include, for example, various media such as human skin. For convenience of description, the medium under measurement is considered to include the background medium and certain components in the background medium (ie, the background medium may be other components than the specific components in the medium to be measured). Such a specific component may be, for example, a target of interest such as blood glucose.
Those skilled in the art are aware of several ways to perform spectral measurements and acquire spectral data. For example, the medium to be measured is irradiated with a probe light of a certain wavelength by a light source, and diffused reflection and / or diffuse transmission light of the medium to be measured is detected by a detector, and for example, the light intensity is measured. In the following description, diffuse reflection light is taken as an example, but the present disclosure is not limited to this. Alternatively, both the light source and the detector can penetrate into the medium to be measured and measure the spectral data, which is similar to the case of an infinite medium. The position of the detector can be adjusted to achieve multiple radial position measurements. Alternatively, the detector can simultaneously detect light intensity at two or more corresponding positions including two or more light receiving units provided at different positions. This is described in further detail below.
In addition, probe light of one or more wavelengths, for example, ultraviolet, visible, and infrared bands can be selected and measured according to the characteristics of the medium to be measured and / or the specific components thereof. For example, a wavelength that is sensitive to the scattering and / or absorption properties of the particular component and / or a wavelength that is insensitive to the scattering and / or absorption properties of the background medium can be selected.
Advantageously, a change in light intensity (absolute and / or relative) (for example, due to a change in the concentration of a specific component in the medium to be measured) can be measured as spectral data. For example, in the case where the specific component is not included in the background medium or the specific component is a fixed initial density value (hereinafter, the specific component of the background medium and the initial density is referred to as “reference medium”), Measure the spectrum at one radial position, and use I ₁ Can be described. Then, when the concentration of the specific component in the background medium changes with respect to the initial concentration, the spectrum at this radial position of the measured medium at this time is measured, and I _Two Describe in. For example, for the measurement of blood sugar, first, a blood spectrum at the time of fasting (at this time, blood sugar is at a stable low level) is measured and set as an initial spectrum; and after a meal (at this time, blood glucose is measured) Is changed, and gradually becomes stable up to 2 hours after a meal), thereby obtaining blood sugar change information. With these two spectra, the (absolute) change s of the light intensity is s = (I ₂ −I ₁ ) Can be obtained as the above spectral data. However, the spectral data is not limited to the above-mentioned absolute change in light intensity, but may be of another type (for example, the relative change in light intensity S = lnI) as described below. ₂ -LnI ₁ Or s = (I ₂ −I ₁ ) / I ₁ It should be noted that) may be obtained.
In many embodiments of the present disclosure, it may be necessary and possible to measure an initial spectrum. A spectrum when the background medium does not contain a specific component may be adopted as an initial spectrum, and a spectrum when the background medium contains a specific component having an arbitrary fixed initial concentration (that is, a reference medium) is adopted as an initial spectrum. May be. For example, for some media (especially background media that does not contain specific components), a database of initial spectra is constructed and used for duplication (for example, used in advance for experiments and used for actual measurements, etc.). ) May reduce the work load.
At the first radial position and the second radial position, the light intensity of the diffuse reflection light and / or the diffuse scattered light of the medium to be measured with respect to the probe light has a different rate of change with the change in the concentration of the specific component. Thus, the first radial position and the second radial position can be selected. In addition, since common mode interference at these two positions generally has a specific relationship, in actual measurement, the common mode interference between these two positions is removed by data processing to change the concentration of the component to be measured. Can leave information about
Specifically, at the first radial position and the second radial position, the light intensity of the diffuse reflection light and / or the diffuse scattered light of the medium to be measured with respect to the probe light differs according to the change in the concentration of the specific component. The first radial position and the second radial position can be selected to have a sign change rate. Here, the “different signs” can include positive (+) and negative (−), positive (+) and zero (0), or negative (−) and zero (0). That is, in the present application, the zero (0) value is regarded as having a sign different from positive (+) and negative (-). The radial position where the rate of change is zero is, for example, the floating reference position. In an actual measurement, a change rate whose absolute value is smaller than a certain threshold value can be regarded as a “zero” change rate, and this threshold value can be set according to an actual application environment.
As described below, the first radial position and the second radial position thus selected contribute to eliminating common mode interference. For example, the first radial position and the second radial position have a positive and negative rate of change (for example, a negative rate of change in the first radial position and a negative rate of change in the second radial position). Rate can be selected to be positive). At this time, the first radial position is inside the floating reference position (for example, in the area B shown in FIG. 31) (for example, the area A shown in FIG. 31), and the second radial position is the floating reference position. It is on the outside (for example, area C shown in FIG. 31). Thus, in practical applications, the first radial position can be selected to be closer to the light source position and the second radial position can be selected to be further away from the light source position. And for most cases, the first radial position can be inside the floating reference position and the second radial position can be outside the floating reference position. Thereby, the spectral data can be measured at the fixed first radial position and at the second radial position, and it is not necessary to determine the precise position of the floating reference position. Also, as described further below, a detector arrangement suitable for multiple measurement environments can be provided.
The selection of the radial position can be performed simultaneously with the spectrum measurement. For example, several radial locations can be initially selected and at these radial locations an initial spectrum, eg, light intensity (or obtained from an initial spectral database, as described above) can be measured. Then, after the specific component concentration in the medium to be measured changes (or the specific component concentration differs from the specific component concentration used to acquire data from the initial spectrum database), the change occurs at these radial positions. Measure the spectrum, for example, light intensity. The direction (positive or negative) of the light intensity change (rate) at each radial position can be determined from the initial spectrum and the change spectrum. The light intensity change (rate) at other radial positions can also be obtained by interpolation. One radial position where the change is positive and one radial position where the change is negative can be selected as the first radial position and the second radial position, respectively, or the change is positive or negative. One radial position and one radial position whose change is less than a fixed threshold (or "zero") (as described above, this radial position can actually be considered a floating reference position). The first radial position and the second radial position can be selected, and at this time, the spectral data at the first radial position and the second radial position are also obtained as described above.
As described above, it is not necessary to determine the floating reference position in advance, and such determination is time-consuming (it is necessary to measure a plurality of times to determine the minimum position of the light intensity change). If the initially selected radial position just includes the floating reference position, this position can of course be used. However, this is different from using the spectrum data at this position after determining the floating reference position in advance, and is because the inconvenience of determining the floating reference position has been eliminated.
According to another embodiment, the position of the floating reference point can be determined. For example, the minimum radial position of the absolute change in light intensity is selected as the floating reference point. By measuring a plurality of points near the radial position where the light intensity change is close to zero, the position accuracy of the floating reference point can be improved. In addition, spectral data at the floating reference point can be obtained.
After obtaining the spectral data at the first and second radial positions as described above, the method also includes performing a difference process on the spectral data in operation S503.
For example, such a difference process can be performed as follows.
The first radial position is ρ _m And the second radial position is ρ _n Is written. In particular, if the radial position is inside the floating reference point, ρ _I (The rate of change can be negative); if the radial position is outside the floating reference point, ρ _O (The rate of change can be positive). If the floating reference point is determined in advance, or if the floating reference point is exactly included in the selected radial position, the floating reference point becomes ρ _R Is written.
According to the embodiment of the present disclosure, the weighting coefficient η can be determined, for example, as follows. By adopting numerical calculation or keeping the specific component concentration C constant, the diffuse reflection light at different radial positions is repeatedly measured, and the diffusion under the influence of the interference factor ΔN at any two radial positions The ratio ΔI (ρ _m , C, ΔN) / ΔI (ρ _n , C, ΔN), denoted as η, ie:

Where ρ _m And ρ _n Is any different radial position, for example ρ _I , Ρ _O And ρ _R ΔI (ρ _m , C, ΔN) is ρ when the specific component concentration C is fixed _m Changes in light intensity due to the interference factor ΔN at ΔI (ρ _n , C, ΔN) is ρ when the specific component concentration C is fixed _n 5 shows a change in light intensity due to ΔN in the above.
In an actual measurement process, there is a change in an interference factor that causes a change in diffusely reflected light other than a change in the concentration of a component to be measured. When the concentration of the component to be measured changes by ΔC and the interference factor changes by ΔN, the following occurs.

Where ρ _i Is any radial position, for example ρ _I , Ρ _O And ρ _R ΔI (ρ _i , ΔC, ΔN) is ρ _i And the light intensity change due to interference factor ΔN and ΔI (ρ _i , C, ΔN) is ρ _i And the light intensity change due to the interference factor ΔN at ΔI (ρ _i , ΔC, N) is ρ _i 5 shows a change in light intensity due to a density change ΔC in FIG.
According to equation (22), any two radial positions (for example, ρ _I , Ρ _O And ρ _R Any of the two) can be subjected to the following difference processing.

As can be seen from equation (24), such a difference processing can effectively reduce or subtract a noise signal due to common mode interference, and a useful signal (ΔI (ΔC) only relating to the component concentration (ΔC) to be measured. Get)
In the following description, mainly ρ _I , Ρ _O And ρ _R However, as can be seen from equation (24), such a difference process is performed at any two radial positions ρ _m And ρ _n It should be noted that
Also, any two radial positions ρ _m And ρ _n The proportional constant η between noise signals due to common mode interference can be estimated in advance. In an actual measurement, this proportionality constant can be directly adopted to perform a difference process on the absolute change in light intensity at both positions, that is, a useful signal (ΔC) relating only to the concentration (ΔC) of the component to be measured. ΔI (ΔC)).
Hereinafter, the expression of η is estimated by the steady solution of the diffusion equation in an infinite medium, and a sample estimation method of the proportionality constant η is given based on this theory.
The solution of the light flux Φ for a single point light source in an infinite medium is:・

Where ρ is the radial distance between the detector and the light source; λ is the wavelength of the probe light emitted from the light source; μ _a Is the absorption coefficient; μ _s 'Is the equivalent scattering coefficient, (1-g) μ _s Where g is the anisotropy factor; μ _s Is the scattering coefficient; D is the photon diffusion coefficient;

; Μ _eff Is the effective damping coefficient,

. Therefore, equation (25) can be described as follows.

