WO2010073908A1 - Biological information signal processing apparatus, biological information signal processing method and biological information measuring apparatus - Google Patents

Biological information signal processing apparatus, biological information signal processing method and biological information measuring apparatus Download PDF

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WO2010073908A1
WO2010073908A1 PCT/JP2009/070616 JP2009070616W WO2010073908A1 WO 2010073908 A1 WO2010073908 A1 WO 2010073908A1 JP 2009070616 W JP2009070616 W JP 2009070616W WO 2010073908 A1 WO2010073908 A1 WO 2010073908A1
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signal
component
biological information
noise component
noise
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PCT/JP2009/070616
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French (fr)
Japanese (ja)
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謙治 蛤
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コニカミノルタセンシング株式会社
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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/145Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1455Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
    • A61B5/14551Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters for measuring blood gases
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02416Detecting, measuring or recording pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infra-red radiation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021Measuring pressure in heart or blood vessels
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02438Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient

Abstract

A biological information signal processing apparatus comprises: a signal generating unit that generates, from first and second time series signals, a signal including a first signal component, based on the first time series signal including both the first signal component having a periodicity and a first noise component, based on a second time series signal including both a second signal component having a predetermined relationship with the first signal component and a second noise component having a predetermined relationship with the first noise component, and based on the predetermined relationship between the first and second noise components; and an estimating unit that uses the periodicity of the generated signal within a first predetermined time range to estimate the predetermined relationship between the first and second noise components within the first predetermined time range.

Description

Biometric information signal processing apparatus, the biometric information signal processing method and the biological information measuring device

The present invention, when the biological information signal processing apparatus for removing a noise component from the time series signal, related to biometric information signal processing method and the biological information measuring device.

Conventionally, techniques to signal processing for removing a noise component from the time series data a noise component is superimposed have been applied to various signal processing device. In particular, when time-series data includes information related to biometric information, said signal processing device is called a biological information measurement device. The biological information measuring device is a device for detecting biological information in a noninvasive from the living tissue, specifically measuring device and for measuring the pulse waveform and pulse rate of a living body, called a photoelectric plethysmograph in a pulse oximeter a measuring apparatus that measures the arterial blood oxygen saturation called. The principle of these measuring devices is obtained by receiving light transmitted through or reflected by the living body tissue, based on the signal component corresponding to the variation due to the pulsation of a living tissue, the living body, such as the concentration of light absorbing materials in blood and requests the information.

Generally obtained by receiving light transmitted through or reflected from the living tissue, a variety of noise components in the data required for the detection of biological information is superimposed. Figure 1 is obtained by receiving light transmitted through or reflected by the living body tissue, is a diagram showing an example of the data required to detect the biological information. The horizontal axis of FIG. 1 is a time, the vertical axis represents the intensity of the transmitted or reflected light to body tissue. Noise component, mainly when using biological information measurement device, the living body is by performing body motion such as moving the body. In the example shown in FIG. 1, initially, the noise component caused by body motion or the like is not superimposed on the signal component, the noise component is superimposed on the signal component from a predetermined time. It causes an error in the calculation of the biometric information in this way noise component is superimposed on the signal component. Therefore, it is desired to remove noise components.

When a plurality of lights having different wavelengths is irradiated respectively to the living body to each other, based on the DC-AC ratio in intensity of the light transmitted through or reflected from the living tissue, a technique for calculating biological information it has been proposed. In particular, if the noise component to the signal component is superimposed, the DC-AC ratio for each wavelength is represented by the signal and noise components. As a technique for calculating the thus expressed noise components include method using a cross-correlation between the signal and noise components. For example, when the removal of the noise component, Patent Document 1, that the DC-AC ratio for each wavelength is determined, the above predetermined frequency is constant ratio due to the wavelength of the noise component over the entire frequency range with include noise components under the assumption, the ratio by the wavelength of the noise component is calculated, the noise component removing waveform is calculated by using a cross-correlation between the signal and noise components. Further, for example, in Patent Document 2, under the condition that the correlation is low between the signal and noise components, determining the ratio by the wavelength of the ratio and the noise component due to the wavelength of the signal component, such as the power of the signal components is maximized noise components are removed by.

Japanese Patent No. 3627214 Publication US Pat. No. 7254433

Incidentally, the technique of Patent Document 1 and Patent Document 2, for processing a relatively large amount, the power consumption increases. This is especially the portable biological information measurement device for typically because they are driven by the battery, the at serious problem in terms of power consumption.

In addition, the biological information measuring device, operating room, not only the ward, such as intensive care, respiratory failure patients, home oxygen therapy daily life data collection and management of respiratory conditions in patients, screening of sleep apnea syndrome, It is being used up to the application to wear sports field and the like at all times only mountain climbing, and the like. Also in view of such circumstances, the biological information measuring device, compact, lightweight, and the like also demanded power consumption and low cost.

Not only the biological information measuring apparatus taken as an example, and in general, when also in the signal processing device for performing signal processing for removing a noise component from the time series data, the signal processing for removing noise components serious problems in terms of power consumption it can be said.

The present invention is an invention made in view of the above circumstances, the object, the signal processing amount was reduced further suppressed biological information signal processing apparatus power consumption, the biometric information signal processing method and the biological information measuring device it is to provide.

According to one aspect of the present invention, a first time series signal including a first signal component and a first noise component having periodicity, a second signal component and the having the first signal component and a predetermined relationship a second time series signal including the second noise component having a first noise component in a predetermined relationship, based on said predetermined relationship between said first noise component and the second noise component, the first when generates a signal including the first signal component sequence signal from said second time series signal, using the periodicity of the generated signal at a predetermined time range, the first noise in the predetermined time range estimating the predetermined relationship between the the component second noise component. Thus, the amount of signal processing required for the noise component removal can be reduced compared with the conventional art.

Obtained by receiving light transmitted through or reflected from the living body tissue, it is a diagram showing an example of the data required to detect the biological information. Is a block diagram showing the configuration of a biological information measuring apparatus according to an embodiment of the present invention. It is a flowchart for calculating the initial value of the biological information measuring device. Is a flow chart for calculating arterial oxygen saturation in the biological information measuring device. Is a flow chart for calculating a pulse rate in the biological information measuring device. It is a diagram showing the R-kv * IR waveform by the measured data shown in FIG.

Described principles and embodiments of the present invention. For convenience, in the signal processing device, in particular pick up the biological information measuring device as an example, not the biological information measuring device but also the present invention to a signal processing apparatus for removing a noise component can be applied.

(The principles of the present invention)
First, a description will be given of the principle of the present invention. Upon this will be described, on the basis of an example, one another wavelength IR, in each measurement data obtained by irradiated respectively a plurality of lights having different R to the organism to each received transmitted or reflected each light to the living body It will be described for measuring the blood oxygen saturation as a biometric information of a living body.

By Lambert-Beer's law, the ratio between the AC component and the DC component of the intensity of light of a certain wavelength transmitted through or reflected by the living tissue is approximated to be equal to the change in the absorbance of the biological tissue at that wavelength.

By using the approximation by law the Lambert-Beer, for infrared wavelength IR, infrared orthogonal ratio IR_signal which is the ratio of the DC component and an AC component of the intensity of the transmitted light or reflected light, the biological for the wavelength IR it can be regarded as equal to the change in the absorbance of the tissue. Similarly, for the red wavelength R, red orthogonal ratio R_signal which is the ratio of the DC component and an AC component of the intensity of the transmitted light or reflected light, can be regarded as equal to the absorbance change in the biological tissue for the wavelength R it can.

The infrared orthogonal ratio IR_signal is expressed by the equation (1).

Figure JPOXMLDOC01-appb-I000001

Here, s is the signal component of the change in absorbance, n is the noise component superimposed on the signal component.

Then, the red quadrature ratio R_signal is expressed by equation (2).

Figure JPOXMLDOC01-appb-I000002

Here, k_a is the ratio of the absorbance change in the signal component s and the absorbance of the variation of the signal component of the wavelength R at a wavelength of IR, K_v the noise component n and wavelengths superimposed on the signal component of the wavelength IR which is the ratio of the noise component superimposed on the signal component of the R.

The k_a and blood oxygen saturation of the formula (2), one-to-one are known to correspond to, by determining the k_a, it is possible to determine the blood oxygen saturation.

Further, (1) (3) is obtained by multiplying the k_v the equation, by subtracting the expression (3) from equation (2), the equation (4) below is obtained.

Figure JPOXMLDOC01-appb-I000003
Figure JPOXMLDOC01-appb-I000004

Similarly, by multiplying the k_a in (1) above (5) is obtained by subtracting the expression (2) to (5), (6) below is obtained.

