WO2024085042A1 - Device for measuring oxygen saturation, method for measuring oxygen saturation, and program for measuring oxygen saturation - Google Patents

Abstract

This device for measuring oxygen saturation measures arterial oxygen saturation by: projecting, onto an artery, red light, infrared light, and a reference light having a wavelength for which the absorption coefficient for oxidized hemoglobin and the absorption coefficient for reduced hemoglobin are higher than those for the red light and infrared light; receiving, as received light, transmitted light or reflected light corresponding to each of the projected red light, infrared light, and reference light; acquiring a first pulse wave signal in accordance with the light intensity of the received light for the red light, a second pulse wave signal in accordance with the light intensity of the received light for the infrared light, and a third pulse wave signal in accordance with the light intensity of the received light for the reference light; and calculating first information based on the strength of the first pulse wave signal and the strength of the third pulse wave signal, calculating second information based on the strength of the second pulse wave signal and the strength of the third pulse wave signal, and calculating an oxygen saturation based on the ratio between the respectively calculated first information and second information.

Description

Oxygen saturation measurement device, oxygen saturation measurement method, and oxygen saturation measurement program

This disclosure relates to an oxygen saturation measurement device, an oxygen saturation measurement method, and an oxygen saturation measurement program.

Conventionally, as one example of a method for measuring oxygen saturation ( _SpO2 ) in arterial blood, a measurement method using absorption spectroscopy is known, as disclosed in Japanese Patent Laid-Open Publication No. 7-327964. Specifically, red light and infrared light having different wavelengths are projected onto arterial blood, and transmitted light or reflected light corresponding to each light is received by a light receiving element. For ease of explanation, the light received by the light receiving element, such as transmitted light and reflected light, will be collectively referred to as "received light" below.

Patent document 1: JP 7-327964 A

In absorption spectroscopy, multiple amplitudes of the pulse wave signal for each of the red light and infrared light are calculated from the maximum and minimum values obtained from the pulse wave signal of the received light. The fluctuating component (in other words, AC) and fixed component (in other words, DC) of the pulse wave signal are calculated from the multiple calculated amplitudes, and the perfusion index (PI value) for each of the red light and infrared light is calculated from the calculated fluctuating component and fixed component.

Then, by introducing the ratio of the PI value of red light to the PI value of infrared light (i.e., the absorbance ratio) into a preset formula for calculating oxygen saturation, the measured oxygen saturation value can be calculated. In other words, the absorbance ratio is calculated by the amplitude ratio of the amplitude of the pulse wave signal of infrared received light to the amplitude of the pulse wave signal of red received light.

However, the lower the blood perfusion, i.e., the weaker the light intensity of the received light pulse wave signal, the lower the signal-to-noise ratio, and the lower the accuracy of calculating the amplitude of the pulse wave signal. For this reason, when the absorbance ratio is calculated based on the amplitude ratio, the accuracy of calculating the variable and fixed components is also low, resulting in a decrease in the accuracy of measuring oxygen saturation, or even in the event that measurement is impossible.

A method known as the regression method is known as a means for calculating the absorbance ratio even when the signal-to-noise ratio is low. In the regression method, for example, a red light pulse wave signal and an infrared light pulse wave signal that correspond over time are plotted on an XY coordinate system with the received light intensity of the red light on the Y axis and the received light intensity of the infrared light on the X axis to calculate a scatter diagram of the data. Then, using a regression method such as the least squares method, the slope of the regression line found from the scatter diagram of the data is calculated as the absorbance ratio.

In the regression method, all of the waveform data of the pulse wave signal of the received light is used to calculate a linear equation that represents the true relationship between red light and infrared light. On the other hand, when the absorbance ratio is calculated from the amplitude ratio, only the maximum and minimum values of the pulse wave signal of the received light are used to calculate the amplitude. For this reason, compared to methods that calculate the amplitude ratio, the regression method is robust even for pulse wave signals with a relatively low S/N ratio, and is capable of calculating the absorbance ratio with high accuracy.