After the incident light enters the medium, the photons interact with the particles in the medium and are emitted to obtain diffuse reflected light.Generally, the factors causing the diffuse reflected energy change are mainly classified into the following three types. It is possible to: (1) change in the optical characteristics of the medium to be measured; (2) drift of the incident light source; (3) drift of the detector state. After the incident light enters the medium, the photons collide with the particles in the medium, some of the photons are absorbed and lost by the particles, and the other parts of the photons are scattered, causing a change in the optical properties of the measured medium. Is the result of the combined effect of the absorption and scattering effects. Factors that cause changes in the optical characteristics such as the absorption coefficient and the scattering coefficient of the measured medium mainly include a change in the concentration of the component to be measured in the measured medium, a change in the concentration of the interference component, a change in the temperature, and the like. Among the factors causing the change in the diffuse reflection energy, only the measurement of the change in the concentration of the component to be measured in the medium to be measured is desired, and the change in the diffuse reflection energy due to other influence factors should be reduced or subtracted. is there.
The blood glucose concentration changes by the steady solution of the diffusion equation in an infinite medium, taking the glucose concentration change in human tissue as an example. _g In this case, the change amount ΔΦ (ρ, ΔC of the light flux Φ (ρ) due to the change in blood glucose concentration at the same radial position _g ) Is:

However,

As can be seen from equation (6), the change amount of light flux ΔΦ (ρ, ΔC _g ) Is a function of the radial distance ρ.
According to the definition of the floating reference position, the light receiving point where the rate of change of the light intensity at the different position in the medium to be measured is different from the light source by the object to be measured, that is, the radial position that is not sensitive to a change in the concentration of a specific component such as blood glucose Is the floating reference position. Therefore, in an ideal case, the blood glucose concentration change ΔC _g At one wavelength and the steady-state solution of the diffusion equation in an infinite medium, the floating reference position ρ _R Below sensitivity Sen _g (ρ _R ) Is:

The floating reference position obtained by substituting equations (28) and (29) into (30) is as follows:

At this position, the luminous flux Φ (ρ _R ) Change ΔΦ (ρ _R , ΔC _g ) Is 0 (zero). Then, in the actual measurement process, the floating reference position ρ _R The change in diffuse reflected light at is due to background interference change and is not related to blood glucose concentration change,

Usually ∂μ _a / ∂C _g Is ∂μ _s '/ ∂C _g Equation (29) can be approximated by substituting equation (29) into equation (27):

The rate of change of the diffuse reflection obtained by this is:

Where 式 μ _s '/ ∂C _g Is the rate of change of the equivalent scattering coefficient due to the change in glucose concentration. Normally, for one fixed mother liquor model, the effect of a change in glucose concentration on the equivalent scattering coefficient is a constant. For example, for different concentrations of Intralipid solution models, ∂μ _s '/ ∂C _g Can be expressed as:

∂μ for skin (water + polystyrene) model _s '/ ∂C _g Can be expressed as:

Here, as shown in FIG. 33, the m value is a scattering coefficient due to a wavelength change calculated by Mie theory, as shown in Matthias Kohl, Matthias Essenpreis and Mark Cope, The influence of glucose concentration upon the transport of light in tissue-simulating phantoms. Is the rate of change of The two solid lines in the figure show the scattering coefficient μ when the glucose concentration is 85 mM / L and 144 mM / L in the skin (water + polystyrene) model, respectively. _s The curve of the change is shown, and the slope of fitting it to a straight line is -1.569 * 10 ^-7 And -1.5 * 10 ^-7 Since the subsequent simulation is performed using three different gradients of 50, 100, and 150 mM, calculation is performed by selecting approximate gradients.
As a result, as shown in FIG. 50, the rate of change dΦ / Φ of the diffuse reflection light due to the change in glucose concentration is approximately considered to be a (substantially linear) function of the radial distance ρ.
In the actual measurement, the relationship between the light intensity I and the energy flux density Φ of the light is a fixed multiple relationship, and the relative change in the energy flux density of the light is approximately equivalent to the relative change in the light intensity, that is,

. Therefore, the measurement position changes

Is also linearly approximated.
Therefore, the proportionality constant η between different positions can be estimated as follows.
With the same influencing factor ΔX, ΔI (ρ) / I (ρ) uses a linear function of ρ, and the light intensity relative change ΔI (ρ _m , ΔX) / I (ρ _m ), The light intensity relative change ΔI (ρ _n , ΔX) / I (ρ _n ) Is estimated and the ratio between the two is denoted by 、, which relates to the selection of the radial position, and is represented by the following equation (S-1).

(S-1)

In the equation (S-1),
ρ _R Is the insensitive position of this factor action. For example, if glucose changes, this position is the floating reference position for glucose measurement. For a specific DUT and a specific DUT,
ξ has been proven to be a relative fixed position. Therefore, two measurement positions
After ρm and ρn are fixed, the value of ξ is one fixed constant value. As can be seen, the value of ξ can be estimated in advance by experiment.
After transforming equation (S-1), the following equation (S-2) can be obtained.

(S-2)
And

(S-3)
As can be seen from equations (S-2) and (S-3), after estimating the value of ξ in advance, and substituting it into equation (S-3), the value of the proportionality constant η can be obtained. A useful signal (ΔI (ΔC)) relating to the component concentration (ΔC) to be measured by substituting into the equation (3) can be obtained.
We discuss the influence factor ΔN that causes a change in diffuse reflected light energy in the actual measurement process in two broad categories: one is the change in the optical properties of the medium to be measured due to the concentration of the interference component or the measurement temperature; One type is light source drift or detector state drift in the measurement system.
(1) Changes in optical characteristics of the medium to be measured due to interference component concentration or measurement temperature
When the interference component concentration or the measurement temperature changes, the optical characteristics of the medium to be measured change. Taking temperature change as an example, the change in temperature changes the vibration / rotation state and energy transition probability of the molecule, so that the molar extinction coefficients of the substances at different temperatures will be slightly different. At the same time, a change in temperature will cause the concentration of the absorbent to change with it, because: increasing temperature will increase the degree of chemical bonding between molecules. However, as the number of adjacent molecules of the same molecule increases, the density of the substance increases; however, an increase in temperature also greatly increases the distance between the molecules and decreases the density of the substance. The combined effect of the two determines the rule for changing the substance concentration with temperature. Blood glucose concentration relatively constant C _g And when there is only a temperature change ΔT, the change amount ΔΦ (ρ, C of the light flux Φ (ρ) caused at the same radial position _g , ΔT) are as follows.

By substituting the equations (28) and (29) into the equation (37), the following equation (38) can be obtained.

However,

Is written.
The radial distance away from the light source is ρ _I And ρ _O Are obtained as a floating reference inner measurement position and an outer measurement position, respectively, and according to equation (38), the floating reference inner measurement position ρ _I And floating reference position ρ _R Of the amount of change in the luminous flux due to the temperature change at the point, and the floating reference outside measurement position _O And floating reference position ρ _R Are as follows.

Since the living tissue contains about 70% of water, the temperature for the near-infrared spectrum of the living tissue is considerably related to the temperature characteristic of the spectrum of water. FIG. 34 shows the water molar extinction coefficient ε at 32 ° C. to 42 ° C. obtained by experiments by Jensen et al. _w (λ) and ε at 30 ° C _w (λ) (Peter Snor Jensen, Jimmy Bak, Stenfan Andersson-Engels, Influence of temperature on water and aqueous glucose absorption spectra in the near- and mid-infrared regions at physiologically relevant temperatures, Applied Spectroscopy, 2003 , 57 (1): 28-36). Other than being insensitive to temperature changes at 1440 nm, 1780 nm, 2180 nm, 2750 nm, 4900 nm, 5300 nm, and 6300 nm, ε at other wavelengths _w (λ) changes regularly as the temperature changes. For this reason, the rate of change of the molar extinction coefficient with temperature ∂ε under each wavelength within the range of human body temperature change (about 35 ° C. to 40 ° C.) _w (λ) / ΔT is a constant, but it is approximately considered that this constant takes a different value for different wavelengths. Thus, the rate of change of the extinction coefficient due to temperature under each wavelength ∂μ _a (λ) / ∂T is also approximated by a constant. Similarly, the authors performed spectral measurement experiments on water samples in the temperature range of 30 ° C. to 40 ° C. at intervals of 2 ° C. to obtain water at different temperatures and 30 ° C. shown in FIG. Curve for the absorbance change between water at 1525, 1832, and 2060 nm, and a linear relationship between the absorbance change at 1525, and 2060 nm (temperature, near-infrared noninvasive blood glucose measurement-reference wavelength drift). Research on reference method: "Doctoral Dissertation", Tianjin, Tianjin University, 2009). As can be seen from the figure, at each wavelength, the relationship between the amount of change in absorbance and the temperature approximates a linear relationship. Since water is a pure absorbing medium, the same conclusion is reached: the rate of change of the extinction coefficient with temperature under each wavelength ∂μ _a We can get the idea that (λ) / ∂T approximates a constant.
Laufer et al. Used in vitro skin sample experiments to study the relationship between human dermis and subcutaneous tissue and temperature effects within the range of 25 ° C to 40 ° C (Jan Laufer, et al., Effect of temperature on the optical properties of ex vivo human dermis and subdermis, Phys. Med. Biol., 1998, 43: 2479-2489). The experimental results show that the rate of change of the equivalent scattering coefficient of the dermis layer due to temperature change is (4.7 ± 0.5) × 10 ^-3 ° C ^-1 The change in the equivalent scattering coefficient of the subcutaneous tissue due to temperature change is (-1.4 ± 0.28) × 10 ^-3 ° C ^-1 Is shown. Therefore, within the range of human body temperature change (about 35 ° C. to 40 ° C.), the rate of change of the equivalent scattering coefficient due to temperature change Δμ _s '/ ∂T approximates a constant.
Therefore, as can be seen from equations (39) and (40), the floating reference inner measurement position ρ _I ,
Floating reference position ρ _R And floating reference outside measurement position ρ _O Is determined, the ratio ΔΦ (ρ of the change amount of the luminous flux due to the temperature change under the same wavelength _I , C _g , ΔT) / ΔΦ (ρ _R , C _g , ΔT) and ΔΦ (ρ _O , C _g , ΔT) / ΔΦ (ρ _R , C _g , ΔT) are constants, and η ₁ And η _Two Describe. That is:

Therefore, the amount of change in the intensity of the diffuse reflected light due to the temperature change can be regarded as common mode interference. Among them, the constant η is obtained by using the equations (39) and (40) for the measured medium whose optical parameters are known. ₁ And η _Two It is possible to calculate the optical parameters of the medium to be measured by a method of reconstructing the optical parameters using the diffuse reflection spectrum obtained by measuring the medium to be measured whose optical parameters are unknown. And the constant η is given by Equations (39) and (40). ₁ And η _Two Or in the case where the blood glucose concentration is kept relatively constant, the amount of change in the diffuse reflection light at the time of temperature change is repeatedly measured, and the constant η is calculated by the equations (41) and (42). ₁ And η _Two (Eg, take the average of multiple measurements).
In the actual measurement process, the glucose concentration is ΔC _g When the measured temperature changes by ΔT at the same time, the amount of change ΔΦ (ρ, ΔC of the light flux Φ (ρ) due to these two factors at the same radial position _g , ΔT) are as follows.

Where ΔΦ (ρ, ΔC _g , T) is a useful signal of interest awaiting measurement and ΔΦ (ρ, C _g , ΔT) are common mode interference signals related to the radial position.
Next, according to equations (32) and (43), the floating reference inner measurement position ρ _I , Floating reference position ρ _R And floating reference outside measurement position ρ _O At ΔC _g Δ (ρ) change ΔΦ (ρ) _I , ΔC _g , ΔT), ΔΦ (ρ _R , ΔC _g , ΔT) and ΔΦ (ρ _O , ΔC _g , ΔT) are as follows.

The following equation can be obtained by performing a weighted difference operation on equations (44) and (45) in equation (41).

As can be seen from the equation (47), the common mode interference amount of the diffuse reflection light change due to the temperature change is the floating reference inner measurement position ρ _I And floating reference position ρ _R Thus, a useful signal relating only to a change in blood glucose concentration can be obtained.
Similarly, according to equations (42), (45) and (46), the floating reference outer measurement position ρ _O And floating reference position ρ _R In the same manner, the difference calculation of the amount of change in the amount of diffuse reflection can remove the amount of common mode interference due to the change in diffuse reflection due to temperature change:

Equations (47) and (48) give the floating reference inner measurement position ρ _I And the floating reference outside measurement position ρ _O Floating reference position ρ _R And effectively obtaining a useful signal relating only to blood glucose concentration change information, and subtracting interference of common mode noise.
As can be seen from equations (41) and (42), the floating reference inner measurement position ρ _I And floating reference outside measurement position ρ _O Is determined, the ratio ΔΦ (ρ of the amount of change in the luminous flux at the two measurement positions due to the temperature change under the same wavelength _I , C _g , ΔT) / ΔΦ (ρ _O , C _g , ΔT) is also a constant and η _Three It is written.

That is:

Then, by using the equations (44), (46) and (50), the difference between the measurement signals at the floating reference inner measurement position and the outer reference measurement position is calculated to obtain the following equation.

As can be seen from equation (51), the floating reference inner measurement position ρ _I And outer measurement position ρ _O By the difference calculation of the amount of change in the amount of diffuse reflection light, the common mode interference amount of change in the amount of diffuse reflection light due to a change in temperature can be similarly removed, and the purpose of obtaining a useful signal relating only to the change in blood glucose concentration can be achieved. As can be seen from FIG. 31, the floating reference inner measurement position ρ due to the blood glucose concentration change _I And outer measurement position ρ _O The direction of the amount of change in the diffuse reflected light at the point is opposite, and employing the difference calculation method in equation (51) increases the absolute value of a weak useful signal, thereby improving the specificity of the signal waiting for measurement. And obtain more accurate measurement results.
A common mode interference signal due to a change in the interference component concentration in the medium to be measured can be subtracted by using a similar method.
(2) Light source drift or detector state drift in the measurement system
When the light intensity of the incident light source drifts or the state of the detector for detecting the diffuse reflection light drifts, both cause a change in the diffuse reflection light intensity value. The blood glucose concentration is relatively constant, for example, when the light intensity of the incident light source drifts. _g When the light intensity of the incident light source changes by ΔF times, the change amount ΔΦ (ρ, C of the light flux Φ (ρ) caused for the same radial position _g , ΔF) are as follows.

Where Φ ₀ (ρ) indicates the initial value of the diffuse reflection light intensity at this measurement position. The radial distance away from the light source is ρ _I And ρ _O Are taken as the floating reference inner measurement position and the outer reference measurement position, respectively, and according to equation (52), the floating reference inner measurement position ρ _I And floating reference position ρ _R And the ratio of the light flux change due to the drift of the light intensity of the incident light source, and the floating reference outside measurement position ρ _O And floating reference position ρ _R The ratios of the luminous flux changes due to the drift of the light intensity of the incident light source are as follows.

Equations (53) and (54) can also be extended to any two measurement positions. Transform the formula
As can be seen, the relative change in light intensity at any measurement position

Are all the same and can be regarded as one fixed value. That is, in FIG. 50, when there is only light source drift interference, one of its action lines is a straight line parallel to the horizontal axis, and the equation (S-3) ) Is about 1, which simplifies equation (S-3) into equation (S-4). That is,

(S-4)
FIG. 51 shows the result of measuring diffuse reflection light with respect to an intralipid 3% solution. By simulating the drift of the light source by changing the output power of the diffused light, after five consecutive changes, three different measurement positions can be found, and the relative change in the diffuse reflected light intensity is consistent A phenomenon is exhibited, in which case the value of ξ can be written as about 1.
Floating reference inner measurement position ρ _I , Floating reference position ρ _R And floating reference outside measurement position ρ _O Is determined and the initial value of the diffuse reflection light intensity at each measurement position is known and determined, so that the ratio ΔΦ (ρ of the change amount of the light flux due to the drift of the light intensity of the incident light source under the same wavelength is obtained. _I , C _g , ΔF) / ΔΦ (ρ _R , C _g , ΔF) and ΔΦ (ρ _O , C _g , ΔF) / ΔΦ (ρ _R , C _g , ΔF) are constants, and η _Four And η _Five That is, there is the following equation.

Therefore, the amount of change in the intensity of the diffuse reflection light due to the drift of the light intensity of the incident light source can be regarded as common mode interference. Where η _Four And η _Five The value of is obtained by repeatedly measuring the amount of change in the diffuse reflection light when the temperature changes when the blood sugar concentration is kept relatively constant, and calculating by the equations (55) and (56).
In the actual measurement process, the glucose concentration is ΔC _g When the light intensity value of the incident light source drifts by ΔF at the same time as the change, the amount of change ΔΦ (ρ, ΔC of the light flux Φ (ρ) due to these two factors at the same radial position _g , ΔF) are as follows.

In the actual measurement process, ΔF is 10 ^-3 ~Ten ^-2 Order and product

Is negligible. Equation (57) can be written as:

Where ΔΦ (ρ, C _g , ΔF) is the common mode interference signal for the radial measurement position, ΔΦ (ρ, ΔC _g , F) are useful signals awaiting measurement.
Then, according to equations (32) and (58), the floating reference inner measurement position ρ _I , Floating reference position ρ _R And floating reference outside measurement position ρ _O At ΔC _g ΔF (ρ) _I , ΔC _g , ΔF), ΔΦ (ρ _R , ΔC _g , ΔF) and ΔΦ (ρ _O , ΔC _g , ΔF) are as follows.

The following equation can be obtained by calculating the difference between equations (59) and (60) using equation (55).

As can be seen from the equation (59), the common mode interference amount of the diffuse reflection light change due to the drift of the light intensity of the incident light source is the floating reference inner measurement position ρ _I And floating reference position ρ _R Thus, a useful signal relating only to the blood glucose concentration change can be obtained.
Similarly, according to equations (56), (60) and (61), the floating reference outer measurement position ρ _O Sum and floating reference position ρ _R Similarly, the common mode interference amount of the diffuse reflection light change due to the drift of the light intensity of the incident light source can be removed by the difference calculation of the diffuse reflection light change amount.

Equations (62) and (63) represent the floating reference inner measurement position ρ, respectively. _I And the floating reference outside measurement position ρ _O Floating reference position ρ _R , And effectively obtains a useful division method relating only to blood glucose concentration change information, and subtracts interference of common mode noise.
As can be seen from equations (55) and (56), the floating reference inner measurement position ρ _I And floating reference outside measurement position ρ _O Is determined, the ratio ΔΦ (ρ of the change amount of the luminous flux at the two measurement positions due to the drift of the light intensity of the incident light source under the same wavelength. _I , C _g , ΔF) / ΔΦ (ρ _O , C _g , ΔF) is also a constant and η ₆ It is written.