Figure JPOXMLDOC01-appb-I000005
Figure JPOXMLDOC01-appb-I000006

Here, the signal component s and a noise component n uses the relationship that it is independent, i.e. the following relational expression (7), and, within a short time, under the condition that k_a and k_v constant, above ( 4) by correlating equation (6), equation (8) is obtained.

Figure JPOXMLDOC01-appb-I000007
Figure JPOXMLDOC01-appb-I000008

Here, sigma is the sum of terms a short time as are k_a and k_v constant. i is, the time-series data IR_signal of the amount of change in the intensity of the light, is a data number of R_signal, the measurement time interval of data Δt, as the measurement start time t0, and time t in the relationship of t = Δt * i + t0 It is linked. (8) because it contains two unknowns that k_v and k_a the expression can not be obtained and k_a and k_v only (8).

Here, (4) the right side of the equation to determine the k_v focuses on it is nearly periodic, seek k_v as with (4) of the left side periodicity.

By substituting this way the k_v obtained in (8), determine the k_a when satisfying the expression (8). Based on this k_a, it is possible to determine the blood oxygen saturation with reduced noise component. Then, in the above calculation method, for example, since the amount of computation is not necessary to use a relatively large Fourier transform and the like, it is possible to further reduce the amount of arithmetic processing.

(Embodiment)
It will be described below based on an embodiment of the present invention with reference to the drawings. Incidentally, the components denoted by the same reference numerals in each figure, show that those having the same configuration and function, as appropriate, and description thereof is omitted.

First, the configuration of an embodiment of the present invention. Figure 2 is a block diagram showing the configuration of a biological information measuring apparatus according to the embodiment. Note that the solid line in the figure represents a flow between the blocks of the electrical signal components corresponding to the time-series data of the pulse wave which will be described later.

The biological information measurement device 30, for example, to measure the biological information obtained by removing the influence of noise components due to body movement or the like, using the time-series data of the intensity of the transmitted or reflected light the living body measured (subject) Te effect to the removal of the living body information measurement values ​​by body motion or the like of the measurement object, based on the time series data from which the noise components have been removed, for example, a measurement device that measures biological information of a blood oxygen saturation and the like.

More specifically, the biological information measuring device main body of the biological information measuring device 30 is obtained by receiving each respective light transmitted through or reflected by the living body by irradiating each a plurality of lights having different wavelengths to the living body to each other measures biological information of a subject based on the measurement data. Biological information measuring device body, the data including a signal component having periodicity is generated based on the measurement data, and extracts the noise component is a component excluding the signal component by using a periodic, noise component from the data removed, and a measurement unit 10 for measuring biological information of the living body on the basis of the data obtained by removing noise components.

That is, the biological information measuring device 30 includes a data acquisition unit 1 to acquire the measurement data by receiving each respective light transmitted through or reflected by the living body by irradiating each a plurality of lights having different wavelengths to a living body to each other, the data based on the measurement data obtained by the obtaining unit 1 and a biological information measuring apparatus main body for measuring biological information of the living body.

In such a configuration of the biological information measuring apparatus body and the biological information measurement device 30, since the extracted noise component by using the periodicity, the arithmetic processing amount necessary for the noise component removing be reduced over the prior art it can. Therefore, by reducing the amount of arithmetic processing, the power consumption due to the operation of the noise component is also becomes possible to suppress.

Further, in the biological information measuring device 30 described above, the measurement part 10, in order to extract a noise component from the data, for a given two wavelengths of the plurality of wavelengths, the ratio of the DC component and the AC component of the measured data seeking a certain DC-AC ratio, the relational expression obtained by subtracting the DC-AC ratio for the remaining one wavelength from the DC-AC ratio for one wavelength multiplied by a variable containing information about the noise components to have a periodicity decision variables to.

According to such a configuration, the variable determined from the above equation, since the extraction of the noise component, the amount of computation involved in the extraction of the noise component can be reduced prior art more effectively. Therefore, by reducing the amount of arithmetic processing, the power consumption due to the operation of the noise component is also becomes possible to effectively suppress.

Hereinafter, more detailed, there will be described a configuration of the biological information measurement device 30. The biological information measuring device 30 includes, for example, as shown in FIG. 2, a data acquisition unit 1, a measuring unit 10, an output unit 20.

Data acquisition unit 1 is required for measuring biological information in the measurement unit 10 is measured at predetermined time intervals, a device for acquiring the time-series data relating to the pulsation of a living body. Here, as a method of detecting the pulsations, various methods can be employed, it can be suitably employed for the example methods utilizing light absorption characteristics of hemoglobin biological tissue. As is well known, oxygen is transported to each cell of a living body by hemoglobin, hemoglobin combines with oxygen in the lungs becomes oxyhemoglobin and oxygen in living cells is consumed returns to hemoglobin. Oxygen saturation refers to the percentage of oxygenated hemoglobin in the blood. Absorbance of absorbance and oxyhemoglobin these hemoglobin has a wavelength dependence, for example, hemoglobin, absorbs more light than oxygenated hemoglobin relative to the red light of the wavelength R in the red region, the wavelength in the infrared region less absorption of light than oxygenated hemoglobin for the IR of infrared light. This method is to obtain such a hemoglobin and red light and infrared light in blood oxygen saturation and pulse rate, etc. For example by utilizing a difference in light absorption characteristic with respect to the biometric information of the oxygenated hemoglobin. Data acquisition unit 1 is, for example, as shown in FIG. 2, the red light (hereinafter, R) light-emitting element for irradiating a predetermined biological tissue (R), and, to be measured is irradiated by the light emitting element (R) a sensor (R) 2 having a light receiving element (R) for receiving light transmitted through or reflected from the living body tissue, the infrared light (hereinafter, IR) light-emitting element for irradiating a predetermined biological tissue (IR), and, in the reflection-type or transmission-type sensor and a sensor (IR) portion 3 provided with a light receiving element (IR) for receiving the light transmitted or reflected by the irradiated body tissue to be measured by the light emitting device (IR) is there. Data acquisition unit 1 having such a configuration is set to a predetermined biological tissue, the light receiving element (R, IR) to monitor the amount of light received respectively by each being light-receiving optical to electrical signal according to the light intensity each acquires the relating pulse wave each time-series data by converting each photoelectric. The data acquisition unit 1, the addition, a pressure sensor or the like, by detecting the pulse pressure by vascular pulsation directly can be an apparatus for acquiring a pulse wave data as the time-sequence data. Data acquisition unit 1 is connected to the measuring unit 10, and outputs the respective time-series data to the AC / DC (R) unit 11 which will be described later.

The output unit 20 is connected to the measuring unit 10 is a device for outputting a measurement value or the like of the biological information about the living body is measured by the measuring unit 10. The output unit 20 is, for example, a liquid crystal display device (LCD; Liquid Crystal Display), 7 segment LED, organic photoluminescence display, CRT (Cathode Ray Tube) display or the like display device and a plasma display device, a microphone and a speaker and a sound output device and the like, a printing apparatus such as a printer. For example, various measurement information of the data analysis results of pulse wave data, optical lighting (points off, including flashing), characters, images are output in any form to the appropriate voice or printing.

The output unit 20 includes, for example, as shown in FIG. 2, an SpO2 output section 22, and the pulse rate output unit 23, and a reliability output unit 24. SpO2 output unit 22 is a device for outputting the blood oxygen saturation calculated by the SvO2 estimating SpO2 determination unit 19 described later. Pulse rate output unit 23 is a device for outputting the pulse rate calculated by pulse rate calculator 20 which will be described later. Then, the reliability output unit 24 is a device for outputting a reliability calculated by the reliability calculation unit 21 described later.

The measurement unit 10 is, for example, as shown in FIG. 2, a functional, AC / DC (R) conversion unit 11, AC / DC (IR) conversion unit 12, BPF (R) unit 13, BPF (IR) part 14, ΣR_signal * IR_signal calculator 15 includes a Shigumaaru_signal 2 calculation section 16, ΣIR_signal 2 calculator 17, an initial value calculating section 18, SvO2 estimation SpO2 determination unit 19, the pulse rate calculating section 20 and the reliability calculation section 21, and , according to a pre-stored control program, and controls each in accordance with the data acquisition unit 1 and the output unit 20 to the function.

