CN112022167A - Noninvasive blood glucose detection method based on spectral sensor - Google Patents
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Abstract
The invention relates to a noninvasive blood glucose detection method, in particular to a noninvasive blood glucose detection method based on a spectrum sensor; the technology for detecting the blood sugar by the spectrum sensor in a non-invasive way is broken through, the improved near infrared spectrum transmission measurement technology is adopted, an original calibration mechanism is adopted, no material consumption is caused, the clinical verification data is accurate, the influence of the personal state and the environmental change of a human body is small, the error is less than +/-15%, and the method can be compared favorably with detection equipment with wounds; the method comprises the following steps: the method comprises the following steps: a spectrum sensor is designed at the fingertip position, and an LED is designed at the other side relative to the fingertip position; step two: a tunable filter of a Fabry-Perot interferometer is adapted in the spectrum sensor, and the optical receiving range of the tunable filter is adjusted to reach the nm level; step three: light rays emitted by a 1650nm LED penetrate through human tissues and are collected by a spectral sensor with the wavelength of 1350nm to 1650 nm; step four: the light emitted by 1720nm LED is collected by 1550nm-1850nm spectrum sensor after passing through human tissue.
Description
Technical Field
The invention relates to a noninvasive blood glucose detection method, in particular to a noninvasive blood glucose detection method based on a spectrum sensor.
Background
By 2019, the international diabetes alliance issued "global diabetes overview", has a total of about 4.63 million diabetics in 20-79 years of age worldwide, with chinese diabetics ranked first, with a total of about 1.164 million people, a second in india, about 7700 million diabetics, and a third in the united states, 3100 million diabetics.
Blood sugar detection is a key link in diabetes treatment, but blood (venous blood or fingertip blood) is required to be taken in traditional detection, and the blood taking trauma causes difficulty in daily blood sugar monitoring of patients. This has also been a problem that has plagued the medical community for many years (at least 74% of patients do not comply with the physician's order to test blood glucose). The following is a conventional way of blood glucose testing at the present stage:
venous blood detection: in the traditional detection method, a subject needs to draw venous blood in a medical institution and waits for 2 to 3 hours for the result.
Detecting blood of a fingertip: the portable equipment which occupies the market leading position adopts a small amount of fingertip blood in a traumatic manner, the use is not limited by the environment, the result is obtained in about ten seconds, the consumable is a test strip, and the comprehensive cost is 5-10 yuan each time; the error range is +/-15-20%.
Minimally invasive wound detection and continuous monitoring: several minimally invasive test devices are continuously marketed after 2016, a sensor is fixed on the upper arm or the abdomen, a probe with the length of about 5mm penetrates into the skin, the skin tissue fluid is detected, the blood sugar is calculated, continuous monitoring for several days (recording every 15 minutes) can be realized, and the numerical value is read by a special matching instrument. The consumable is a sensor, and the daily use cost is 30-40 yuan; the error range is +/-20%.
The near infrared spectrum blood sugar detection technology is expected to realize noninvasive detection all the time, but the reasons for preventing the noninvasive detection by the near infrared spectrum blood sugar detection technology are mainly as follows:
(1) weak signal
More than 90% of human blood is water, the proportion of the blood is only 7-8%, and the content of blood sugar in the blood is very low; moreover, water absorbs near infrared light seriously, which causes serious interference to noninvasive detection; in addition, the core of the near infrared spectral band is the frequency doubling and combined frequency absorption of molecules, the absorption peaks are wide and are overlapped seriously, and the absorbance magnitude has magnitude difference compared with the fundamental frequency of the mid infrared. In view of the above, if the change information of the blood glucose component with a weak content is to be detected accurately, a higher requirement is put forward on the performance of the spectrum acquisition system.
(2) Background interference
Human tissues such as skin, muscle, bone and the like all belong to strong near-infrared absorbers, human spectra carry a large amount of interference information related to the tissues, and effective information which can be used for analysis is easily submerged in a strong background. Therefore, the tissue background interference problem is one of the important reasons for influencing the accuracy of non-invasive blood glucose detection.