In the regression method disclosed in JP-A-7-327964, red and infrared light are projected onto biological tissue, and the intensity of each transmitted light that passes through the biological tissue is measured. The logarithms of the measured intensities of each transmitted light are plotted on the vertical and horizontal axes. A regression line is then calculated on the coordinate system using the least squares method, and oxygen saturation is measured based on the slope of the calculated regression line.

The least squares method only takes into account the variance in data on one of the X and Y axes. For this reason, the slope of the regression line found by the least squares method may deviate from the slope of the linear equation that represents the true relationship. In particular, in measuring oxygen saturation, if the signal-to-noise ratio of the pulse wave signal of the received light corresponding to red light and the pulse wave signal of the received light corresponding to infrared light, which are variables arranged on each axis, is relatively low, the decrease in measurement accuracy becomes more noticeable. In this regard, the regression method of JP-A-7-327964 cannot suppress the decrease in measurement accuracy because the oxygen saturation is calculated only by the least squares method for the intensity of the transmitted light of red light and infrared light.

The present disclosure has been made in light of the above, and provides an oxygen saturation measurement device, an oxygen saturation measurement method, and an oxygen saturation measurement program that can improve measurement accuracy.

The oxygen saturation measuring device according to the first aspect of the present disclosure includes a sensor unit having a first light-emitting element that projects red light onto the artery, a second light-emitting element that projects infrared light onto the artery, a third light-emitting element that projects reference light onto the artery, the reference light having a wavelength at which the absorption coefficients of oxyhemoglobin and deoxyhemoglobin are higher than those of red light and infrared light, and a light-receiving element that receives transmitted or reflected light corresponding to the projected red light, infrared light, and reference light as received light, and outputs a first pulse wave signal according to the intensity of the received red light, a second pulse wave signal according to the intensity of the received infrared light, and a third pulse wave signal according to the intensity of the received reference light, and a processor that is electrically connected to the light-receiving element and calculates first information based on the intensity of the first pulse wave signal and the intensity of the third pulse wave signal, calculates second information based on the intensity of the second pulse wave signal and the intensity of the third pulse wave signal, and measures the oxygen saturation of the artery by calculating the oxygen saturation based on the ratio between the calculated first information and the second information.

　With the above configuration, the wavelength of the reference light projected onto the artery is a wavelength at which the absorption coefficients of oxygenated hemoglobin and reduced hemoglobin are higher than those of red light and infrared light. Therefore, the signal-to-noise ratio of the third pulse wave signal corresponding to the reference light is higher than those of the first pulse wave signal corresponding to red light and the second pulse wave signal corresponding to infrared light. In other words, the signal-to-noise ratio of the pulse wave signal of the received light depends on the wavelength of the light projected. By including reference light as a third light other than the two lights of red light and infrared light in the oxygen saturation calculation algorithm, the accuracy of oxygen saturation measurement can be improved compared to when the absorbance ratio is calculated using only the two lights of red light and infrared light.

In the second aspect, as in the first aspect, the processor is configured to continuously acquire the intensity of the first pulse wave signal, the intensity of the third pulse wave signal, and the intensity of the second pulse wave signal over time, calculate the slope of the first regression line as first information by regression analysis using the intensity of the third pulse wave signal and the intensity of the first pulse wave signal, and calculate the slope of the second regression line as second information by regression analysis using the intensity of the third pulse wave signal and the intensity of the second pulse wave signal.

　With the above configuration, the slope of the regression line is prevented from deviating from the slope of the linear equation that represents the true relationship, compared to when the absorbance ratio is calculated using only two types of light, red and infrared. This makes it possible to calculate oxygen saturation with greater accuracy.

In a third aspect, in the second aspect, the processor is configured to calculate the first regression line and the second regression line using only the least squares method.

According to the above configuration, the type of regression method used to calculate the first regression line and the second regression line is the least squares method only. Here, the calculation algorithm of principal component regression, such as orthogonal distance regression, is more complicated than the least squares method, and therefore the overall amount of calculation is greater. This causes problems such as an increase in the calculation load, such as an increase in the power consumption of the measuring device or a longer processing time. For this reason, in the present disclosure, in which only the least squares method is used, the overall amount of calculation can be reduced compared to when orthogonal distance regression or the like is used, and therefore the calculation load can be suppressed.