Measurement unit 10, to the time-series data of the pulse wave acquired by the data acquisition unit 1, after the predetermined preprocessing to calculate the initial value required for the operation of removal and the biological information of the noise component, using the initial value, performs noise component removing process for removing a noise component contained in the time-series data of the pulse wave, based on the time-series data of the pulse wave after the noise component removal, and measures biological information such as, the is a device that outputs a measurement value of the biological information to the output unit 20. Measurement unit 10, for example, ROM (Read Only Memory) for storing the respective computing programs for performing the processing to be described later, RAM for temporarily storing data to function as a so-called working memory (Random Access Memory) and the operational central processing unit for executing a processing program or the like read from the ROM (CPU) and its peripheral circuits.

AC / DC (R) converter 11, with respect to time-series data of the red light (R) input from the sensor (R) 2 of the data acquisition unit 1, the data which is the ratio of the DC component and an AC component is a circuit that converts. In the present embodiment, AC / DC (R) converter 11, as the pre-processing, the dark treatment for removing components due to the dark current.

BPF (R) 13, from AC / DC (R) conversion unit 11 is inputted time series data of the red light (R), the red light by removing a noise component (R) to obtain the frequency components of the it is a band-pass filter (BPF). BPF (R) unit 13 outputs the R_signal a time series data after filtering ΣR_signal * IR_signal calculator 15, the Shigumaaru_signal 2 calculator 16 and SvO2 estimation SpO2 determination unit 19.

AC / DC (IR) converter 12 is the ratio of the relative time-series data of infrared light (IR) input from the sensor (IR) unit 3 data acquisition unit 1, a DC component and an AC component data it is a circuit for converting to. In the present embodiment, AC / DC (IR) converter 12, as the pre-processing, the dark treatment for removing components due to the dark current.

BPF (IR) unit 14, AC / DC (IR) time-series data of infrared light (IR) is inputted from the conversion unit 12 to obtain the frequency components of the infrared light (IR) by removing the noise component it is a band-pass filter for. BPF (IR) unit 14 outputs the IR_signal a time series data after filtering ΣR_signal * IR_signal calculator 15, the ShigumaIR_signal 2 calculator 17 and SvO2 estimation SpO2 determination unit 19.

ΣR_signal * IR_signal calculating unit 15, the time-series data of the red light input from the BPF (R) unit 13 (R), and time-series data of the infrared light that is input from the BPF (IR) portion 14 (IR) It was used to calculate the cross-correlation ΣR_signal * IR_signal, a circuit for outputting the calculated correlation ΣR_signal * IR_signal the initial value calculation section 18. Shigumaaru_signal the second calculating unit 16, using the time-series data of BPF red light input from the (R) unit 13 (R), to calculate the autocorrelation Shigumaaru_signal 2, autocorrelation Shigumaaru_signal 2 Initial value calculating section 18 for calculating the is a circuit to output to. Shigumaaru_signal the second calculating unit 16, using the time-series data of BPF red light input from the (R) unit 13 (R), to calculate the autocorrelation Shigumaaru_signal 2, autocorrelation Shigumaaru_signal 2 Initial value calculating section 18 for calculating the is a circuit to output to. ShigumaIR_signal 2 calculating unit 17, using the time-series data of the BPF infrared light input from the (IR) portion 14 (IR), to calculate the autocorrelation ShigumaIR_signal 2, an initial value calculating section autocorrelation ShigumaIR_signal 2 the calculated 18 is a circuit to output to. The initial value calculation section 18 is a circuit for calculating the initial value, more specifically, ΣR_signal * IR_signal mutual inputted correlation from the calculation unit 15 ΣR_signal * IR_signal, autocorrelation Shigumaaru_signal inputted from Shigumaaru_signal 2 calculator 16 2, and, by using the autocorrelation ShigumaIR_signal 2 inputted from ShigumaIR_signal 2 calculator 17 calculates the initial value, and outputs the calculated initial value to the SvO2 estimating SpO2 determination unit 19.

SvO2 estimation SpO2 determination unit 19, time-series data including a signal component having periodicity to remove the noise component superimposed on the signal component with a periodicity, on the basis of the time series data obtained by removing noise components, arterial a circuit for calculating the blood oxygen saturation. SvO2 estimation SpO2 determination unit 19 corresponds to the signal generating unit and the estimation unit disclosed in the means for solving the problems. SvO2 estimation SpO2 determination unit 19 determining unit 19, more specifically, time series data R_signal input from BPF (R) unit 13, and from the time series data IR_signal input from BPF (IR) unit 14, an initial based on the initial value calculated by the value calculating section 18, a circuit for calculating the blood oxygen saturation in the artery, to calculate the blood oxygen saturation in the vein based on the noise component if necessary, was calculated blood outputting a medium oxygen saturation to SpO2 output unit 22. Pulse rate calculating section 20, based on the time series data obtained by removing noise components in SvO2 estimating SpO2 determination unit 19 calculates the pulse rate, a circuit for outputting the calculated number of pulse to pulse rate output unit 23. Reliability calculation section 21, for measuring biological information, a circuit for calculating the reliability indicating the degree of error, and outputs the calculated reliability to the reliability output unit 24.

Incidentally, the biological information measuring device 30 optionally may further include an external storage unit of an unillustrated. The external storage unit, for example, a memory card, a flexible disk, CD-ROM (Compact Disc Read Only Memory), CD-R (Compact Disc Recordable), DVD-R (Digital Versatile Disc Recordable) and Blu-ray disc (Blue-ray Disc ) is a device which performs read and / or write data to and from the storage medium such as, for example, a memory card interface, floppy disk drive, CD-ROM drive, CD-R drive, DVD-R drive and a Blu-ray disc drive and the like.

Here, the biological information measuring device 30, when the arithmetic processing program in the measuring unit 10 is not stored is installed from the recording medium recording these programs, the measurement unit 10 via the external storage unit it may be configured so that. Alternatively, the biological information measuring device 30 may be configured so that data, such as detected biometric information is recorded on the recording medium via the external storage unit.

Next, the operation of the present embodiment. Figure 3 is a flowchart for calculating the initial value of the biological information measuring apparatus according to the embodiment. Figure 4 is a flowchart for calculating the arterial blood oxygen saturation in the biological information measuring apparatus according to the embodiment. Figure 5 is a flow chart for calculating a pulse rate in the biological information measuring apparatus according to the embodiment.

The biological information measuring device 30, for example, executes the processing program by the boot. Execution of this processing program, each unit 11-21 of the measuring unit 10 is functionally configured. The biological information measurement device 30, by the following operation, on the basis of the time series data acquired by the data acquisition unit 1, for measuring the reduced e.g. biometric information such as the blood oxygen saturation noise components.

The 3 and the flowchart shown in FIG. 4 (steps S1 ~ S15) is composed of large and the initial value calculation flow of step S1 ~ S7 separately, the blood oxygen saturation detecting flow of step S8 ~ S15. Flow chart (steps S16 ~ S20) shown in FIG. 5 is a pulse rate detecting flow.

<Initial value calculation flow (S1 ~ S7)>
The initial value calculation flow, after pre-processing of data (step S1 ~ step S4), and calculates an initial value (step S5 ~ Step S7).

First, in step S1, the measurement part 10, from the data acquisition unit 1, the component of the sensor (R) 2 of the dark current R_dark, and, components IR_dark are input by the dark current of the sensor (IR) part 3 . Then, the measuring unit 10, from the data acquisition unit 1, a data time series relating to the intensity variation of the light in the wavelength IR and wavelength R transmitted through or reflected from the living tissue R_signal_and_dark (i) and IR_signal_and_dark (i) are inputted, respectively that. Here, i represents that from 1 to i-th time-series data in up to N, the corresponding i and time are as described in the principles of the invention. N is chosen the number of data required for calculation of the oxygen saturation, is used a value of e.g., 200 or the like. For convenience, hereinafter will be described by omitting the i of time-series data. Note that the data R_signal_and_dark to wavelength R, sensor (R) 2 of the dark current due to component R_dark is, the data IR_signal_and_dark to wavelength IR, component IR_dark are included respectively by the dark current of the sensor (IR) part 3 .

Next, in step S2, AC / DC (R) unit 11 performs dark treatment subtracting R_dark from R_signal_and_dark. Likewise, AC / DC (IR) unit 12 performs dark treatment subtracting IR_dark from IR_signal_and_dark. Next, in step S3, it converts each signal of each wavelength that is dark treatment to the ratio of the DC component and an AC component (AC component / DC component). More specifically, IR_dark component is removed from the IR_signal_and_dark, which is the ratio of the DC component and an AC component consisting of only the intensity of the light from the biological IR_signal is calculated. Similarly R_dark component is removed from the R_signal_and_dark, which is the ratio of the DC component and an AC component consisting of only the intensity of the light from the biological R_signal is calculated.