How to extract effective information from the strong background spectrum is a key problem to be solved for noninvasive detection of blood glucose by near infrared spectrum.
(3) Individual difference
The tissue characteristics of blood, skin, muscle and the like are greatly different among different individuals, even the tissue background components of different parts of the same individual are different, which causes the acquired spectrum background noise to be complicated, and further increases the difficulty of extracting the blood component information from the human spectrum.
(4) Volume change of blood flow
The human body belongs to a complex living body, the physiological phenomena of heart pulsation, blood circulation and the like can cause the periodic fluctuation of blood flow volume, the time-varying characteristic of the blood flow volume can cause the change of absorbance in the near infrared spectrum of the human body, and obviously influences the measurement result, which is mainly represented as the instability of the spectrum time domain.
(5) Too wide wavelength range of photoelectric sensor
The wavelength range of the photoelectric sensor which can be used for detecting the blood sugar wavelength is too wide, the spectral information of the LED with the specific wavelength cannot be accurately received, the wavelength range needs to be cut off by the optical filter to be reduced, and the accuracy is affected due to insufficient light passing rate after the optical filter is used
(6) Too low power and insufficient light transmission of LED
The power of LEDs with specific wavelengths which can be used for detecting blood sugar in the market is too small and is concentrated in 1-3mw, so that the passing rate of light irradiating the fingers is insufficient.
In summary, it can be seen that how to implement non-invasive blood glucose detection by using spectroscopic techniques is a technical problem that has yet to be solved.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the existing defects and provide a noninvasive blood glucose detection method based on a spectral sensor; the technology for detecting the blood sugar by the spectrum sensor in a non-invasive way is broken through, the improved near infrared spectrum transmission measurement technology is adopted, an original calibration mechanism is adopted, no material consumption is caused, the clinical verification data is accurate, the influence of the personal state and the environmental change of a human body is small, the error is less than +/-15%, and the method can be compared favorably with detection equipment with wounds.
In order to solve the technical problems, the invention provides the following technical scheme: a noninvasive blood glucose detection method based on a spectral sensor comprises the following steps: the method comprises the following steps: a spectrum sensor is designed at the fingertip position, and an LED is designed at the other side relative to the fingertip position;
step two: a tunable filter of a Fabry-Perot interferometer is adapted in the spectrum sensor, and the optical receiving range of the tunable filter is adjusted to reach the nm level;
step three: light rays emitted by a 1650nm LED penetrate through human tissues and are collected by a spectral sensor with the wavelength of 1350nm to 1650 nm;
step four: the light emitted by 1720nm LED is collected by 1550nm-1850nm spectrum sensor after passing through human tissue.
Preferably, the number of the 1650nm LEDs is four.
Preferably, the 1720nm LED is also four in number.
Preferably, the spectrum sensor is a single-point InGaAs PIN combined Fabry-Perot interferometer tunable filter.
Preferably, the optical signal received by the spectrum sensor is transmitted to the processor, and the algorithm is called to calculate the blood glucose level.
Preferably, the 1650nm LED and the 1350nm-1650nm spectrum sensor adopted in the third step can be suitable for the small thumb.
Preferably, the 1720nm LED and the 1550nm-1850nm spectrum sensor employed in the fourth step are applicable to the ring finger.
The invention has the beneficial effects that: the noninvasive blood glucose detection method based on the spectral sensor is a method for obtaining blood glucose concentration without damaging human tissues, has the characteristics of no pain, no infection, no consumable material and the like, and has very important practical significance for developing noninvasive blood glucose detection equipment:
1. the pain of blood collection is relieved, and the measurement times are increased, so that the blood sugar is more accurately controlled;
2. the method replaces the prior invasive detection technology using consumables, not only can reduce the cost, but also can reduce the pollution to the environment;
3. the noninvasive blood glucose is the result of multidisciplinary cross development, the development of a spectrum technology, a chemometric analysis technology, an information processing technology and a detection control technology is driven, and the research result can be popularized and applied to noninvasive detection of other trace chemical components in the body, so that the noninvasive blood glucose sensor contributes to strengthening daily health management of people and improving the quality of life.