That is:

Then, the following equation is obtained by calculating the difference between the measurement signals at the floating reference inner measurement position and the outer reference measurement position by the equations (59), (61) and (65).

As can be seen from equation (66), the floating reference inner measurement position ρ _I And outer measurement position ρ _O In the same way, the purpose of removing the common mode interference amount of the change of diffuse reflection light due to the drift of the light intensity of the incident light source by the difference calculation of the amount of change of the diffuse reflection light at, and similarly obtaining the purpose of obtaining a useful signal concerning only the blood glucose concentration change is achieved And increase the universality of the floating reference measurement method and increase the absolute value of the weak useful signal.
Common mode interference signals due to detector state drift for detecting diffuse reflected light intensity can be subtracted using similar methods.
As can be seen, in operation 503, the spectral data at the first and second radial positions are subjected to difference processing, and the two different interference factors are caused by the common mode by the weighted difference as shown in equation (24). Interference signals can be removed. The diffuse reflection signal measured under other different wavelengths is modified in a similar manner, and the effective signal ΔΦ (λ _i , C _g ) Can be obtained.
According to the embodiments of the present disclosure, it is possible to detect spectrum signals at different positions by adopting different reception schemes.
If the offset of the floating reference position is not very large due to the change of the different measurement sites, different measurement wavelengths or different measurement media of the same measured medium, it is possible to extract the diffuse reflection spectrum at different positions as follows. it can.
1) As shown in FIG. 36A, a spectrum signal at a position inside the floating reference (area A in FIG. 31) from the light source is received as a measurement point, and the floating reference position (area B in FIG. 31) is received. Receive the spectral signal at as a reference point;
2) As shown in FIG. 36B, the light receiving point having the smallest absolute change rate, that is, the point B is selected as the floating reference position, and the light receiving point having the local maximum value of the change rate, that is, the point C is the measurement point. Select as;
3) As shown in FIG. 36 (c), a position inside the floating reference from the light source (area A in FIG. 31), a floating reference position (area B in FIG. 31) and a position outside the floating reference from the light source (area B) The spectrum signals in the area C) in FIG. 31 are simultaneously received, and the weighted difference processing is performed on the spectrum signals inside and outside the floating reference.
Diffuse reflection at different positions when the floating reference position is difficult to determine due to a large offset of the floating reference position due to a change in the part to be measured, a different measurement wavelength or a different medium to be measured on the same medium to be measured, as follows: A spectrum can be extracted. Specifically, the difference in optical parameters greatly affects the determination of the floating reference position for different measurement sites, different wavelengths, or different measurement individuals of the same measurement individual. Therefore, as shown in FIG. Changes, the floating reference position changes correspondingly. As a result, as shown in FIG. 36 (d), the reception radius inside the floating reference is appropriately reduced by using a special expedition in which the inside and outside of the floating reference from the light source include the same noise information, and the outside of the floating reference is reduced. The radial radius is smaller than the floating reference position (area A in FIG. 31) and the floating reference position is increased by increasing the receiving radius to ensure that none of the floating reference positions at each wavelength or location are included. By receiving the larger (area C in FIG. 31) diffusely reflected light, weighted difference analysis calculation is performed on the spectra on both the inside and outside of the floating reference position.
FIG. 37A schematically illustrates an optical fiber probe structure according to an embodiment of the present disclosure. As shown in FIG. 37, the optical fiber probe 1000 can include a plurality of optical fiber bundles 1001, 1003, 1005 and 1007 coated on a clad. One or more fibers may be included for each optical fiber bundle. Among them, an optical fiber bundle 1001 is used to guide incident light from a light source, and optical fiber bundles 1003, 1005, and 1007 are used to guide diffused reflected light from a medium to be measured. More specifically, an optical fiber bundle 1003 is used to guide diffusely reflected light from a radial position inside the floating reference position, and an optical fiber bundle 1005 is used to guide diffused reflected light from the floating reference position. An optical fiber bundle 1007 is used to guide diffusely reflected light from a radial position outside the floating reference position, and these optical fiber bundles converge from the N end. The incident light guided to the optical fiber bundle 1001 can exit from the M end, and the optical fiber bundles 1003, 1005, and 1007 can receive diffuse reflected light from the M end. Thus, the M end can be referred to as a detection end face of the optical fiber probe 1000.
It should be noted that the "fiber optic bundle" described herein is a logical division of these functions. Physically, all fibers may be mixed and there is no clear grouping.
Although FIG. 37A shows four optical fiber bundles, the present disclosure is not limited to this. For example, more or fewer bundles of optical fibers may be included. The arrangement of these optical fiber bundles is not limited to the layout shown in FIG. For example, even the optics in each optical fiber bundle can become entangled in the cladding.
37 (b) to 37 (e) schematically show cross-sectional views at the M end of the optical fiber probe according to another embodiment of the present disclosure. In the figure, each circular pattern can indicate the end face of the fiber in the optical fiber bundle.
As shown in FIG. 37B, an optical fiber bundle 1001 for guiding incident light can be located substantially at the center. The optical fiber bundle 1003 can be installed around the optical fiber bundle 1001 and the optical fiber bundle 1007 can be installed around the optical fiber bundle 1001 and relatively away from the optical fiber bundle 1001. . The optical fiber bundle 1005 can be installed between the optical fiber bundles 1003 and 1007 around the optical fiber bundle 1001. Different sizes of fiber optic probes can be designed depending on the difference in the floating reference position of different devices under test.
In actual measurement, the end face of the optical fiber bundle 1005 is substantially aligned with the floating reference position (if present and fixed, or its approximate range is known), and the diffuse reflection in the optical fiber bundle 1003, 1005 sum 1007 is determined. The optical fiber probe 1000 is left so that the optical signal (ie, the floating reference position and the spectral signals at the inside and outside positions of the floating reference position) can be extracted. Alternatively, the diffusely reflected light signals in the fiber optic bundles 1003 and 1007 (i.e., the spectral signals inside and outside the floating reference; for example, when the floating reference position is not accurately determined or when the end face of the optical fiber bundle 1005 is (If not roughly aligned with the approximate location of the location and not exactly at the floating reference position), or the diffuse reflected light signal at the fiber optic bundles 1003 and 1005 (ie, the spectral signal at the inside and at the floating reference position) ) Or only the diffusely reflected light signals in the optical fiber bundles 1005 and 1007 (ie, the floating reference position and the spectral signal outside the floating reference).
FIG. 37C shows an arrangement including the optical fiber bundles 1001, 1003, and 1005 without including the optical fiber bundle 1007. With such an arrangement, it is possible to receive the spectral signals inside and at the floating reference position.
FIG. 37D shows an arrangement including the optical fiber bundles 1001, 1003, and 1007 without including the optical fiber bundle 1005. With such an arrangement, it is possible to receive the spectral signals inside the floating reference position and outside the floating reference position.
FIG. 37E shows an arrangement including the optical fiber bundles 1001, 1005, and 1007 without including the optical fiber bundle 1003. With such an arrangement, the floating reference position and the spectral signal outside the floating reference position can be received.
Usually, the distance between the end face of the optical fiber bundle 1005 and the end face of the optical fiber bundle 1001 with respect to the floating reference position is a substantially deterministic value (in the above arrangement, the end face of the optical fiber bundle 1005 goes around the end face of the optical fiber bundle 1001). The distance between the end face of the other optical fiber bundle 1003/1007 and the end face of the optical fiber bundle 1001 is within a certain range (in the above arrangement, the end face of the optical fiber bundle 1003/1007). Appears in a ring shape around the end face of the optical fiber bundle 1001).
It should be noted that in FIGS. 37B to 37E, the end faces of the optical fibers in the optical fiber bundles 1003, 1005, and 1007 are turned into a substantially circular shape or a ring shape around the optical fiber bundle 1001. Although shown as closely aligned, the disclosure is not so limited. For example, they may not be tightly arranged and may be sparsely arranged; or they may not constitute a complete circular or ring-shaped pattern, but may constitute only a portion of such a pattern.
In an actual measurement environment, the measurement position and the reference position can be made up of physically achievable points. And includes a circular shape, a ring shape, a rectangular shape, and the like.
According to the embodiment of the present disclosure, the relative change amount of the light intensity is adopted as the spectrum data and is differentiated, and only the measurement information regarding the density change is reserved.
The inventor has already found that the relative change in the light intensity along the radial position ρ also exhibits a linear or linear approximation. With reference to the above-mentioned discussion, as can be seen by combining the description of FIG. 50, for example, the above-described difference processing is similarly applied to the light intensity relative change amount. For example, multiplicative noise can be removed by directly processing the relative change in light intensity at two radial positions; the relative change in light intensity at two radial positions can be factored as described above. By performing weighting difference processing using η, additive noise can be removed.
FIG. 38 shows a general principle of performing density prediction using spectral data. As shown in FIG. 38, the background medium or the reference medium (including the background medium and the specific component of the initial concentration) includes a series of known concentrations {C _i }, And spectral data {I (ρ)} corresponding to the specific component is obtained. These known concentration data set X⌒ and corresponding spectrum data set Y⌒
Thus, a prediction model can be constructed. Then, the unknown density (or density change) C 'of the specific component is set on the background medium or the reference medium. _i , The corresponding spectrum data I ′ (ρ) (“Y”) can be obtained. Based on I ′ (ρ) and the prediction model M, the concentration (“X”) can be predicted.
As described above, the spectral data can include various suitable data, such as light intensity changes and relative changes in diffuse reflection and / or diffuse scattered light.
When modeling, the spectrum of the background or reference medium can be measured as the initial spectrum and the known concentration {C _i The spectrum after the characteristic component {} is inserted can be measured as a measured spectrum, and light intensity change information can be obtained from this spectrum. When predicting, it is also possible to measure the spectrum of the background medium or the reference medium (which may be the same as or different from the initial concentration of the specific component in the reference medium when modeling the initial concentration of the specific component in the reference medium) as the initial spectrum. Thus, the spectrum after the specific component concentration change can be measured as the measurement spectrum, and the light intensity change information can be obtained with this. The predicted value may be a density relative value (that is, a density change amount), and a density predicted value may be obtained by adding an initial value (0 for a background medium; the above initial density for a reference medium). good.
According to the embodiment of the present disclosure, the above-described difference processing is performed on these spectrum data, so that the influence of the interference factor can be effectively removed. For example, the prediction model M is constructed by employing the chemometric method. Specifically, the data after the difference processing is performed can be modeled by employing the least squares method, and a net signal model can be constructed.
The prediction model M is pre-constructed for the background medium / reference medium and the specific component, and can be stored in, for example, a database or a server. When necessary, the prediction model M can be obtained from a database or a server.
Here, such a modeling and / or concentration prediction method is submitted. Referring to FIG. 39, in operation S1201, spectrum data can be acquired. For example, when modeling, the known concentration {C _i }, Spectral data (eg, light intensity change information before the specific component is added) can be obtained for the background medium or the reference medium after the specific component is added; Spectral data (for example, light intensity change information before a specific component concentration change) can be acquired for a background medium or a reference medium in which the specific component concentration has changed. Subsequently, in operation S1203, a difference process can be performed on the spectrum data. For example, the difference process is performed on the spectrum data at two positions having different signs of the light intensity change rate. Then, in operation S1205, modeling or prediction can be performed using the processed difference signal. The processing in FIG. 39 is basically the same when applied to modeling and applied to prediction, and the distinction is as follows: When modeling, the concentration of a specific component is known and the concentration (X⌒ )) And the spectral data (Y⌒); to obtain a prediction model (M); at the time of prediction, the concentration (or concentration change) of a specific component is unknown, and the spectral data (Y) and the prediction model (M) To obtain a predicted density (or density change) (X).
According to an embodiment of the present disclosure, such a modeling / prediction method can be applied to non-invasive blood glucose concentration measurement. In this case, the wavelength of the probe light may be in the range of about 1.0 to 2.4 μm.
According to one example, the floating reference position of the 5% intralipid solution can be determined by the Monte Carlo simulation method, and the drift of the light source can be simulated by changing the number of incident photons.
FIG. 40 shows the result of calculation of the floating reference position of the Monte Carlo simulation for the intralipid solution having a concentration of 5%. The optical parameters used for the simulation, including the absorption coefficient, scattering coefficient, each anisotropy factor and scattering coefficient, were determined by Tamara L. Troy & Suresh N. Thennadil, Optical properties of human skin in the near infrared wavelength range of 1000 to 2200 nm, Journal of Biomedical Optical, 2001, 6 (2): 167-176. The wavelength range of the simulation is 1100-1600 nm. The glucose concentrations are each 0-100 mM, the interval is 10 mM, and the number of photons is 10 ⁹ It is. The difference between the diffuse reflected light by the intralipid solution under different glucose concentrations and the diffuse reflected light by the pure intralipid solution containing no glucose is calculated, the wavelength range is 1100 to 1600 nm, and the floating reference position is about 0.9 to It can be seen that it changes within the range of 2 mm. This shows that the reference position of the same measured individual or sample has a large difference under different wavelengths.
Therefore, the diffuse reflection light receiving method shown in FIG. 36D can be adopted. Specifically, the spectrums at both the inside and outside positions of the floating reference from the light source are simultaneously received. FIG. 41 shows that the number of incident photons is 10 ⁹ FIG. 5 is a diagram of the amount of change in the number of diffuse reflected photons when the glucose concentration changes from 50 mM to 100 mM at a wavelength of 1300 nm in the case of FIG.
Usually, the measured signal is converted to a useful signal _S And the noise signal I related to changes in the human physiological background or external environment _N Divided into