Next, in step S4, BPF (R) unit 13 filters the R_signal, performs processing for obtaining only the desired frequency components to remove unwanted frequency components. Similarly BPF (IR) unit 14 filters the IR_signal, performs processing for obtaining the desired frequency component signal components by removing unnecessary frequency components.

Next, in step S5, the data R_signal retrieved in step S4, with respect IR_signal, ΣR_signal * IR_signal calculator 15, ΣR_signal 2 calculator 16, ΣIR_signal 2 calculating unit 17, the cross-correlation ΣR_signal * IR_signal, for the wavelength R calculating autocorrelation Shigumaaru_signal 2 and autocorrelation ShigumaIR_signal 2 for the wavelength IR respectively. As described in the principle of the invention described above, a sum Σ is taken from 1 for i to N, at short time intervals, K_v and k_a the holds assumption that constant.

Next, in step S6, the initial value calculation section 18, which is the initial value of k_v k_v_0, substituting the appropriate value, such as K_v previously obtained.

Next, in step S7, ΣR_signal * IR_signal determined in step S5 and step S6, using ΣR_signal 2, ΣIR_signal 2 and K_v_0, the initial value calculation section 18 is required in blood oxygen saturation detection flow, k_a calculates the initial values ​​k_a_0 and k_ns_0 is the initial value of k_ns respectively.

k_ns is an index for determining whether to extract a noise component is expressed by a ratio or the like between the intensity of the intensity of the noise component and the signal component, for example, is expressed by the equation (9).

Figure JPOXMLDOC01-appb-I000009

Here, the value relating to the intensity of n_square a signal component which is a value related to the intensity of the noise component s_square is given by substituting k_v_0 the equation (8) by different equations depending on whether the equality.

By substituting k_v_0 the equation (8), when the equality (i.e. the left side equals zero) the value of such k_a determined, the value of the k_a is a K_a_0, the following equation ( k_ns_0 is calculated using 10) and equation (11) and (9).

Figure JPOXMLDOC01-appb-I000010
Figure JPOXMLDOC01-appb-I000011

On the other hand, by substituting k_v_0 the equation (8), the equality does not hold (i.e. the left side is not zero) if such k_a is not obtained, the appropriate k_a including previous k_a the K_a_0, the following k_ns_0 is calculated using equations (12) and (13) equation (9). Further, assuming as the difference in oxygen saturation of arterial blood and venous blood for example 10%, the value may be a k_a_0 obtained by subtracting the value corresponding thereto from K_v_0.

Figure JPOXMLDOC01-appb-I000012
Figure JPOXMLDOC01-appb-I000013

The initial value calculating section 18, the K_a_0, is previously stored in a memory or the like (not shown) (step S7). The initial value calculation section 18, ΣR_signal * IR_signal, ΣR_signal 2, ΣIR_signal 2, k_v_0, is pre-stored in such a memory k_a_0 and K_ns_0 (not shown).

<Blood oxygen saturation detected flow (S8 ~ S15)>
After the initial value calculation is completed by the above steps, blood oxygen saturation detection flow is performed.

In step S8, SvO2 estimation SpO2 determination unit 19 determines the beginning, by comparing k_ns_0 with a predetermined value which is an index of the noise component, the noise component state. Process divided by the determination result in the following two. The predetermined value is selected appropriately in accordance with the level of the noise component to be removed, for example, which in this embodiment is 0.05 like.

Indication of the noise component is zero or small, (e.g., | k_ns_0 | <0.05) in the SvO2 when the estimated SpO2 determination unit 19 determines (No), for example, is known as a conventional art, the wavelength IR to k_a is k_a using absorbance variation of the signal components and the ratio is a method of obtaining a mean value equation the change in the signal component of the absorbance at a wavelength R (14) is calculated (step S9), and followed by step S14 There is executed.

Figure JPOXMLDOC01-appb-I000014

On the other hand, in step S8, the index of the noise component is larger (e.g. | k_ns_0 | ≧ 0.05) in the case where the SvO2 estimating SpO2 determination unit 19 determines (Yes), step S10 is executed, the periodicity is calculated.

As described in the principle of the present invention, selected K_v as q corresponding to the left side (the following formula (see 15) has the strongest periodicity of formula (4) is a best K_v.

Figure JPOXMLDOC01-appb-I000015

Here, q represents the value of the left side of for a K_v, i-th data sequence in which the formula (4).

More specifically, according to the value of K_v, formula (15), for how changes will be described below with reference to FIG.

Figure 6 is a diagram showing the R-kv * IR waveform by the measured data used in FIG. 6 (a) is the case given in the optimum value less than the K_v, shows a waveform by data series given by equation (15) for K_v, FIG. 6 (b), is approximated to the optimum value K_v that when given a value, shows a waveform by data series given by equation (15) for K_v, and, FIG. 6 (c), when given at the optimum value greater than a K_v, expression for K_v ( It shows the waveform by the data sequence given by 15). The waveform is interpolated between data of the time series data. In FIGS. 6 (a) from (c), these horizontal axis is a predetermined short time period (corresponding to the data sequence from 1, number i of the data sequence to N), the vertical axis is the q of formula 15 .

When given in equation (15) is an optimum value smaller than K_v, when given in a waveform shown in FIG. 6 (a), the value K_v which approximates the optimal value equation (15), 6 ( and it has a waveform shown in b). These as seen by comparing the two figures, in the case (FIG. 6 (b) the value k_v approximated to the optimum value is substituted, strong periodicity in waveform even when a noise component to the signal component is superimposed Although observed, when given in equation (15) is an optimum value smaller than K_v, the noise component to the signal component is superimposed, the waveform is disturbed, weak periodicity. then, greater than the optimum value when given in equation (15) is a K_v, has a waveform shown in FIG. 6 (c). the FIG. 6 (c) as can be seen by comparison with FIG. 6 (b), the optimum value greater than K_v to the case given in equation (15) (FIG. 6 (c)), the noise component to the signal component is superimposed, the waveform is disturbed, weak periodicity.

To utilize the change in the expression (15) for more K_v, periodicity of formula (15) is detected. More specifically, in the present embodiment, the period of q given by Equation (15) is calculated. That is, in step S10, as K_v_0 the initial value of K_v, within the K_v a predetermined (e.g., k_v_0-0.5 <k_v <k_v_0 + 0.5) to q given by a sequential change is not obtained formula (15) 2 by digitizing the width of the waveform is calculated. Incidentally, the threshold value used for binarizing, may be stored in advance in the measurement unit 10, be determined appropriately from the amplitude characteristics of the data as 40 percent, such as measurement unit 10 is, for example, with respect to the maximum amplitude of the data good.

Briefly a specific procedure for calculating the width of the binarized waveform. Binarizing the value of equal to or higher than a predetermined threshold constant (e.g., 1) converts into a value less than the threshold value other constants (e.g., 0) is the process of converting to. Incidentally, the binarization threshold value, a suitable value (e.g., 0), but is chosen, is not limited thereto and may be changed as appropriate.

For example, the use of the constant, after q of formula (15) is a binary process, takes the value of one or zero, focusing on 1 and zero adjacent, and one adjacent zero it is the period of the waveform to be calculated period that set is repeated. For one and a zero adjacent to calculate the period of all waveform. Further, for example, fine sub-peak in order to remove, by plotting the time to be a predetermined amplitude or more levels between the q of formula (15) is increased (or decreased), the average value of the difference of time in the plots of the adjacent it may be used as the cycle. The predetermined amplitude may be stored in advance in the measurement unit 10, measurement unit 10 may be determined from the amplitude characteristic of the data.

In step S11, the SvO2 estimation SpO2 determination unit 19, obtained in the step S10, the range of K_v_0 given the initial value of each K_v (e.g., k_v_0-0.5 <k_v <k_v_0 + 0.5) are sequentially varied variations in the width of the resulting waveform is calculated and determined k_v such variations is minimized.

Incidentally, in Metropolitan step S10 and step S11, as an index for determining the k_v like having a periodicity formula (15), but using periodic peaks and valleys of the binarized processed waveforms, limited to not intended to be. In binarization processing after waveform, as other indicators, only periods mountain is repeated, it may be used only cycle trough is repeated. The maximum value of the period of mountain - minimum value of the period of the mountain, the maximum value of the period of the valley - minimum value of the period of the valley, the standard deviation of the period of the mountain, the standard deviation of the period of the valley, the maximum value of the width of the mountain - the minimum value of the width of the mountain, the maximum value of valley width - minimum width of the valley, the standard deviation of the width of the mountain may be used the standard deviation of the valley width. Further, as an index, the maximum amplitude determined from the maximum and minimum values ​​of the waveform of R_signal-k_v * IR_signal - may be used minimum and standard deviation or the like.