4. The non-invasive blood sugar detection equipment in the market is integrated in one equipment, and the LED and the spectrum sensor with different wavelengths can be designed to work in the two equipment simultaneously, so that the problems of insufficient power of the LED and interference of the spectrum sensor are avoided.
Drawings
Fig. 1 is a blood vessel distribution diagram of the palm.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
At present, equipment for researching and developing noninvasive blood sugar based on near infrared spectroscopy on the market is designed based on a specific wavelength LED and a traditional photoelectric sensor, and due to the fact that the receiving wavelength range of the photoelectric sensor is wide, if optical data with high precision is required to be obtained, the wavelength needs to be cut off by an optical filter, but the optical signal is only 97% -98% passed through due to the influence of the processing precision of the optical filter, and therefore the precision of the optical signal is insufficient.
At present, the position of human tissue is detected by noninvasive blood glucose detection, most of the noninvasive blood glucose detection is concentrated on fingers, earlobes and arms, but because bones exist in the human tissue, near infrared light can be blocked, blood vessels in the earlobes are less distributed, and therefore blood glucose information is not easy to obtain.
Almost all non-invasive blood glucose detection LEDs on the market select wavelengths which are concentrated below 1450nm, and are easily interfered by water, so that data is inaccurate.
Because a plurality of wavelengths are needed to provide optical signals with blood glucose data at the same time, LEDs and photoelectric sensors are integrated in the same device in all non-invasive blood glucose detection devices at present, and a human body has fat, muscle and bones, so that when the optical signals are transmitted, the selective optical signals of the human body part cannot be integrated at the same point, and the data have large deviation.
Aiming at the problems, the invention provides a noninvasive blood glucose detection method based on a spectral sensor, which comprises the following steps: the method comprises the following steps: a spectrum sensor is designed at the fingertip position, and an LED is designed at the other side relative to the fingertip position;
step two: adapting a tunable filter within the spectral sensor and adjusting an optical receiving range of the tunable filter to a nm level;
step three: when the device is used for the little finger, a 1650nm LED and a 1350nm-1650nm spectrum sensor are adopted;
step four: for the ring finger, 1720nm LED and 1550nm-1850nm spectrum sensor are used.
The 1650nm LEDs are four in number.
The 1720nm LED is also adopted, and the number of the LED is four.
The spectrum sensor is a tunable filter of a single-point InGaAs PIN combined Fabry-Perot interferometer.
And sending the optical signal received by the spectral sensor to a processor, and calling an algorithm to calculate the blood sugar value.
A spectral sensor was used in this scheme: the biggest difference from the photoelectric sensor is that no optical filter is used independently, an MEMS-FPI (Fabry-Perot interferometer) tunable filter is arranged in the packaging of the size of a fingertip in the spectrum sensor, the filter can adjust the receiving range of transmission wavelength according to the difference of voltage, meanwhile, a single-point InGaAs PIN photodiode is also arranged in the packaging of the spectrum sensor, the optical receiving range can be accurately adjusted through the voltage, the maximum wavelength can be 1nm, and the accuracy and the repeatability of spectrum information after the LED transmits the finger are improved.
4 wavelength-specific LEDs were used: because the power of a single LED is too small, the power is enhanced by adding the LED with the specific wavelength, so that the spectral information after the finger is transmitted is high.
Two devices are used simultaneously: in all the devices in the market, LEDs and photoelectric sensors are integrated in one device, so that the structural positions of the LEDs with different wavelengths are shifted, the light transmission positions are not uniform, and the deviation of spectral information is caused.