In addition, the wavelength of the reference light for the third pulse wave signal is a wavelength at which the absorption coefficients of oxygenated hemoglobin and reduced hemoglobin are higher than those of red light and infrared light, and therefore the signal-to-noise ratio of the light received from the artery is higher than that of red light and infrared light. Therefore, even if the least-squares method is not used to minimize the sum of the squares of the distance along the axis on the side on which the data of the third pulse wave signal is placed, the effect on the slope of the regression line caused by the data of the third pulse wave signal can be suppressed. Therefore, even if only the least-squares method is used as the regression method, the accuracy of calculating the slope can be improved compared to when the absorbance ratio of red light to infrared light is directly calculated using only two lights, red light and infrared light.

In a fourth aspect, in any of the first to third aspects, the processor continuously acquires the intensity of the first pulse wave signal, the intensity of the third pulse wave signal, and the intensity of the second pulse wave signal, calculates the average of the ratio of the intensity of the third pulse wave signal to the intensity of the first pulse wave signal as the first information, and calculates the average of the ratio of the intensity of the third pulse wave signal to the intensity of the second pulse wave signal as the second information.

With the above configuration, the oxygen saturation level can be calculated with high accuracy using the first information and the second information, both of which are average values of the ratios.

In a fifth aspect, in any of the first to fourth aspects, the processor is configured to calculate a plurality of oxygen saturations and determine one of the calculated plurality of oxygen saturations as the arterial oxygen saturation based on a preset criterion.

With the above configuration, for example, by incorporating multiple calculation methods with different characteristics, it is possible to improve the robustness of oxygen saturation measurement and further improve the measurement accuracy of oxygen saturation.

In a sixth aspect, in any of the first to fifth aspects, the processor is configured to determine, among the data of the first pulse wave signal and the data of the third pulse wave signal output by the light receiving elements, data that satisfies a threshold value that is set in advance based on the relationship between the data of the first pulse wave signal and the data of the third pulse wave signal as an outlier not related to arterial pulsation, and calculate the first information excluding the determined outlier; or, among the data of the second pulse wave signal and the data of the third pulse wave signal output by the light receiving elements, data that satisfies a threshold value that is set in advance based on the relationship between the data of the second pulse wave signal and the data of the third pulse wave signal as an outlier not related to arterial pulsation, and calculate the second information excluding the determined outlier.

The above configuration can further improve the accuracy of oxygen saturation measurement.

In a seventh aspect, the oxygen saturation measuring device in any one of the first to sixth aspects is a wearable device that can be worn by the person being measured.

The above configuration makes it possible to realize a wearable device that can be designed to have a long lifespan.

The oxygen saturation measurement method according to the eighth aspect of the present disclosure projects red light, infrared light, and reference light having a wavelength at which the absorption coefficient of oxygenated hemoglobin and the absorption coefficient of reduced hemoglobin are higher than those of red light and infrared light onto an artery, receives transmitted light or reflected light corresponding to the projected red light, infrared light, and reference light, respectively, as received light, obtains a first pulse wave signal corresponding to the intensity of the received red light, a second pulse wave signal corresponding to the intensity of the received infrared light, and a third pulse wave signal corresponding to the intensity of the received reference light, calculates first information based on the intensity of the first pulse wave signal and the intensity of the third pulse wave signal, calculates second information based on the intensity of the second pulse wave signal and the intensity of the third pulse wave signal, and measures oxygen saturation in the artery by calculating oxygen saturation based on the calculated first information and second information, respectively.

According to the eighth aspect, like the first aspect, it is possible to realize an oxygen saturation measurement method that can improve the accuracy of oxygen saturation measurement.