Where I _S Is glucose concentration C _g Is related to _N Is mainly affected by physical factors such as light source drift, temperature, pressure, and displacement. Here, only noise interference due to light source drift will be considered. Thus, the change in the measured light intensity I due to the light source drift and the change in blood glucose concentration is as follows.

Here, ρ is a radial distance between the detector and the light source (a radial position in spherical coordinates in the Monte Carlo simulation), ΔC _g Is the amount of change in blood glucose concentration, and ΔN is the amount of change in the background. ΔI _S (ρ, ΔC _g , N) is valid glucose concentration information, and this part of the information is required. ΔI which is the background interference signal _N (ρ, C _g , ΔN) is irrelevant to glucose concentration information, and usually changes irregularly to give ΔI (ρ, ΔC _g , ΔN) is the main reason for extracting glucose concentration change information.
Reference position ρ _R The diffuse light intensity is not sensitive to glucose concentration change or related to glucose concentration change, and includes the following:

The light intensity change at the reference position is completely caused by background interference and has the following:

Correspondingly, the changes in the diffuse reflected light intensity at the floating reference inner and outer measurement positions are respectively as follows.

Reference position ρ _R Interference change ΔI _N (ρ _R , C _g , ΔN), and the background interference change at the measurement location is fixed,

Where η ₁ And η _Two Is a proportionality coefficient. It should be noted that when selecting different radial positions or different measuring radii as measuring positions, the resulting multiple relationship is different, i.e. an appropriate weighting factor should be selected. In the actual measurement process, it can be obtained by repeatedly measuring when the glucose concentration is kept relatively constant. From Equations (70) to (74), the following effective glucose signal expression can be obtained by the difference operation.

Equation (75) allows for further chemometric modeling analysis to be performed using only the floating reference inner and floating reference measurement location information; Equation (76) allows only the floating reference outer and floating reference location information to be taken. Can be employed to perform chemometric modeling analysis. When the information of the floating reference position is not completely adopted, the following equation is obtained by dividing equations (73) and (74).

This allows the use of a floating reference inner-outer reception scheme to provide a valid measurement signal ΔI _IO (ΔC _g ) Can be obtained.

The blood glucose information obtained by differentially processing the diffuse reflection signal based on the floating reference position has higher specificity than the diffuse reflection light intensity change information obtained by direct measurement, and the actual measurement The background interference in is effectively subtracted.
In this embodiment, the drift of the light source is simulated by changing the number of incident photons, and the change range is ± 20%. As can be seen from FIG. 40, since the floating reference position of glucose is about 1.3 mm at a wavelength of 1300 nm, the radial position is 0.7 to 0.9 mm as shown in area A in FIG. It can be selected as a floating reference inner measurement position and the measured spectrum is I (ρ _I ); As shown in area B in FIG. 41, a position whose radial position is 1.3 mm is selected as a floating reference position, and the measured spectrum is I (ρ _R 41); a position at a radial position of 1.8 mm to 2.0 mm is selected as a floating reference outside measurement position as in the area C in FIG. 41, and the measured spectrum is I (ρ _O ).
If glucose is not contained in the solution, that is, if only the noise signal of the light source drift is contained, the same measurement position will emit a corresponding noise signal with the light source drift. Table 1 shows the number of diffusely reflected photons at different measurement positions with different numbers of incident photons, obtained from the results of the Monte Carlo simulation. 10 incident photons ⁹ Table 2 shows the amount of change in the number of diffusely reflected photons at an appropriate measurement position when the value changes by ± 20%. The relative change in the number of diffusely reflected photons is shown in Table 2-1. As can be seen, at the three measurement positions, the relative changes in the number of diffusely reflected photons basically match. Therefore, the ratio の of the relative change amount of the number of diffused photons at any two positions is about 1.

At this time, since the glucose concentration does not change, the measured signal change is completely caused by a change in light source drift, that is, the signal change measured at this time is considered to be a noise signal. Therefore, as shown in Table 3, the ratio of noise interference at different measurement positions can be calculated.

The ratio of the absolute change amount of the noise interference at any two positions in Table 3 is also directly obtained by the following method. Since ξ is determined to be 1, the value of η can be directly obtained by using the equation (S-3) as shown in Table 3-1.

Comparison between Table 3 and Table 3-1 shows that the actually obtained value of η basically matches the value of η estimated by using the equation (S-3).
As can be seen from Tables 3 and 3-1, when the glucose concentration does not change and only the light source drifts:
Change amount ΔI of floating reference inner measurement position signal _N (ρ _I , ΔC _g , ΔN) is the variation ΔI of the floating reference measurement position signal. _N (ρ _R , ΔC _g , ΔN) is about 7.0 times, that is, ΔI _N (ρ _I , ΔC _g , ΔN) = 7.0ΔI _N (ρ _R , ΔC _g , ΔN);
Variation ΔI of floating reference outside measurement position signal _N (ρ _O , ΔC _g , ΔN) is about 1.06 times the amount of change of the floating reference measurement position signal, that is, ΔI _N (ρ _o , ΔC _g , ΔN) = 1.06ΔI _N (ρ _R , ΔC _g , ΔN);
Change amount ΔI of floating reference inner measurement position signal _N (ρ _I , ΔC _g , ΔN) is the variation ΔI of the floating reference outside measurement position signal. _N (ρ _O , ΔC _g , ΔN), that is, ΔI _N (ρ _I , ΔC _g , ΔN) = 6.6ΔI _N (ρ _O , ΔC _g , ΔN).
If both the glucose concentration and the light source change, the change in light intensity at the floating reference position is not related to the change in glucose concentration, i.e., the change in light intensity at this position is completely caused by the light source drift. Therefore, useful signals according to the glucose concentration change inside and outside the floating reference obtained by the equations (75) and (76) are as follows, respectively.