Near infrared light with specific wavelength is adopted to transmit the finger, transmitted light with different light intensities is obtained after the near infrared light is absorbed by tissues at the front end of the finger tip, and the transmitted light is converted into an electric signal through a spectrum sensor, so that pulse waves carrying blood sugar signals can be obtained. According to the invention, the 1650nm and 1720nm near-infrared LED light sources are selected, because 1650nm and 1720nm are sensitive wavelengths of blood sugar, compared with other wavelengths, the blood sugar has a strong absorption peak at the position, and meanwhile, the absorption peak of water at 1440 nm-1460 nm is avoided, so that the influence of water in blood on the measurement result is well reduced.
The near-infrared spectroscopy is mainly based on characteristic absorption of glucose molecules in a near-infrared region, and a regression model between the blood glucose concentration and a near-infrared spectrum is established by means of modern chemometrics, so that noninvasive detection of the blood glucose concentration is realized.
The near infrared spectroscopy realizes a non-invasive blood glucose measurement system by using an LED light source with specific wavelength and a spectrum sensor according to a photoelectric transmission principle. Firstly, the finger tip is irradiated by an LED (with the wavelength of 1650nm and 1720nm) in the finger chamber of the device, then a spectral sensor (with the wavelength of 1350nm-1650nm, the wavelength of 1550nm-1850nm and the wavelength of 1750nm-2150nm) is used for receiving a transmitted optical signal after the finger is transmitted, and the signal is filtered and amplified in a targeted manner by a signal processing module, so that the signal-to-noise ratio and the peak value of a signal waveform are improved. And then, the signal is lifted and amplitude limited, so that the signal conforms to the acquisition range of the ARM. Then, an ADC acquisition function of the ARM is used for converting the analog signals from the filter circuit into digital signals for subsequent use, and the ARM processes the acquired digital signals through a series of algorithm software to finally obtain processed waveform peak data. After data are transmitted to APP in electronic equipment (such as a mobile phone, a tablet personal computer and a notebook computer) with a Bluetooth function through Bluetooth, a blood glucose meter with a medical instrument license is utilized to test a blood glucose value of a user, the blood glucose value is input into the APP to serve as a reference value for modeling, and the reference value is matched with waveform data and provided for MATLAB together to establish a support vector machine model. Executing the prediction function of the model in MATLAB by using the acquired peak data when the predicted blood sugar mode is used each time, calculating to obtain a predicted blood sugar value,
the system hardware design scheme of the invention mainly comprises: designing and manufacturing an LED with a finger bin and a spectrum sensor; the design and manufacture of a spectrum sensor signal amplifying and filtering circuit, a power supply circuit and an ARM-based data acquisition, storage, processing and display circuit.
A finger bin module: the LED lamp is controlled to be on or off through the IO port of the single chip microcomputer, the constant current power supply is used for supplying power to the LED lamp, the brightness of the LED lamp is stable, and when specific infrared light penetrates through finger fingertips, the spectrum sensor receives light signals and converts the light signals into current signals.
The signal processing module: the method comprises the steps of firstly converting weak current signals into voltage signals through an operational amplifier and a resistor, then carrying out band-pass filtering, wherein low frequency filtering is used for reducing ambient light interference, high frequency filtering is used for reducing clutter interference, the voltage signals are boosted through an amplifier, and because negative voltage signals exist and a single chip AD cannot convert the negative voltage signals, the amplification factor needs to be controlled, so that the output voltage signals are between 0 and 3.3V.
A CPU processing module: convert the voltage signal of front end input through the ADC module, then communicate the signal to APP through a plurality of bluetooth equipment, obtain blood glucose data after the APP will be handled with cloud computing calling algorithm, return to APP again and show blood glucose value and data waveform.
As shown in fig. 1, blood vessels of the palm are distributed, and it can be known from observation of the graph that finger tips are distributed with rich capillary vessel networks, which can effectively reflect blood sugar content in the human body, and the position has obvious blood volume change characteristics; the muscle and skeletal tissue of the finger is relatively thin, so background interference information has relatively little influence; in addition, the front end of the finger is convenient to measure, and the examinee has no psychological burden, so that a stable high signal-to-noise ratio spectrum signal can be obtained; the invention finally selects the fingertips of the ring finger and the fingertips of the little finger as the measuring parts.