Although the above has been described as providing one threshold may be set multiple thresholds. For example, a provided threshold value 1 and threshold value 2, and threshold value 1> 0, the threshold value 2 <0. +1 If the formula (15)> threshold 1, formula (15) <-1 if threshold 2, the threshold value 1 ≦ formula (15) ≦ threshold 2 0 +1 pulse width and pulse period of the variation in the case ( maximum - minimum or standard deviation) and / or -1 of the pulse width and pulse period fluctuation (maximum value - minimum value and standard deviation) may be obtained as an optimal value k_v to minimize. Further, a pulse binarized depending on whether the signal corresponding to the formula (15) exceeds the threshold value 1 for each pulse that is binarized by whether more than the threshold value 2 the indication of the various periodicity of the calculates and an average value (simple mean, harmonic mean, including geometric average) may be an optimum value k_v to minimize. Furthermore, it provided with three or more thresholds, an indication of the variety of periodicity for formula (15) three or more kinds of binary pulses respectively signals corresponding is binarized by whether more than the respective thresholds to it is calculated and the average value (simple mean, harmonic mean, including geometric average) may be an optimum value k_v to minimize. Amount of calculation for increasing the number of threshold is increased, but the advantage of improving the accuracy of evaluation of the periodicity.

In any indicator, from differentially between the maximum value and the minimum value of the standard deviation and indicators indicators within a predetermined time may be calculated k_v such as variations in the most indices is minimized. When using a plurality of indicators, which may k_v for each index to a minimum it is different. In that case is the optimum value harmonic mean value of k_v for each index to a minimum. Simple average value as an average value, may be the geometric mean value. It is also possible to employ a closest multiple previous k_v of k_v that a plurality of indices to a minimum. The average value of the plurality of indices (simple average, harmonic mean, etc. geometric mean value) may be evaluated as an index. Since K_v is not changed rapidly, in evaluating the indication of changing the K_v, as an absolute value or an index value obtained by multiplying a coefficient corresponding to that of the difference between those of the previous K_v optimum value and K_v it may be evaluated.

In step S10 and step S11, as an example utilizing the periodicity, an example for obtaining the k_v as the left-hand side of equation (15) satisfies the periodicity is not limited to the equation (15) if a formula that k_v is represented by the signal components, it may be used in place of the equation (15).

Next, in step S12, SvO2 estimation SpO2 determination unit 19, a k_v obtained in step S11 are substituted into the equation (8) is calculated k_a by solving this equation. Equation (8) R_signal, may be replaced with a respective time difference between the IR_signal.

Incidentally, in step S10 and step S11 Prefecture, when asked multiple K_v according to a plurality of indicators for each K_v, and each calculated k_a such equality is established of the formula (8) it may be. How to determine the final k_a from multiple k_a, the average value of the plurality of k_a (simple average, harmonic mean, geometric mean value, etc.) may be a final k_a a previous one of the plurality of k_a it is closest to the final k_a may be present final k_a, or as the final k_a an average value but excluding the maximum and minimum of the plurality of k_a. Furthermore, it may be weighted mean over the weight corresponding to the absolute value of the difference between the previous k_a. Further, calculation k_v approximately 200 pairs of R_signal, said determined by the method for IR_signal, four k_a by solving equation (8) 4 sets of 200 sets of data, for example, 4 divided by the time of obtaining the k_a the average value of them was (simple average, harmonic mean, geometric mean value, such as weighted average values ​​to weight the absolute value of the difference between the previous k_a) may be obtained. The average value of k_a said four k_a found throughout 200 sets of data may be further averaged.

In addition, in step S10 and step S11, when a plurality of k_v is obtained in accordance with the respective plurality of indices were obtained by median or previous arterial oxygen saturation calculation, the range of consecutive k_v value closest to the k_v it may be used as the optimum value. Note that the index is zero noise component in the description so far, or less when it has been calculated k_a by conventional methods such as formula (14), by substituting k_v (= k_v_0) previous to the formula (8) k_a may be obtained Te. Left side Σ {IR_signal * k_v-R_signal} * {IR_signal * k_a-R_signal} ≒ if noise is low the formula (8) (k_v-k_a) * ΣIR_signal * {IR_signal * k_a-R_signal} ≒ (k_v-k_a) * Since {ΣIR_signal 2 * k_a-ΣIR_signal * R_signal}, by substituting a value different from the k_a as K_v, equation is equivalent to ΣIR_signal 2 * k_a-ΣIR_signal * R_signal = 0. This solution k_a = ΣIR_signal * R_signal / ΣIR_signal 2 is obtained. So R_signal ≒ true k_a * IR_signal when the noise is small, the right-hand side of the above equation is the true k_a. Accordingly, by solving by substituting the values ​​appear to differ from the k_a such previous k_v the formula (8), it is possible to obtain a value sufficiently close to the true k_a. Although when the noise is small has a strong periodicity on the R_signal-k_v * IR_signal a wide range of K_v, were subjected to various index absolute value of the difference of the previous K_v and K_v Even then the value by evaluating, the optimum value of k_v is substantially close to the previous k_v, can be time indicator of noise is large and even if the same processing to obtain a value sufficiently close to the true k_a. When than the calculated speed to emphasize simplification of the program may not divide the processing by the size of the noise index.

Next, in step S13, the SvO2 estimation SpO2 determination unit 19, using equation (9), calculates the k_ns indicative of the noise component. The calculation of K_ns, the memory stored ΣR_signal * IR_signal, ΣR_signal 2 and ShigumaIR_signal 2 is used in step S7.

Next, in step S14, the SvO2 estimation SpO2 determination unit 19 calculates the reliability or k_v reliability of k_a, based on k_a, to calculate the blood oxygen saturation. Here, the reliability of k_a, a value indicating the degree of error contained in k_a. Similarly, the reliability of K_v, a value indicating the degree of error contained in K_v.

Next, in step S15, the SvO2 estimation SpO2 determination unit 19, in preparation for the next measurement, the K_v, stored as K_v_0. SpO2 output section 22 and the reliability output unit 24, and outputs the reliability of each and blood oxygen saturation is detected at step S14 k_a. Reliability output unit 24 may output the reliability of k_v instead reliability k_a. Further, that the measurement unit 10 compares the K_ns the first predetermined value calculated in step S13, K_ns is if it exceeds a first predetermined value, the K_ns exceeds a first predetermined value a warning to alert the output to the SpO2 output unit 22. Further, warning measuring unit 10 compares the reliability and the second predetermined value k_a, when k_a exceeds a second predetermined value, indicating k_a exceeds a second predetermined value may output further to the reliability output unit 24 a. The measurement unit 10 uses the reliability of K_v instead reliability of k_a, compared with the predetermined value the reliability and the third of K_v, if K_v exceeds a third predetermined value the, K_v may output a third addition reliability output unit 24 a warning indicating that exceeds a predetermined value.

In general, the magnitude of the calculated arterial oxygen saturation value, and the errors contained in it is known to be different, for example, arterial oxygen saturation between cases where the arterial oxygen saturation of about 95% and 70% every time the magnitude of the error is different. Therefore, the predetermined value of k_ns alters as follows. Predetermined value of k_ns is smaller sets a predetermined value of k_ns if arterial oxygen saturation is smaller than the predetermined arterial oxygen saturation (large and k_a and K_v, corresponds to a case the blood oxygen saturation in the vein is small) and, on the other hand, large sets a predetermined value of k_ns if arterial oxygen saturation is greater than a predetermined arterial oxygen saturation (smaller and k_a and K_v, corresponds to a case the blood oxygen saturation in the vein is large) in the opposite Then good. Thus in accordance with the calculated value of the arterial oxygen saturation, by changing the predetermined value of K_ns, for example, if a large arterial oxygen saturation by increasing the threshold value, almost as if arterial oxygen saturation is small it is possible to perform a warning or output prohibited by the same value. Here, the predetermined value of k_ns corresponding to a predetermined arterial oxygen saturation and predetermined arterial oxygen saturation may be stored in advance values ​​determined based on the past measurement data to the measurement section 10 it may be changed as appropriate according to the state of the living body or living body. Besides the k_ns as an indicator of the reliability of the obtained k_a or K_v, for example, it may be used the values ​​z given by Equation (16) in any of the formula (21). When the absolute value of z is large, the reliability of k_a is low. Further, when the absolute value of z is larger, the reliability of k_v is low.