The oxygen saturation measurement program according to the ninth aspect of the present disclosure causes a processor to execute the following steps: projecting red light, infrared light, and reference light having a wavelength at which the absorption coefficient of oxygenated hemoglobin and the absorption coefficient of reduced hemoglobin are higher than those of red light and infrared light onto an artery; receiving transmitted light or reflected light corresponding to the projected red light, infrared light, and reference light, respectively, as received light; acquiring a first pulse wave signal corresponding to the intensity of the received red light, a second pulse wave signal corresponding to the intensity of the received infrared light, and a third pulse wave signal corresponding to the intensity of the received reference light; calculating first information based on the intensity of the first pulse wave signal and the intensity of the third pulse wave signal; calculating second information based on the intensity of the second pulse wave signal and the intensity of the third pulse wave signal; and measuring the oxygen saturation of the artery by calculating the oxygen saturation based on the calculated first information and second information, respectively.

According to the ninth aspect, like the first aspect, it is possible to realize an oxygen saturation measurement program that can improve the accuracy of oxygen saturation measurement.

The oxygen saturation measurement device, oxygen saturation measurement method, and oxygen saturation measurement program disclosed herein can improve measurement accuracy.

FIG. 1 is a perspective view illustrating an oxygen saturation measuring device according to an embodiment of the present disclosure. 2 is a cross-sectional view illustrating a sensor unit of the oxygen saturation measuring device according to the embodiment. FIG. 2 is a block diagram showing a hardware configuration of a processor of the oxygen saturation measuring device according to the present embodiment. FIG. 4 is a flowchart illustrating an oxygen saturation measuring method using the oxygen saturation measuring device according to the present embodiment. FIG. 4 is a diagram illustrating the waveform of a first pulse wave signal obtained from the reflected light of red light projected onto an artery to be measured. FIG. 13 is a diagram illustrating the waveform of a second pulse wave signal obtained from reflected light of infrared light projected onto an artery to be measured. FIG. 13 is a diagram illustrating the waveform of a third pulse wave signal obtained from reflected light of a reference light projected onto an artery to be measured. 11 is a graph illustrating a method for determining a first regression line by using the least squares method on a scatter plot of first pulse wave signal data and third pulse wave signal data in an oxygen saturation measuring method using the oxygen saturation measuring device according to the present embodiment. 13 is a graph illustrating a method for determining a second regression line by using the least squares method on a scatter plot of second pulse wave signal data and third pulse wave signal data in an oxygen saturation measuring method using the oxygen saturation measuring device according to this embodiment. 11 is a graph illustrating the variability in data when a regression line is obtained by using the least squares method on a scatter plot of first pulse wave signal data and second pulse wave signal data in an oxygen saturation measurement method using an oxygen saturation measurement device according to a first comparative example. 11 is a graph illustrating the variability in data when a regression line is obtained by applying the least squares method to a scatter plot of first pulse wave signal data and third pulse wave signal data in an oxygen saturation measuring method using the oxygen saturation measuring device according to this embodiment. 11 is a graph illustrating absorbance ratios calculated in an example according to the present embodiment, a first comparative example, and a second comparative example. 11 is a graph illustrating the processing time required to calculate the absorbance ratio for each of an example according to the present embodiment, a first comparative example, and a second comparative example. 13 is a graph illustrating the overlapping state of the distribution of data related to pulse and the distribution of outliers in a scatter plot in which the AC/DC of a first pulse wave signal is used as a response variable and the AC/DC of a second pulse wave signal is used as an explanatory variable. 13 is a graph illustrating the overlapping state of the distribution of data related to pulse and the distribution of outliers in a scatter plot in which the AC/DC of a first pulse wave signal is used as a response variable and the AC/DC of a third pulse wave signal is used as an explanatory variable. 13 is a graph illustrating the distribution of data related to pulsation and the distribution of outliers in a scatter plot obtained when the AC/DC of the first pulse wave signal and the AC/DC of the second pulse wave signal are sorted in order of signal strength of the third pulse wave signal.

The present embodiment will be described below. In the following description of the drawings, identical and similar parts are given the same or similar symbols. However, the drawings are schematic, and the relationship between thickness and planar dimensions, the thickness ratio of each device and each component, etc. differ from the actual ones. Therefore, specific thicknesses and dimensions should be determined with reference to the following description. Furthermore, there are parts with different dimensional relationships and ratios between the drawings. Furthermore, unless otherwise specified in the specification, the number of each component of the present disclosure is not limited to one, and there may be more than one.