In order to extract effective signals from a spectrum containing strong background interference, it is an effective scheme to adopt near background subtraction, which can effectively eliminate interference such as background variation. However, the human body is an extremely complicated time-varying living body, and it is difficult to find a standard plate whose physicochemical properties are similar to those of human tissue in time and space to eliminate the influence caused by the change of tissue background. However, if the spectrum of the human body itself at a certain time is used as a standard plate, background subtraction will be effectively realized.
The blood flow volume in the human tissue will change periodically with the heart beat, with different blood flow volumes corresponding to different blood thicknesses. Within one or a few cycles (in the order of seconds) of the change of the blood flow volume, the physicochemical properties and blood component content information of the background tissues such as skin, muscle and the like are not substantially changed. Therefore, with the blood flow volume spectral subtraction method: the two spectra with different blood volume contents acquired in a very short time are subjected to differential processing, and the background interference of tissues can be effectively deducted.
At two times T1 and T2 with a time interval Δ T (in the order of seconds), the blood thickness changes from L1 to L2 at the same measurement position by an amount of Δ L in volume. When a beam of near infrared light irradiates the measurement site, the absorbance characteristics corresponding to the times t1 and t2 can be calculated according to the Lambert-Beer law:
A1＝lg〔I0/I(t1)〕＝lg(I0/I1)
A2＝lg〔I0/I(t2)〕＝lg(I0/I2)
because the delta T is extremely short, the tissue characteristics of the skin, muscle and the like of the measurement part and the content information of blood components are basically not changed, and the change is only the optical path of blood, therefore, the spectrums measured at the two moments can be mutually referred to, and the absorbance spectrum of the blood corresponding to the change amount of the optical path is obtained:
ΔA＝lg〔I2/I1〕＝lg(I0/I1)-lg(I0/I2)＝A1-A2
the above process is equivalent to differentiating the human body spectra measured at two moments at an interval of Δ T, i.e. obtaining a near-infrared volume difference spectrum. The analysis formula shows that when the blood composition is analyzed by the blood flow volume spectrum subtraction method, the blood spectrum information with the volume difference delta L can be obtained only by directly calculating the logarithm of the ratio of the light signals with different intensities measured at the time t1 and the time t 2.
After the spectrum subtraction method is used for processing, the volume difference spectrum does not carry human tissue background information any more, and meanwhile, interference factors such as individual difference, different contact pressures and the like which are related to the tissue background and are easy to change in the measurement process are effectively eliminated. The effective signal content related to blood components in the volume difference spectrum is greatly improved, and the near infrared spectrum noninvasive detection blood glucose analysis precision is favorably ensured.
The algorithm used by the invention usually contains some errors, such as stray light, human tissue influence and the like, according to the spectral information measured by the spectral sensor, so that the measured data has certain noise and the calculation precision of blood sugar is influenced, therefore, the collected original spectral data needs to be preprocessed before modeling, the error is reduced, and effective information in the data is extracted, so that the calculation precision of a blood sugar model is improved. Modeling the multi-modal spectral data using MATLAB software according to support vector machine theory.