Figure JPOXMLDOC01-appb-I000016
Figure JPOXMLDOC01-appb-I000017
Figure JPOXMLDOC01-appb-I000018
Figure JPOXMLDOC01-appb-I000019
Figure JPOXMLDOC01-appb-I000020
Figure JPOXMLDOC01-appb-I000021

Furthermore, as an alternative indicator of the reliability of k_a, variations of given values ​​w by the following equation (22) (standard deviation, maximum value - minimum value, etc.) may be used. Variation in the value w is small, the reliability of k_a obtained shows a high.

Figure JPOXMLDOC01-appb-I000022

In addition, the R_signal y, IR_signal may evaluate k_a reliability from differentially with variation and maximum and minimum values ​​of y with respect to the regression line of the (x, y) in the case of the x and.

<Pulse rate detection flow (S16 ~ S20)>
5, steps S16, the pulse rate calculating section 20 starts the pulse rate detection flow. In step S17, the pulse rate calculating section 20, the k_v calculated in step S11 in blood oxygen saturation flow, determine the pulse waveform from which noise components are removed. The pulse rate calculating section 20, similarly to the binarization processing performed in step S10, with respect to pulse waveform from which noise components are removed, performs binarization processing. It this threshold in this case may be 0, or a threshold value used when determining the above K_v.

Next, in step S18, the pulse rate calculating section 20, R_signal (i) -k_v * average of IR_signal period within a predetermined time (i) T (j) T_ave (T_ave = 1 / N (ΣT (j) )) is calculated.

Next, in step S19, to calculate the pulse rate. Pulse rate is calculated as the reciprocal of the period. That is, the pulse rate as a Pulse (times / min), represented by Pulse = 60 / T_ave. R_signal (i) -k_v * IR_signal Fourier or may calculate the pulse rate from the frequency at which the peak of the absolute value of (i).

Next, in step S20, the pulse rate calculating section 20, and outputs the calculated number of pulse to pulse rate output unit 23, and ends the pulse rate detection flow.

By such an operation, the biological information measuring device 30, the oxygen saturation detecting flow and pulse rate detecting flow to measure the oxygen saturation and pulse rate.

According to the above-described embodiment, since the removal of the noise component by utilizing the periodicity of the signal components, it is possible to simplify the operation process from the prior art, it is possible to reduce the amount of arithmetic processing . Therefore, it is possible to suppress the power consumption associated with the operation processing. As a result, it becomes possible to use the battery in the biological information measuring device 30, it is possible to provide a convenient size and weight biological information measuring device to the mobile. For this reason, for example, climbers and home oxygen therapy patients it is possible to reduce the physical burden even if the mobile phone at all times.

The biological information measuring device 30 according to this embodiment, on the basis of the index with information on the ratio of the intensity of the signal component and the intensity of the noise component, since it is determined whether to extract a noise component, in case the noise component is small enough to be ignored, it is possible to omit the operation for removing the noise component, reduces the computation time for obtaining biometric information, a longer battery operating time with reduced power consumption it is possible, it can be obtained more quickly biological information.

The biological information measuring device 30 according to this embodiment, audio, biological information by characters and light, etc., so outputs a signal reliability and noise confidence, it is possible to confirm these easily. Further, the biological information measuring device 30 according to this embodiment, since the index outputs a warning indicating a decrease warning, or signal reliability or noise confidence indicating that exceeds a predetermined value, the measured person and measurement it is also possible to draw attention with respect to the handling of biological information to, such as Sha. Then, the index, in response to said noise reliability and the signal reliability, it is possible to change the handling of calculated biological information, for example, it is possible to re-measurement or the like based on the index.

The biological information measuring device 30 according to this embodiment, when calculating the pulse rate, by using the binarized waveform can be reduced for example erroneous measurements by double peaks like.

The biological information measuring method according to the present embodiment, the same computing resources (hardware resources), can be calculated biological information at an earlier computation time.

In the above embodiment, as an example, by detecting a change in light intensity of two wavelengths having a periodicity illustrated the biological information measurement device 30 for determining the blood oxygen saturation. In addition, based on the change in light intensity of one wavelength with periodicity, pulse, detection of arrhythmia (atrial fibrillation, extrasystole), defibrillation when the monitor, autonomic neuropathy, a diagnosis such as blood vessel age also possible to apply the present invention to the biological information measurement device that performs. Furthermore, in addition to pulse waveform, to an apparatus for biological information of the electrocardiogram, such as a measurement target it can be applied.

In the above embodiment, when calculating the K_v, but utilizing the periodicity of the signal components, instead of the steps S11 and Step S12, the formula of the Fourier transform of q given by Equation (15) (23) it may be used.

Figure JPOXMLDOC01-appb-I000023

Here, F is the Fourier transform, ω is the frequency. | F (ω) | of it may be obtained k_v from omega to the maximum peak height / peak width as an indicator. k_v the multiplied by the absolute value of the difference between the k_v and the previous k_v in this indicator may be the best indication of whether or not. The omega gives a peak of F (omega) at which the optimum K_v was obtained by 60 times may be obtained pulse rate, determine the pulse rate from the period of R_signal-k_v * IR_signal with optimal K_v and it may be.

In addition, in the above embodiment, when to calculate the K_v, but utilizing the periodicity of the signal components, instead of steps S11 and step S12, the q given by Equation (15), from the square of q the q square of the time average may be used equation (24) is the Fourier transform of the subtracted signal.

Figure JPOXMLDOC01-appb-I000024

Here, P is, Fourier transform, ω is the frequency. P (omega) of the peak height / peak width as an indicator it may be determined k_v from omega maximized. k_v the multiplied by the absolute value of the difference between the k_v and the previous k_v in this indicator may be the best indication of whether or not. The optimum values ​​obtained by 30 times the omega gives a peak of P when k_v was obtained (omega) may be a pulse rate.

Note that, in step S9 in the embodiment described above, from the equation in place of (14) the following equation (25) using any of the formula (34) may be obtained k_a.

Here, the formula (26) formula (25) is an equation for obtaining the k_a from the ratio of the time difference between R_signal and IR_signal.

Figure JPOXMLDOC01-appb-I000025
Figure JPOXMLDOC01-appb-I000026

Equation (29) From Equation (27) is an equation for obtaining the k_a from the ratio of the autocorrelation and cross-correlation R_signal and IR_signal.

Figure JPOXMLDOC01-appb-I000027
Figure JPOXMLDOC01-appb-I000028
Figure JPOXMLDOC01-appb-I000029

Equation (30) is an equation for obtaining the k_a from the slope of the regression line of R_signal and IR_signal. Note that Δ in equation (34) from the following equation (30) represents the time difference between each data series.

Figure JPOXMLDOC01-appb-I000030
Figure JPOXMLDOC01-appb-I000031
Figure JPOXMLDOC01-appb-I000032
Figure JPOXMLDOC01-appb-I000033
Figure JPOXMLDOC01-appb-I000034

As described above, the novel biological information signal processing apparatus comprises: a first time-series signal including a first signal component and a first noise component having a periodicity, the first signal component and a predetermined relationship 2 signal component and the second time series signal including the second noise component having the first noise component in a predetermined relationship and, based on said predetermined relationship between said first noise component and the second noise component , using the periodicity of the first time and the signal generator for generating a signal including the first signal component from the time-series signal and the second time series signals and, the product signal at a first predetermined time range Te, and a estimation unit that estimates a predetermined relationship with said first of said first noise component and said second noise component at a given time range.

Further, in the above-described biological information signal processing apparatus, the signal generation unit further generates a binary signal by performing binarization processing on the generated signal, wherein the estimation unit, the period of the binary signal preferably, estimating the period of the generated signal with sex.

Further, in the above-described biological information signal processing apparatus, wherein the estimating unit for calculating the periodicity of the binary signal, of the change in variation and pulse period of the pulse width of the binary signal, at least one whether it is preferable to use.

Further, in the above-described biological information signal processing apparatus, the estimating unit, at a first predetermined time range, calculating a plurality of maximum values ​​and / or minimum values ​​of the generation signal, variations in the plurality of maxima and / or by using a plurality of variations in local minima, it is preferable to calculate the period of the generated signal.

Further, in the above-described biological information signal processing apparatus, the estimating unit, based on the plurality of indices having information on the period of the generated signal, preferably calculates the period of the generated signal.

Further, in the above-described biological information signal processing apparatus, the signal generation unit, by performing the Fourier transform on the first of the generated signal at a predetermined time range, further generates the Fourier signal, the estimating unit, the based on the peak width of the Fourier signal, preferably estimates the predetermined relationship between the first of the first noise component and said second noise component at a given time range.