<Oxygen saturation measuring device>
The structure of an oxygen saturation measuring device 10 according to this embodiment will be described with reference to Figures 1 to 3. As shown in Figure 1, the oxygen saturation measuring device 10 according to this embodiment is a portable wearable device that includes a band 12, a housing 14, a sensor unit 16, a display unit 18, and an arithmetic and control unit 20 and can be worn by a person to be measured.

Furthermore, the oxygen saturation measuring device 10 according to this embodiment is provided with a driving power source 11. The driving power source 11 may be a primary battery or a secondary battery. Note that in this disclosure, the shape of the oxygen saturation measuring device is not limited to a wearable device that can be worn by the person being measured. The oxygen saturation measuring device of this disclosure may be a portable type that can be worn or not, for example, a portable type that can be placed close to the wrist, or may be a stationary type, or may be configured in any manner.

In this specification, the "direction E in which the forearm extends" overlaps with the direction in which the radius, ulna, and artery of the person being measured extend. Furthermore, strictly speaking, the "direction E in which the forearm extends" differs for each person being measured. In other words, the "direction E in which the forearm extends" is not uniquely determined by coordinates in three-dimensional space, but is determined individually based on the direction in which the radius, ulna, and artery extend for each person being measured.

(band)
1, the band 12 is wrapped around the wrist of the person being measured along the circumferential direction C of the wrist. The band 12 may be made of any material, such as resin, fabric, metal, etc. The band 12 is also provided with a clasp for adjusting the length when wrapped around the wrist and for fixing the band 12 in place.

(Housing)
The housing 14 is attached to the band 12 and contacts the surface of the back of the wrist (i.e., the back of the hand) of the person being measured. The material of the housing 14 may be any material, such as resin or metal. The housing 14 has a certain width along the direction E in which the forearm extends. The housing 14 is provided with a sensor unit 16, a display unit 18, and a calculation control unit 20.

(Display)
1, the display unit 18 is disposed on the surface of the housing 14 opposite the wrist. The display unit 18 is an image display device formed of, for example, liquid crystal or the like. The display unit 18 displays the results of the calculation by the calculation control unit 20 to the outside so that the result can be visually recognized by the subject. The display unit 18 may be provided with a storage device for temporarily storing the measurement results.

(Sensor unit)
The sensor unit 16 is attached to the band 12. The sensor unit 16 acquires a pulse wave signal of the wrist artery and measures the oxygen saturation of the wrist artery based on the acquired pulse wave signal. The sensor unit of this embodiment faces, for example, an artery included in the dorsal carpal artery network on the dorsal side of the wrist of the person being measured. The dorsal carpal artery network includes branches from the radial artery and branches from the ulnar artery. Note that in the present disclosure, the artery to be measured is not limited to the artery in the wrist.

As shown in FIG. 2, the sensor unit 16 has a light-emitting section 16A having a first light-emitting element LED1, a second light-emitting element LED2, and a third light-emitting element LED3, and a light-receiving section 16B having a light-receiving element PD. That is, in this embodiment, one "sensor unit" is composed of three light-emitting elements and one light-receiving element corresponding to the three light-emitting elements. Note that in this disclosure, multiple sensor units may be provided. Also, the number of light-emitting elements and the number of light-receiving elements included in one "sensor unit" can both be set arbitrarily.

An opening 14A is formed between the light-emitting section 16A in the housing 14 and the outside. An optical device 15A that is translucent to the light emitted from the light-emitting element is disposed in the opening 14A. The optical device 15A is, for example, a diffusion lens that can expand the irradiation area. Although not shown, a diffusion agent may be disposed above the light-emitting element together with or instead of the diffusion lens.

In addition, an opening 14B is formed between the light receiving unit 16B in the housing 14 and the outside. An optical device 15B that is translucent to light reflected from the artery in the wrist is disposed in the opening 14B. The optical device 15B is, for example, a focusing lens that can collect the reflected light. Note that in this disclosure, the optical devices 15A and 15B are not essential.