Two groups of near infrared spectrum data with different wavelengths are used as independent variable matrixes of the model to be input, blood glucose values adopted by the household glucometer are used as dependent variables of the model, and a sample training set and a test set are divided. 88 sets of data were measured as modeling data by testing diabetic patients in the early stage. Sorting the screened spectral data according to the blood sugar values measured by a household blood sugar meter, and dividing the training set and the test set according to the ratio of 3: 1 to ensure that the selected samples cover all the blood sugar values, namely 66 groups of sample data are used as the training set, and 22 groups of sample data are used as the test set. The sample data is then normalized. The spectral data measured by two groups of different wavelengths are used as independent variables, the blood sugar values are used as dependent variables, normalization is respectively carried out, probability distribution is in the same range, the influence on a modeling result due to too large data distribution range and inconsistent order of magnitude is reduced, and training efficiency is improved. The optimal kernel function, penalty factor coefficient (c) and parameter coefficient (g) of the kernel function are required to be selected for SVM parameter setting, and due to the difference of models and data, the optimal parameters cannot be obtained before modeling, so that the optimal values of c and g are obtained by adopting a cross validation method in the modeling process for training and predicting. The experimental training set has 66 groups of data, and the spectral data and the blood glucose truth value of the 66 groups of samples are used for training to obtain a model between the spectral data and the blood glucose truth value. The 22 groups of data in the test set are substituted into the model for calculation, and the calculated values of the blood sugar of the 22 groups of data can be obtained.
For the established correction model, the model is evaluated by adopting four indexes, namely a correlation coefficient R, a correction set root mean square error (R MSEC), a test set root mean square error (R MSEP) and a relative error E, wherein the correlation coefficient reflects the similarity degree of a predicted value and a theoretical value, and the root mean square error and the relative error reflect the model precision.
When the two specific wavelength spectrum data are used for modeling, the correlation coefficient of a training set is 97.29%, the root mean square error is 0.3558 mmol/L, the correlation coefficient of a testing set is 96.3%, the root mean square error is 0.3804 mmol/L, the maximum relative error is 13.68%, and the average relative error is 0.069%.
The above embodiments are preferred embodiments of the present invention, and those skilled in the art can make variations and modifications to the above embodiments, therefore, the present invention is not limited to the above embodiments, and any obvious improvements, substitutions or modifications made by those skilled in the art based on the present invention are within the protection scope of the present invention.
Claims (7)
1. A noninvasive blood glucose detection method based on a spectral sensor is characterized by comprising the following steps: the method comprises the following steps: the method comprises the following steps: a spectrum sensor is designed at the fingertip position, and an LED is designed at the other side relative to the fingertip position;
step two: a tunable filter of a Fabry-Perot interferometer is adapted in the spectrum sensor, and the optical receiving range of the tunable filter is adjusted to reach the nm level;
step three: light rays emitted by a 1650nm LED penetrate through human tissues and are collected by a spectral sensor with the wavelength of 1350nm to 1650 nm;
step four: the light emitted by 1720nm LED is collected by 1550nm-1850nm spectrum sensor after passing through human tissue.
2. The method of noninvasive blood glucose sensing based on spectral sensor of claim 1, characterized in that: the 1650nm LEDs are four in number.
3. The method of noninvasive blood glucose sensing based on spectral sensor of claim 1, characterized in that: the 1720nm LED is also adopted, and the number of the LED is four.
4. The method of noninvasive blood glucose sensing based on spectral sensor of claim 1, characterized in that: the spectrum sensor is a tunable filter of a single-point InGaAs PIN combined Fabry-Perot interferometer.
5. The method of noninvasive blood glucose sensing based on spectral sensor of claim 1, characterized in that: and sending the optical signal received by the spectral sensor to a processor, and calling an algorithm to calculate the blood sugar value.
6. The method of noninvasive blood glucose sensing based on spectral sensor of claim 1, characterized in that: the 1650nm LED and the 1350nm-1650nm spectrum sensor adopted in the third step can be suitable for the small thumb.
7. The method of noninvasive blood glucose sensing based on spectral sensor of claim 1, characterized in that: the 1720nm LED and the 1550nm-1850nm spectrum sensor employed in the fourth step may be applied to a ring finger.
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| CN114569122A (en) * | 2022-02-12 | 2022-06-03 | 徐州蓝色电子科技有限公司 | Noninvasive blood glucose meter |
| CN116242804B (en) * | 2023-05-09 | 2023-08-15 | 四川威斯派克科技有限公司 | Portable near infrared spectrometer |
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| WO2023280017A1 (en) | 2023-01-12 |
| CN113261954B (en) | 2023-03-07 |
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