Further, in the above-described biological information signal processing apparatus, the estimation unit uses the periodicity of the generated signal, more preferably to calculate the period of the periodic or the second signal component of said first signal component.

Further, in the above-described biological information signal processing apparatus, the estimating unit, the first of the first noise component at a given time range and said predetermined relationship between said second noise component, said first predetermined time preferably further estimates said predetermined relationship with said second signal component and said first signal component by using the said the first signal component and the first noise component independent range.

Further, in the above-described biological information signal processing apparatus, the estimating portion includes a predetermined relationship between the first of the first noise component and said second noise component at a given time range, the second predetermined time range in using and that the first signal component and a first noise component is independent, further estimates said predetermined relationship between said second of said first signal component at a given time range and the second signal component it is preferable to.

Further, in the above-described biological information signal processing apparatus, the second predetermined time range is a plurality, the estimation unit, the first signal component for each of the second predetermined time range and the second signal component preferred said predetermined relationship to that estimate, respectively.

Further, in the above-described biological information signal processing apparatus, the estimation unit uses a predetermined relationship between said second of said first signal component of each predetermined time range and the second signal component, the first signal preferably, it calculates the average value of the predetermined relationship between the component and the second signal component.

Further, in the above-described biological information signal processing apparatus, the estimating unit, the first of said first signal component at a given time range and said predetermined relationship between said second signal component, the second predetermined time using said first signal component for each range and the predetermined relationship between the second signal component, preferably calculates the average value of said predetermined relationship between said first signal component and the second signal component .

Further, in the above-described biological information signal processing apparatus, preferably the average value is a value calculated by the weighted average.

Further, in the above-described biological information signal processing apparatus, the estimating unit, as an index for determining whether to remove the first noise component, regarding the ratio between the first noise component of the first signal component further calculates the index with information, the indicators and by comparing the first predetermined value, when it is determined that the removal of the first noise component, the said first time series signal a 2 when based on the sequence signal, preferably estimates the predetermined relationship between said first signal component and the second signal component.

In the biological information signal processing apparatus having such a configuration, since removes a noise component by using the periodicity, the signal processing amount required for the noise component removal can be reduced compared with the conventional art. Therefore, by reducing the amount of signal processing, power consumption due to the operation of the noise component removal also can be suppressed. Furthermore, unnecessary signal processing is not necessary result performed by performing signal processing in accordance with the index, it is possible to speed up the signal processing.

Further, in the above-described biological information signal processing apparatus, the estimating unit further calculates the signal reliability indicating the degree of error contained in the predetermined relationship between said first signal component and the second signal component, the preferably further comprising an output unit for outputting a signal reliability.

Further, in the above-described biological information signal processing apparatus, the estimating unit further calculates the noise confidence indicating the degree of error contained in the predetermined relationship between said first noise component and the second noise component, wherein preferably further comprising an output unit for outputting a noise reliability.

Further, in the above-described biological information signal processing apparatus, the estimator compares the signal reliability and the second predetermined value, when the signal reliability has exceeded the second predetermined value, the output unit is preferably further outputs a warning indicating that the signal reliability has exceeded the second predetermined value.

Further, in the above-described biological information signal processing apparatus, the estimating unit compares the predetermined value of the noise confidence and third, when the noise confidence exceeds the third predetermined value, the output unit is preferably further outputs a warning indicating that the noise confidence exceeds the third predetermined value.

According to the biological information signal processing apparatus having such a configuration, by referring to the noise confidence or the signal reliability, can recognize the degree of error contained in a predetermined relationship estimated by the estimating unit to become.

Also, novel bio-information signal processing method, in a first predetermined time range, the first time series signal including a first signal component and a first noise component having a periodicity, the first signal a second time series signal including the second noise component having a second signal component and the first noise component in a predetermined relationship with a component in a predetermined relationship, between the first noise component of the second noise component based on said predetermined relationship, using the periodicity of the first time and the signal generating step of generating a signal including the first signal component from the time-series signal and the second time series signals and, the product signal Te, and a estimation step of estimating the predetermined relationship between the second noise component from the first noise component.

Further, in the biometric information signal processing method described above, in the signal generating step, the further generates a binary signal by performing a binarization process to generate a signal, in the estimating step, the period of the binary signal using sex, preferably to estimate the period of the generated signal.

Further, in the biometric information signal processing method described above, in the signal generating step, the generating signal and comparing the at least two thresholds, the generated signal is based on whether exceeds the threshold value, at least two more further generate a binary signal, the estimated step, using the periodicity of the at least two or more of the binary signal, it is preferable to estimate the period of the generated signal.

Further, in the biometric information signal processing method described above, the binarization processing compares the positive threshold and negative threshold value serving as the generation signal and binarizing the reference, the generated signal exceeds the positive threshold If converting the generated signal to the positive first constant, when the generating signal is less than a negative threshold value converts the generated signal to a negative second constant, the generation signal is negative preferably, when the threshold value or more and the positive threshold value or less is a process of converting the generated signal to zero.

Also, calculated in the biometric information signal processing method described above, the estimated step, of the change in variation and pulse period of the pulse width of the binary signal, based on at least either the period of the binary signal it is preferable to.

Further, in the biometric information signal processing method described above, the estimated step, the plurality of maximum values ​​and / or further calculates a plurality of minimum values, variations and / or minimum values ​​in the plurality of maximum values ​​of the generation signal with variation, preferably calculates the period of the generated signal.

Further, in the biometric information signal processing method described above, the estimated step uses a plurality of indices representative of the periodicity of the generated signal, the first of the first noise component and the second noise at a given time range preferably, estimating the said predetermined relationship with the component.

Further, in the biometric information signal processing method described above, the estimated step, using the periodicity of the generated signal, preferably further to estimate the amount corresponding to the period of the first signal component or the second signal component .

In such a configuration of the biological information signal processing method, removes a noise component by using the periodicity, the signal processing amount required for the noise component removal can be reduced compared with the conventional art. Therefore, by reducing the amount of signal processing, power consumption due to the signal processing of the noise component removal also can be suppressed.

Furthermore, the novel biological information measuring device includes at least first measurement data and the second obtained by receiving each respective light transmitted through or reflected by the living body by irradiating each a plurality of lights having different wavelengths to the living body to each other based on the measured data, and the a biological information measurement device that measures biological information of a living body, the first measuring unit for measuring a first signal component and the first measurement data consisting of first noise component having a periodicity, a second measuring unit for measuring a second measurement data including a second noise component having a second signal component and a first noise component in a predetermined relationship with said first signal component and a predetermined relationship, the first measurement data When the second measurement data, the first noise component and on the basis of said predetermined relationship between said second noise component, the first signal from the first measurement data and the second measurement data A signal generator for generating a signal including a component, and a estimation unit by using the periodicity of the generated signal, and estimates the predetermined relationship between the second noise component from the first noise component.

Further, in the above-described biological information measurement device, the estimation unit uses the periodicity of the generated signal, preferably estimates the predetermined relationship between said first noise component and the second noise component.

Further, in the above-described biological information measurement device, the estimating unit includes a first noise component and said predetermined relationship between said second noise component from the first signal component and the first noise component is independent based on the fact, preferably further estimates the predetermined relationship between said first signal component and the second signal component.

Further, in the above-described biological information measurement device, the period of the periodic or the second signal component of said first signal component is a due pulsation of arterial blood, the first noise component or the second noise component the biological be by the body movement, the cycle preferably comprises information about the pulse rate.

Further, in the above-described biological information measurement device, wherein the predetermined relationship between the first signal component and said second signal component preferably includes information on arterial oxygen saturation.

According to such a configuration of the biological information measuring apparatus, it is possible to provide a biological information measuring apparatus for measuring the blood oxygen saturation of a living body that suppresses power consumption by reducing the amount of arithmetic processing.

In order to express the present invention, although the present invention was described appropriately and sufficiently through embodiments with reference to the drawings in the above, it is easily to change and / or improve the above embodiments by those skilled in the art it should be recognized that is to be. Accordingly, modifications or improvements embodiment those skilled in the art to practice as long as not intended levels leaving the scope of the claims claimed, the modifications or the refinement, the scope of the claims It is intended to be encompassed by the.