(Light Emitting Element)
The first light-emitting element LED1, the second light-emitting element LED2, and the third light-emitting element LED3 are all electronic components such as light-emitting diodes (LEDs). Each light-emitting element irradiates light onto the artery in the wrist. The first light-emitting element LED1, the second light-emitting element LED2, and the third light-emitting element LED3 are disposed apart from each other. In the present disclosure, the number of each of the first light-emitting element, the second light-emitting element, and the third light-emitting element is one or more and is arbitrary.

(First Light-Emitting Element and Second Light-Emitting Element)
The first light-emitting element LED1 projects red light onto the artery. The second light-emitting element LED2 projects infrared light onto the artery. In Fig. 2, a wavelength λ1 of red light is illustrated inside the first light-emitting element LED1, and a wavelength λ2 of infrared light is illustrated inside the second light-emitting element LED2. From the viewpoint of improving measurement accuracy, it is preferable that the first light-emitting element LED1 and the second light-emitting element LED2 are arranged so that the optical paths of the light projected by each of them are as close to the same as possible.

(Red and infrared light)
In the measurement of oxygen saturation, it is necessary to use a combination of two wavelength bands with different absorption coefficients for oxygenated hemoglobin and reduced hemoglobin. A preferred combination of wavelength bands is a red region having a wavelength band of approximately 590 nm or more and 770 nm or less, and an infrared region having a wavelength band of approximately 770 nm or more and 1000 nm or less.

In particular, to measure oxygen saturation with high accuracy, it is desirable for the difference between the absorption coefficient of oxyhemoglobin and the absorption coefficient of reduced hemoglobin to be large. For this reason, it is preferable that the peak wavelength of the red light is in the range of 640 nm to 660 nm, and the peak wavelength of the infrared light is approximately 940 nm. In this embodiment, the red light and the infrared light are projected intermittently in time, for example, once during one pulsation of the artery.

(Third Light-Emitting Element)
The third light-emitting element LED3 projects a reference light. The reference light has a wavelength that has a higher signal-to-noise ratio than red light and infrared light for the artery. In FIG. 2, a wavelength λ3 of the reference light is illustrated inside the third light-emitting element LED3. In this embodiment, the reference light is projected continuously in time, for example, 10 or 20 times during one pulsation of the artery.

(Reference light)
The reference light has a wavelength at which the absorption coefficient of oxygenated hemoglobin and the absorption coefficient of reduced hemoglobin are higher than those of red light and infrared light. In this embodiment, the signal-to-noise ratio of the pulse wave signal of the received light corresponding to the reference light obtained by photoplethysmography (PPG) is higher than both the signal-to-noise ratio of red light and the signal-to-noise ratio of infrared light. As the reference light, for example, light in a wavelength band of 430 nm or more and 590 nm or less, which has a relatively large absorption coefficient in arterial blood, is preferable. Specifically, a blue region with a wavelength band of 430 nm or more and 490 nm or less, or a green region with a wavelength band of 490 nm or more and 550 nm or less is preferable.

In this embodiment, green light with a peak wavelength of 530 nm or more and 540 nm or less is particularly preferred in that it is easily absorbed by hemoglobin in the blood and easily captures changes in the volume of arterial blood vessels, thereby obtaining a pulse wave signal with a relatively high signal-to-noise ratio. In addition, LED light sources in the green light wavelength band are highly available on the market and relatively inexpensive, making them advantageous as the third light-emitting element that irradiates the reference light. Note that in this disclosure, light sources in the violet and ultraviolet wavelength bands of 430 nm or less are not excluded as light sources of the reference light.

In addition, in this disclosure, the reference light is not limited to green light. In this disclosure, light in any band that can be taken from the hemoglobin absorption spectrum can be used as the reference light, as long as the absorption coefficient of oxygenated hemoglobin and the absorption coefficient of reduced hemoglobin are higher than those of red light and infrared light.

(Light receiving element)
The light receiving element PD is an electronic component such as a photodiode (PD). The light receiving element PD is disposed at a preset position relative to the light emitting element. In this embodiment, the number of the light receiving elements PD is one, but in the present disclosure, the number of the light receiving elements may be multiple.