Table 4 shows the glucose concentration and the number of incident photons corresponding to six different concentrations of glucose diffuse reflection spectrum, respectively.

When the glucose concentration changes by 20, 40, 60, 80, and 100 mM, respectively, as shown in FIG. 42 when the light source drift is not corrected, the diffuse reflection photon number change curve at different radial positions away from the light source. That is, the curve for measuring the diffuse reflection light intensity does not exhibit a regular increasing or decreasing change depending on the glucose concentration. That is, the signal change due to the light source drift covers the characteristic signal of the glucose concentration change.
Similarly, the floating reference inner measurement position is set to 0.7 to 0.9 mm, the reference position is set to 1.3 mm, and the outer measurement position is set to 1.8 to 2 mm. Before correcting for light source drift, as shown in Table 5, the value of the change in the number of diffuse reflected photons at each measurement position under a change in glucose concentration is obtained.

Equations (79) and (80) are used to combine the information of the floating reference position to correct the light source drift for the variation in the number of diffuse reflected photons inside and outside the measurement position at the floating reference. It is shown in Table 6.

As can be seen from FIG. 16, at the floating reference inner measurement position, as the glucose concentration change increases, the number of diffusely reflected photons changes so as to gradually decrease, and the amount of change is a negative value; As the glucose concentration change increases, the number of diffuse reflected photons changes so as to gradually increase, and the amount of change is a positive value. That is, the influence of the light source drift is effectively removed.
If the measurement information at the floating reference position is not completely adopted, as can be seen from the above calculation, the variation ΔI of the floating reference inner measurement position signal _N (ρ _I , ΔC _g , ΔN) is the variation ΔI of the floating reference outside measurement position signal. _N (ρ _O , ΔC _g , ΔN), that is, ΔI _N (ρ _I , ΔC _g , ΔN) = 6.6ΔI _N (ρ _O , ΔC _g , ΔN) and the floating reference inner and outer measurement signals measured by equation (78) are subjected to a weighted difference operation to obtain:

That is, the obtained signal is a weighted sum of the floating reference inner and outer effective signals, and completely eliminates noise due to light source drift.
Formula (81) is adopted, and the floating reference position information is not completely adopted, but only the measurement signal inside and outside the floating reference position is adopted to correct for the situation where not only the glucose concentration change but also the light source drift exists. Then, ΔI at different calculated glucose concentration changes _IO (ΔC _g ) The results are shown in Table 7. What appears in the results is that the effective signal ΔI obtained by the weighted difference processing for the floating reference inner and outer measurement signals with the increase in the glucose concentration change amount _IO (ΔC _g ) Shows a tendency to increase gradually in order to effectively eliminate the influence of common mode interference due to light source drift.

The effective signal ΔI under each wavelength obtained by correcting the light source drift by adopting a similar method to the spectrum signal measured under other different wavelengths and further performing weighting difference processing _S (λ _i ) Can be combined with the corresponding series of reference concentration parameters to construct a partial least squares mathematical model and predict the concentration of the unknown concentration spectrum.
According to another example, it is possible to analyze the situation when the temperature to be measured changes with the inside-outside of the floating reference from the light source as a receiving plan by the Monte Carlo simulation method.
It has been found that for a 2% intralipid solution, if the wavelength is greater than 1400 nm, there is no floating reference position, that is, if the wavelength is greater than 1400, the theory of the floating reference measurement method does not apply. For this purpose, a Monte Carlo simulation is performed on the situation of changes in diffuse reflected light due to glucose concentration and temperature at a wavelength of 1600 nm using an intralipid solution having a concentration of 2% as a model. Glucose concentration change range is 0 to 100 mM, interval is 20 mM; temperature change range is 32 ° C. to 40 ° C., interval is 0.5 ° C .; ¹¹ And the number of absolute photons diffused and reflected after passing through the sample is defined as output light. When the temperature changes, the amounts of change in the absorption coefficient and the scattering coefficient are as follows.

Taking only 1600 nm as an example and changing only the temperature, FIG. 52 shows the relative change amount of the diffused light depending on the obtained temperature based on the emitted light of 32 degrees.
As can be seen, there is a position that is not sensitive to temperature changes near the light source-probe distance of 2 mm and can be referred to as a “temperature reference position”. Further, after a certain distance from the light source, a change rule in which the relative change in light intensity between different positions is linearly approximated within a certain range. It should be noted that after too far from the light source, the outgoing light drops abruptly, which increases the noise effect, which in turn has a large effect on the measurement. Here, the situation where the noise is too large should not be considered. When the two measurement positions are fixed, the value of ξ can be estimated from FIG. Further, the value of η can be directly obtained by using the equation (S-3).
In order to accurately obtain the value of η, the calculation is performed based on the amount of noise actually generated after a temperature change.
When the glucose concentration changes by 60 mM and 100 mM at the temperatures of 32 ° C., 35 ° C., 38 ° C., and 40 ° C., respectively, the amounts of diffuse reflection light changes at different positions are obtained, and the distribution diagram shown in FIG. 44 is obtained. As can be seen, at this wavelength, we assume that there is no floating reference position, because there is really no one radial position where the sensitivity due to changes in glucose concentration is always kept near zero. . However, at any one temperature, there is a radial position where the amount of change in diffuse reflection due to changes in glucose concentration is always negative, and the amount of change in diffuse reflection within this area is higher in absolute value and stability Having. Therefore, in this area, two radial positions can be selected as two measurement positions and used to remove common mode interference noise when there is no floating reference position.
A radial position of 0.6 to 1 mm is selected as a measurement position 1 and a radial position of 1 to 2 mm is selected as a measurement position 2. If the solution contains no glucose, i.e., only changes with temperature, different radial positions will produce a corresponding noise signal with changes in temperature. By Monte Carlo simulation, the number of diffusely reflected photons at different measurement positions in the radial direction at different temperatures can be obtained. When the temperature changes from 32 ° C. to 40 ° C. based on 36 ° C., that is, when the temperature changes ± 4 ° C., the amount of change in the number of diffusely reflected photons detected at the two measurement positions is shown in Table 8.

At this time, since the glucose concentration does not change, the measured signal change is completely caused by the temperature change, that is, the signal change measured at this time is considered to be a noise signal. Therefore, the ratio of the noise interference can be calculated at the two measurement positions, and the ratio of the change amount of the diffuse reflection photons at the measurement position 2 to the change amount of the diffuse reflection photons at the measurement position 1 is about 0.17 due to the temperature change. It is. That is, it can be described as follows.

Therefore, when the glucose concentration and the temperature are all changed, ρ is calculated by the equation (84). ₁ And ρ _Two The effective signal for removing the common mode interference due to the temperature due to the obtained glucose concentration change by performing a difference operation on the amount of change of the diffuse reflection light in the following is as follows.

It is considered that there is no relationship between glucose concentration and temperature because the correlation coefficient between glucose concentration and temperature is -0.01918 by randomly selecting glucose diffuse reflection at different concentrations at six different temperatures. The simulation simulates a situation in which the glucose concentration changes in the actual measurement process and the temperature also generates an irregular drift. The corresponding glucose concentration and temperature conditions are as shown in Table 9.

When the data of the first group is in the state of the measurement start time and is not corrected for the interference signal due to the temperature change, as shown in FIG. 45, when the glucose concentration changes by 20, 40, 60, 80 and 100 mM, respectively, A change curve of the number of diffusely reflected photons at the same two measurement positions is obtained. In the figure, the curve for measuring the amount of change in the diffuse reflection light intensity does not exhibit a regular increase or decrease change due to the change in glucose concentration, and the signal change due to the temperature change covers the characteristic signal of the glucose concentration change. .
The change in temperature is corrected for the amount of change in the number of diffusely reflected photons at two measurement positions by using equation (85), and the calculation result is as shown by the curve in FIG. As can be seen from the figure, the absolute value of the signal at the two measurement positions is smaller than the signal value at the two measurement positions before the correction, and the absolute value of the curve is smaller. It exhibits a regular step-by-step change with the change in glucose concentration, and achieves the object of eliminating common mode interference due to temperature drift.
According to another example, a polycyclic optical fiber measuring system based on an SLD light source is adopted, and a situation where the light source drifts is analyzed with an intralipid solution having a concentration of 3% as a measurement waiting target.
What is measured by experimental analysis is that for a wavelength of 1219 nm, the floating reference position of glucose in a 3% concentration of intralipid solution is approximately 3.0-3.2 mm. As a result, this position is selected as a floating reference position signal detection ring for the polycyclic optical fiber probe. In consideration of the machining process, the position at a radial position of 0.24 to 0.96 mm is defined as an inner measurement position signal detection ring, and the position at a position of 3.2 to 4.1 mm is defined as an outer measurement position signal detection ring. A polycyclic optical fiber probe having the structure shown in FIG.
In the experimental process, the power of the SLD was changed randomly to simulate the irregular drift phenomenon of the light source, and when the wavelength became 1219 nm, the diffuse reflection light intensity at three different radial positions at different times was calculated. When the light source drifts, assuming that the first measurement is the initial measurement, the amount of change in the diffuse reflection is the difference between the measured light intensity in the initial state and the measured light intensity in the initial state. Obtained by performing calculations. This makes it possible to calculate the ratio of the amount of change in the diffuse reflection light signal value at the three measurement positions due to the light source drift. What is obtained by the calculation is that the amount of change in the diffuse reflected light signal value due to the light source drift at the floating reference outside measurement position is about 0.84 of the signal change amount at the floating reference position, and the signal at the floating reference position is The change amount is about 0.7 times the signal change amount at the floating reference inside measurement position, and the signal change amount at the floating reference outside measurement position is about 0.58 times the signal change amount at the inside measurement position. is there. These are used to correct the signal as a difference proportional coefficient when the light source state and the glucose concentration change at the same time, that is, it can be considered approximately as follows.