Claims (31)

  1. The first signal component and the first time series signal related to biometric information including the first noise component, a second signal component and the first noise component with a predetermined having the first signal component and a predetermined relationship with periodicity when the series signal, based on said predetermined relationship between said second noise component from the first noise component, the first time series signal of the second related to biometric information including a second noise component having a relationship a signal generator for generating a signal including the first signal component and a said second time series signal,
    Using the periodicity of the first of the generation signal at a predetermined time range, an estimation unit that estimates a predetermined relationship with said first of said first noise component at a given time range and the second noise component biometric information signal processing apparatus comprising: a.
  2. In the biological information signal processing apparatus according to claim 1, wherein the signal generator generates a binary signal by performing binarization processing on the generated signal, wherein the estimation unit, of the binary signal estimating the period of the generated signal using the periodicity.
  3. In the biological information signal processing apparatus according to claim 2, wherein the estimating unit for calculating the periodicity of the binary signal, of the change in variation and pulse period of the pulse width of the binary signal, at least one is used.
  4. In the biological information signal processing apparatus according to claim 1, wherein the estimation unit, in a first predetermined time range, calculating a plurality of maximum values ​​and / or minimum values ​​of the generation signal, a plurality of local maxima with variations in change and / or a plurality of minima in, it calculates the period of the generated signal.
  5. In the biological information signal processing apparatus according to claim 1, wherein the estimating unit, based on the plurality of indices having information on the period of the generated signals, calculates the period of the generated signal.
  6. In the biological information signal processing apparatus according to claim 1, wherein the signal generating unit, by performing the Fourier transform on the generated signal at the first predetermined time range, to generate a Fourier signal, the estimation unit, on the basis of the peak width of the Fourier signal, it estimates the predetermined relationship between the first of the first noise component and said second noise component at a given time range.
  7. In the biological information signal processing apparatus according to claim 1, wherein the estimation unit uses the periodicity of the generated signal, to calculate the period or cycle of the second signal component of said first signal component.
  8. In the biological information signal processing apparatus according to claim 1, wherein the estimation unit, and the predetermined relationship between the first of the first noise component and said second noise component at a given time range, the first estimating the predetermined relationship between the second signal component and said first signal component by using the means that the first signal component and the first noise component at a predetermined time range is independent.
  9. In the biological information signal processing apparatus according to claim 7, wherein the estimation unit, the said first noise component and said predetermined relationship between said second noise component at a first predetermined time range, the second predetermined with the things in the time range from the first signal component and a first noise component is independent, and the second of said first signal component of a predetermined time range of the predetermined relationship between the second signal component presume.
  10. In the biological information signal processing apparatus according to claim 9, wherein the second predetermined time range is a plurality, the estimation unit, the second of said first signal component and said second signal for each predetermined time range estimating each said predetermined relationship with the component.
  11. In the biological information signal processing apparatus according to claim 10, wherein the estimation unit uses a predetermined relationship between said second of said first signal component of each predetermined time range and the second signal component, the first calculating the average value of a predetermined relationship between the one signal component a second signal component.
  12. In the biological information signal processing apparatus according to claim 10, wherein the estimation unit, the first of said first signal component at a given time range and said predetermined relationship between said second signal component, the second using said predetermined relationship between said first signal component and said second signal component of each predetermined time range, and calculates an average value of said predetermined relationship between said first signal component and the second signal component.
  13. In the biological information signal processing apparatus according to claim 12, wherein the average value is the value determined by the weighted averages.
  14. In the biological information signal processing apparatus according to claim 9, wherein the estimation unit, as an index for determining whether to remove the first noise component, and the first noise component of said first signal component calculates the index with information on the specific, the index and by comparing the first predetermined value, wherein when it is determined that the removal of first noise component, the said first time series signal based on the second time series signals, and estimates the predetermined relationship with the second signal component and the first signal component.
  15. In the biological information signal processing apparatus according to claim 14, wherein the estimation unit calculates a signal reliability indicating the degree of error contained in the predetermined relationship between said first signal component and the second signal component, further comprising an output unit which outputs the signal reliability.
  16. In the biological information signal processing apparatus according to claim 14, wherein the estimation unit calculates a noise confidence indicating the degree of error contained in the predetermined relationship between said first noise component and the second noise component, further comprising an output unit which outputs the noise confidence.
  17. In the biological information signal processing apparatus according to claim 15, wherein the estimation section compares the signal reliability and the second predetermined value, when the signal reliability has exceeded the second predetermined value to the output unit outputs a warning indicating that the signal reliability has exceeded the second predetermined value.
  18. In the biological information signal processing apparatus according to claim 16, wherein the estimation unit, when the noise confidence and compared with the third predetermined value, the noise confidence exceeds the third predetermined value to the output unit outputs a warning that the noise confidence exceeds the third predetermined value.
  19. The having at a first predetermined time range, the first time series signal related to biometric information including the first signal component and a first noise component having a periodicity, the first signal component and a predetermined relationship 2 signal component and second time series signals related to biometric information including a second noise component having the first noise component in a predetermined relationship and, between the first noise component and said predetermined relationship between said second noise component and, the signal generating step of generating a signal including the first signal component from said first time series signal and the second time series signals based on,
    Using periodicity of the generated signal, biological information signal processing method characterized by comprising the estimating step of estimating the predetermined relationship between said first noise component and the second noise component.
  20. In the biological information signal processing method according to claim 19, in the signal generating step, to generate a binary signal by performing binarization processing on the generated signal, the estimated step, of the binary signal with periodicity, to estimate the period of the generated signal.
  21. In the biological information signal processing method according to claim 19, in the signal generating step, the generating signal and comparing the at least two thresholds, the generated signal is based on whether exceeds the threshold value, at least generating two or more of the binary signal, the estimated step, using the periodicity of the at least two or more of the binary signal, to estimate the period of the generated signal.
  22. In the biological information signal processing method according to claim 20, wherein the binarization processing compares the positive threshold and negative threshold value serving as the generation signal and binarizing the reference, the generated signal positive threshold converting the generated signal to the positive first constant when exceeding, if the generated signal is less than the negative threshold value converts the generated signal to a negative second constant, the generated signal is If it is less than the negative threshold or more and the positive threshold is the process of converting the generated signal to zero.
  23. In the biological information signal processing method according to claim 20, wherein in estimating step, of the change in variation and pulse period of the pulse width of the binary signal, based on at least one, the period of the binary signal It is calculated.
  24. In the biological information signal processing method according to claim 19, wherein the estimated step calculates a plurality of maximum values ​​and / or minimum values ​​of the generation signal, variations in the plurality of maxima and / or minima with variations in, and calculates the cycle of the generation signal.
  25. In the biological information signal processing method according to claim 19, wherein in estimation step, using a plurality of indices representative of the periodicity of the generated signal, the said first of said first noise component at a given time range the estimating the said predetermined relationship between the second noise component.
  26. In the biological information signal processing method according to claim 19, wherein in estimation step, using the periodicity of the generated signal, to estimate the amount corresponding to the period of the first signal component or the second signal component.
  27. Based a plurality of lights having different wavelengths in at least first measurement data or the second measurement data obtained by receiving each respective light transmitted through or reflected by the irradiated respectively to the living biological mutually, biometric of the biological a biological information measurement device that measures information,
    A first measuring unit for measuring a first signal component and the first measurement data consisting of first noise component having a periodicity,
    A second measuring unit for measuring a second measurement data including a second noise component having a second signal component and a first noise component in a predetermined relationship with said first signal component and a predetermined relationship,
    Wherein from said first measurement data, and the second measurement data, on the basis of said predetermined relationship between said second noise component from the first noise component, and the first measurement data and the second measurement data a signal generator for generating a signal including a first signal component,
    Using periodicity of the generated signal, the first noise component and the biological information measuring apparatus characterized by comprising a an estimation unit that estimates a predetermined relationship with said second noise component.
  28. In the biological information measuring apparatus according to claim 27, wherein the estimation unit uses the periodicity of the generated signal, and estimates the predetermined relationship between the first noise component and the second noise component.
  29. In the biological information measuring apparatus according to claim 27, wherein the estimation unit is independent of the first noise component and said predetermined relationship between said second noise component, the first signal component of the first noise component in it based on the fact, it estimates the predetermined relationship between the second signal component and the first signal component.
  30. In the biological information measuring apparatus according to claim 29, wherein the period or cycle of the second signal component of the first signal component is a due pulsation of arterial blood, the first noise component or the second noise component be by the body movement of the living body, the cycle includes information about pulse rate.
  31. In the biological information measuring apparatus according to claim 30, wherein the predetermined relationship between the first signal component and the second signal component includes information regarding arterial oxygen saturation.
PCT/JP2009/070616 2008-12-26 2009-12-09 Biological information signal processing apparatus, biological information signal processing method and biological information measuring apparatus WO2010073908A1 (en)

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