Next, six samples having a glucose concentration range of 1000 to 6000 mg / dL and an interval of 1000 mg / dL are arranged using the intralipid solution having a concentration of 3% as a mother liquor, and six glucose intralipid solutions are measured in random order. Simultaneously change the power of the SLD to simulate the irregular drift phenomenon of the light source, measure the diffuse reflection light intensity at three radial positions at different times, and compare the diffuse reflection light intensity of the sample solution with the diffuse reflection light intensity of the sample solution. The difference calculation is performed on the diffuse reflection light intensity in the initial state, and when the light source drift and the glucose concentration change at the same time, the amounts of change of the diffuse reflection light at the three measurement positions are calculated. As shown in FIG. As can be seen from the results, the light source drift has a significant effect on the glucose concentration detection, and due to the random nature of the light source drift, any of the signals measured at the three positions loses a linear relationship with the glucose change, That is, since the amount of change of the diffuse reflection light intensity signal due to the light source drift completely covers the effective information of the glucose concentration change, it is necessary to correct the measured light intensity signal.
Due to the proportionality of equations (86), (87) and (88), diffuse reflection light intensity jointly caused by glucose concentration change and light source drift using equations (75), (76) and (78) The signal has been modified and the results are as shown in FIG. As can be seen from the results, weight difference processing is performed by employing signals at any two positions, and the corrected light intensity signal shows a clear linear relationship with the glucose concentration change, and the light source drift for the glucose concentration detection. The influence is reduced or eliminated, and effective information of the glucose concentration change can be effectively extracted. As can be seen from the results, the effective signal corrected by adopting the signal at the inner ring and the reference ring measurement position and the signal at the outer ring and the inner ring measurement position is used at the outer ring and the reference ring measurement position. Is significantly larger than the effective signal modified by adopting this signal, and as the radial distance from the light source increases, the diffuse reflection intensity value decays exponentially. The effect of using the inner and outer rings and the effect of using the inner and reference rings are in harmony with each other, but when using the inner and outer rings to detect and correct the signal, measurement using the reference ring is performed. The use of a signal is no longer required, and there is no need to be affected by changes in the measurement wavelength with respect to the floating reference position, the state of the measured object itself, and the like, effectively enhancing the universality of the signal correction method.
In the above analysis, a proportional coefficient due to light source drift is calculated using a pure intralipid solution having a concentration of 3%, and the subsequent signal processing is performed using the proportional coefficient as an initial state of measurement. Similarly, following similar steps, for glucose solution samples containing different concentrations, first calculate the appropriate proportionality factor under random drift of the light source, and then use this concentration sample as the initial state of measurement for the subsequent signal Processing can be performed. Samples having glucose concentrations of 3000 and 6000 mg / dL are respectively used to calculate a proportional coefficient used for spectrum correction, and to use the same as an initial state of measurement to correct a spectrum signal, thereby obtaining glucose as shown in FIGS. 47 and 48. The results of signal correction were obtained using samples having concentrations of 3000 and 6000 mg / dL as initial states, respectively. As can be seen from the figure, glucose solutions having different concentrations were used as initial states to reduce common mode interference due to light source drift or The purpose of elimination can likewise be achieved, in which the signal at the inner and outer measuring positions, and the effect modified by employing the signals at the inner and floating reference positions, has the signal at the outer and floating reference positions. Also appears to be superior to the modified effect, and the conclusion obtained is pure intralip Are consistent with the case where the signal correcting the d solution as the initial sample. It should also be noted that no matter what kind of glucose concentration sample is used as the initial state, signal correction is performed as the initial state. The measured glucose concentration at time should be the sum of this change and the initial glucose concentration.
FIG. 49 illustrates an example of the arrangement of the measurement system according to the embodiment of the present disclosure.
As shown in FIG. 49, the measurement system may include a light source 2201, a coupling system 2203 for adapting light from the light source 2201 to be coupled to an optical fiber, an optical fiber probe 2205, and a processing device 2209. it can.
Light source 2201 can include any suitable light source that can emit light of the required wavelength. For example, in the near infrared range, halogen lamps can be used as a continuous light source. Alternatively, light source 2201 can also include a supercontinuum pulsed laser light source.
The coupling system 2203 converts the linearly polarized light from the Gran prism 2203-1 and the Granular prism 2203-1 into + 1st-order light (or-) whose polarization state is orthogonal to the 0th-order light to convert the light from the light source 2201 into linearly-polarized light. An acousto-optic tunable filter (AOTF) 2203-2 for separating (diffracting) the primary light), a Glan prism 2203-3 provided orthogonal to the Glan prism 2203-1 to remove the zero-order light, And a coupler 2203-4 for coupling + 1st order light (or -1st order light) from the grand prism 2203-3 to a successor device.
Note that FIG. 49 illustrates one specific example of a coupling system, but the present disclosure is not so limited. The industry is aware of multiple coupling systems and can couple light from a light source into a fiber optic system.
The optical fiber probe 2205 may include, for example, the structure described above with reference to FIG. Specifically, the coupling system 2203 can couple the light from the light source to the incident optical fiber bundle (for example, 1001 in FIG. 37) of the optical fiber probe 2205, and the incident optical fiber bundle transmits the light to the medium 2207 to be measured. Can be guided. Then, the probe optical fiber bundle (for example, two or more of 1003, 1005 and 1007 in FIG. 37) in the optical fiber probe 2205 can guide the diffuse reflection light of the medium to be measured 2007 to the processing device 2209.
The processing unit 2209 can include a probe 2209-1 (eg, a photoelectric probe), which is used to detect an optical signal from the optical fiber probe, converts it into an electrical signal, and further processes the electrical signal. Can be provided to The probe 2209-1 can detect spectral data at a plurality of radial positions (for example, at the inside of the floating reference position, at the floating reference position and / or outside the floating reference) depending on the arrangement of the optical fiber probe.
The processing unit 2209 further includes a processor 2209-2. The processor 2209-2 can be arranged to perform the above-described difference processing on the spectral data detected by the probe 2401. Specifically, the processor 2209-2 selects two radial positions where the light intensity of the diffuse reflected light has a sign change rate different from that of the specific component in the medium to be measured, and the two radial positions are selected. Weighted difference processing can be performed on the spectral data at the position.
The processor 2209-2 may include various types of computing equipment such as, for example, a general-purpose computer, a dedicated integrated circuit (ASIC), an FPGA, and the like. The processor 2403 operates according to the above-described methods and processes by loading programs, code segments, and the like stored in the storage device to realize spectral data subtraction processing, model building, and concentration prediction. it can.
The processing device 2209 includes, for example, an input device 2209-3 for inputting user commands and data such as a mouse and a keyboard, and a processing result of the processor 2403 such as a display (for example, a separated scattered signal / absorption). And an output device 2209-4 for outputting signals, prediction results, etc.). The input device 2209-3 and the output device 2209-4 can be combined to be realized as a touch panel.
The technology of the present disclosure can be implemented to include a program of an algorithm that can be executed by a data processing device, or can be provided by being stored in a non-transitory computer-readable medium.
The technology of the present disclosure can be implemented as computer-readable code on a computer-readable medium. The computer-readable medium includes a computer-readable recording medium and a computer-readable transmission medium. A computer-readable storage medium is any data storage device that stores data as a program that can thereafter be read by a computer system. Examples of the computer-readable recording medium include a read-only memory (ROM), a random access memory (RAM), a seed ROM (CD-ROM), a tape, a disk, and a storage device for optical data. The computer readable storage medium may be distributed in a computer system connected to the Internet, so that the computer readable code is stored and executed in a distributed format. Computer readable transmission media can be transmitted by carrier waves or signals (eg, wired or wireless data transmission over the Internet). In addition, the functional programs, codes, and code segments that realize the disclosed technology can be easily interpreted by a programmer in this field of the overall concept of the present invention.
As described above, a plurality of embodiments have each described a plurality of features of the present disclosure. However, this does not mean that these features are advantageously combined and cannot be used.
The embodiments of the present disclosure have been described above. However, these examples are illustrative and do not limit the scope of the present disclosure. The scope of the present disclosure is limited by the claims and their equivalents. One skilled in the art can make multiple substitutions and amendments without departing from the scope of the present disclosure, and all such substitutions and amendments should be included in the scope of the present disclosure.

Claims (32)

In predicting changes in the concentration of a particular component in the detected medium based on the diffusion spectrum data of the medium,
At one or more first radial locations, diffuse spectral data of the medium is acquired and optical information is determined according to scattering-insensitive and / or absorption-insensitive points, and the scattering characteristics are determined. A method for processing spread spectrum data, comprising obtaining optical information that is insensitive and / or insensitive to absorption characteristics . Utilizing the processing method according to claim 1, based on the spread spectrum data of the medium, a method of predicting a change in the concentration of a specific component in the medium detected with respect to a certain reference,
One or more first Radial position, a step of acquiring the spread spectrum data of the medium,
From the obtained spread spectrum data, at one or more second radial positions, optical information resulting from substantially only a change in the scattering characteristic of the medium to be detected with respect to the reference, or the detection target with respect to the reference Determining at least one of the optical information due to only the variation of the absorption characteristics of the medium,
And estimating a change in the concentration of the specific component based on the determined optical information insensitive to scattering properties and / or insensitive to absorption properties . Obtaining a spread spectral data, a step to acquire the spread spectrum data in at least two radial positions, and the spread spectrum data in a linear fit (linear fitting) one or more first radial position by method The method of claim 2, comprising determining. The at least two radial positions comprise a composite reference point , the reference point of which the light intensity information contained in the spectral data is substantially insensitive to variations in the concentration of the particular component in the medium. 4. The method of claim 3, wherein the method comprises: Wherein the step of determining the optical information, the insensitive point or absorption in the scattering comprising the step of performing a non-sensitive decisions based on at least one point, here, non-functional point the scattering spectrum The light intensity information contained in the data indicates a radial position that is substantially insensitive to fluctuations in the scattering properties of the medium being detected, and the point insensitive to absorption is the light contained in the spectral data. 3. The method of claim 2, wherein the intensity information indicates a radial position that is substantially insensitive to variations in the absorption characteristics of the detected medium. The medium to be detected includes a background medium and specific components contained in the background medium, and the method further comprises determining a point that is insensitive to scattering / absorption at the first wavelength, the step comprising: A step of preparing a scattering medium containing a medium or a background medium and a specific component at a constant concentration; and the coefficient of the scattering / absorption characteristics of the scattering medium is changed, but the absorption / scattering characteristics of the scattering medium are as described above. Obtaining a light intensity variation when substantially unchanged at the first wavelength; and determining a point insensitive to scattering / absorption as a radial position where the light intensity variation is substantially zero. The method of claim 5, comprising: The method of claim 5, wherein the point insensitive to absorption is at a radial position of approximately zero. 6. The method of claim 5, further comprising determining, at each of the plurality of wavelengths, points that are insensitive to scattering or points that are insensitive to absorption . The determining comprises obtaining spread spectrum data at least one of a scattering insensitive point or an absorption insensitive point; and
Substantially determine the optical information attributable only to the variation in the absorption characteristics of the detected medium at points that are insensitive to absorption and the diffuse spectral data of points that are insensitive to scattering, or to the insensitivity to scattering. 6. The method of claim 5, comprising determining optical information attributable to only the spread spectrum data of points that are insensitive to fluctuations and absorption of the detected medium at different points. The step of obtaining the spread spectrum data comprises selecting a second wavelength that is close to the first wavelength, where a particular component contained in the medium to be detected is relatively weak or has substantially no absorption. And obtaining the spread spectrum data at the first wavelength and the second wavelength, respectively, wherein the method further comprises the step of: being insensitive to scattering at the first wavelength. Determining the point at which the spread spectrum data at the second wavelength is not susceptible to scattering at the second wavelength as the radial position at which the light intensity exhibits substantially zero variation in light intensity. 6. The method of claim 5, comprising the steps of: and determining a point insensitive to scattering at the first wavelength at a point insensitive to scattering at the second wavelength. The step of acquiring the spread spectrum data includes acquiring diffuse spectrum data at least one of a point insensitive to scattering or a point insensitive to absorption,
The step of determining the optical information includes, as optical information resulting from only a substantial change in the absorption characteristics of the medium detected at the point insensitive to scattering, the spread spectrum data at the point insensitive to scattering. Determining the spread spectrum data at the absorption-insensitive points, as optical information caused by substantially only fluctuations in the scattering properties of the medium at the absorption-insensitive points, The method of claim 5. The step of acquiring the spread spectrum data includes the step of acquiring, for each wavelength from among a plurality of wavelengths, at least one of a point insensitive to scattering and / or a point insensitive to absorption. The method of claim 11. Further, for each wavelength from a plurality of wavelengths, a step of acquiring spread spectrum data at at least one fixed radial position, for each wavelength from the plurality of wavelengths from the obtained spread spectrum data, 13. The method according to claim 12, comprising determining spread spectrum data at least one of a point that is insensitive to scattering and / or a point that is insensitive to absorption. Obtaining the spread spectrum data comprises selecting a second wavelength close to the first wavelength where the particular component contained in the medium to be detected is relatively weak or has substantially no absorption; Acquiring spread spectrum data at the first wavelength and the second wavelength, respectively.
The step of determining the optical information includes the steps of:
Determining optical information due to substantially only the variation in the scattering properties of the medium to be detected at the first wavelength; and determining the optical information of the medium detected at the first wavelength based on the spread spectrum data at the first wavelength. 3. The method of claim 2, including the step of determining optical information due to substantially only variations in absorption characteristics. Said step of predicting is performed on the basis of the predictive model, the prediction model, the following steps, namely, a step of acquiring a fragment of the spread spectrum from a series of media, wherein each set of media, A background or reference medium comprising a known component of a known concentration is included, wherein the reference medium comprises the background medium and an initial concentration of the particular component, and at least the optical information comprises a series of media relative to the background or reference medium. Determined solely due to fluctuations in each scattering characteristic or from the resulting scattering spectrum solely due to fluctuations in the respective absorption characteristics of the series of media relative to the background or reference medium at one or more second radial positions. And a step of establishing a predictive model based on each known concentration and the determined optical information of each medium. The method of claim 1, wherein The optical information indicates substantial linearity, and the prediction model indicates the optical information.
16. The method of claim 15, wherein the method is established based on a slope of the information. The reference includes a background or reference medium, where the reference medium is a background medium and a specific component.
17. The method of claim 15, wherein the method comprises the steps of: 18. The method of claim 17, wherein the step of establishing the model and the step of predicting are performed based on the optical information substantially due to only the variation in the absorption characteristics . The spread spectrum data used in the process of setting the model and in the prediction step includes light intensity, absolute change in light intensity, relative change in light intensity, absorption coefficient, absolute change in absorption coefficient, and relative change in absorption coefficient. 19. The method of claim 18, comprising at least one in a variation, or other amount associated therewith. The background or reference medium used in the process of establishing the model is the background of the predicted medium.
20. The method of claim 19, wherein the method is different from the reference medium. In addition, before predicting the concentration change according to the prediction model, a different background or reference medium
21. The method of claim 20, comprising pre-processing the diffusion media data based on a ratio of the absorption coefficients between . 22. The method of claim 21, wherein the step of establishing the model and the step of predicting are performed based on the optical information resulting substantially only from variations in the scattering properties. The spread spectrum data used in establishing and predicting the model includes light intensity, absolute change in light intensity, relative change in light intensity, scattering coefficient, absolute change in scattering coefficient, relative scattering coefficient. 23. The method of claim 22, wherein the method comprises at least one of a variation, or other quantity associated therewith. The background or reference medium used in the model establishment is the medium to be predicted.
24. The method of claim 23, wherein the method is different from a body background or a reference medium. 25. The method of claim 24, further comprising the step of pre-processing the diffusion media data based on a ratio of scattering coefficients between different background or reference media before predicting the concentration change according to the prediction model . The step of predicting the concentration, under unit variation of the concentration of the interference component, a step of obtaining a scattered signal of the interference component other than the specific component,
Predicting the concentration of the interference component according to the interference component prediction model based on the spectral data of the medium detected at a point not affected by scattering;
By multiplying the scattering signal under variation of unit concentration to the concentration of interfering components, and obtaining a further scattering signal of the interference component in the base Ki medium to be detected,
Removing further scattered signals of the interference component from the spectral data of the medium to be detected; and
18. The method of claim 17, comprising estimating a concentration of a particular component based on the spectral data with additional scattered signals of the interfering component removed . 3. The method of claim 2, wherein the spread spectrum data comprises differential spread spectrum data of the medium detected with respect to the reference. A method for predicting concentration, comprising:
Obtaining an absorption coefficient or absorbance for each of a series of media, wherein each media comprises a pure absorbent background medium, each of which contains a known concentration of a particular component in a pure absorbent background medium ; Establishing a predictive model based on the concentration and the respective absorption coefficient or absorbance;
A step of acquiring diffusion spectrum data of the medium to be detected at a point not affected by scattering, wherein the medium to be detected is a scattering background medium and a specific component of an unknown concentration caused by a change in concentration from the initial concentration. And estimating the concentration of a particular component according to a predictive model based on the diffuse spectral data of the medium to be detected at points that are insensitive to scattering, wherein the points insensitive to scattering are provided. The method of claim 1, wherein the light intensity information included in the spectral data indicates a radial position that is substantially insensitive to variations in scattering characteristics of the detected medium.   The prediction model is established based on the relative variance of the respective extinction coefficient or absorbance at each known concentration and the respective known concentration at the known concentration relative to the extinction coefficient or absorbance at the particular zero concentration. 29. The method of claim 28, wherein the method is performed.   The spread spectrum data includes at least one of light intensity, an absolute change in light intensity, a relative change in light intensity, an absorption coefficient, an absolute change in absorption coefficient, a relative change in absorption coefficient, or another amount related thereto. 29. The method of claim 28, comprising and pre-processed by a ratio of absorption coefficients between a scattering background medium and a pure absorbing background medium for concentration prediction by a prediction model. The medium contains specific components therein and is configured to detect the spectrum of the medium to be detected, and the optical information, or the object to be detected, caused only by fluctuations in the scattering properties of the medium to be detected relative to a reference A processor configured to determine at least one of the optical information caused by substantially only a change in the absorption characteristics of the medium of the medium, wherein the determination is made relative to a reference at one or more radial positions from the detection of the detector. A processing device for predicting a change in concentration of a specific component with respect to a reference based on the obtained optical information. Based on the diffusion spectrum data of the scattering medium, in predicting changes in the concentration of a specific component in the detected medium,
Obtaining spread spectrum data of a medium at one or more first radial positions, determining optical information according to scattering-insensitive points, and obtaining optical information insensitive to scattering characteristics The spread spectrum data processing method according to claim 1, wherein:

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