The light receiving element PD receives reflected light corresponding to red light and outputs a first pulse wave signal according to the light intensity of the received reflected light. The light receiving element PD also receives reflected light corresponding to infrared light and outputs a second pulse wave signal according to the light intensity of the received reflected light. The light receiving element PD also receives reflected light corresponding to the reference light and outputs a third pulse wave signal according to the light intensity of the received reflected light. To specifically measure oxygen saturation, two types of reflected light, red light and infrared light, received by the light receiving element are used.

In addition, in the present disclosure, the light receiving element is not limited to the reflected light of each of the red light, infrared light, and reference light, but may receive transmitted light corresponding to each of the lights and output a pulse wave signal according to the light intensity of the received transmitted light. That is, the oxygen saturation measuring device 10 according to the present embodiment is a reflective type in which the intensity of the pulse wave signal is measured by reflected light, but in the present disclosure, it is not limited to the reflective type, and a transmissive oxygen saturation measuring device in which the intensity of the pulse wave signal is measured by transmitted light may be configured.

Although not shown in the figure, a light-shielding section may be provided between the light-emitting element and the light-receiving element. The light-shielding section prevents the light-receiving element from directly receiving light from the light-emitting element.

(Oxygen saturation measurement principle)
Here, the principle of measuring oxygen saturation when the absorbance ratio is calculated using only two lights, red light and infrared light, will be described. Specifically, the change in the intensity of each of the first pulse wave signal of red light and the second pulse wave signal of infrared light is monitored over time. Then, the data of the first pulse wave signal and the data of the second pulse wave signal corresponding to each other over time are plotted on the XY coordinate axis to calculate a scatter diagram of the data. For example, the data value of the second pulse wave signal can be placed on the X axis as an explanatory variable, and the data value of the first pulse wave signal can be placed on the Y axis as a response variable.

Then, a regression line is obtained by performing a regression process on the data included in the scatter plot. The slope of the obtained regression line corresponds to the ratio of the absorbance of red light (AC/DC) to the absorbance of infrared light (AC/DC), i.e., the absorbance ratio Φ. The absorbance of each light (AC/DC) is the ratio of the variable component AC to the fixed component DC of the pulse wave signal. The calculated absorbance ratio Φ can then be used in the following formula (1) to calculate oxygen saturation.

Oxygen saturation [%] = a × Φ + b ... formula (1)

The coefficients a and b in the formula (1) can be determined by experiment.

(Calculation control unit)
In this embodiment, the calculation and control unit 20 is provided in the housing 14. The processor is electrically connected to the first light-emitting element, the second light-emitting element, the third light-emitting element, and the light-receiving element PD. Pulse wave signal data of reflected light corresponding to the light emitted from each light-emitting element is input over time from the light-receiving element PD to the calculation and control unit 20. Based on the pulse wave signal obtained from the reflected light, the calculation and control unit 20 measures the oxygen saturation of the artery irradiated with light by a method using the ratio of PI values, for example.

As shown in FIG. 3, the calculation control unit 20 has a CPU (Central Processing Unit: processor) 21, a ROM (Read Only Memory) 22, a RAM (Random Access Memory) 23, a storage 24, a user interface 25, and a communication interface 26. Each component is connected to each other so as to be able to communicate with each other via a bus 27.

The CPU 21 is a central processing unit that executes various programs and controls each part. That is, the CPU 21 reads a program from the ROM 22 or the storage 24, and executes the program using the RAM 23 as a working area. The CPU 21 controls each of the above components and performs various calculation processes according to the program recorded in the ROM 22 or the storage 24. The CPU 21 is the processor of the present disclosure.

In this embodiment, the ROM 22 or the storage 24 stores an oxygen saturation measurement program. The oxygen saturation measurement program is a calculation program for measuring oxygen saturation.

The ROM 22 stores various programs and data. The RAM 23 temporarily stores programs or data as a working area. The storage 24 is composed of a HDD (Hard Disk Drive) or SSD (Solid State Drive) and stores various programs including the operating system and various data.

The user interface 25 is an interface that is used when the subject wearing the oxygen saturation measuring device 10, which is a wearable device, uses the calculation control unit 20. The user interface 25 may include, for example, at least one of a liquid crystal display equipped with a touch panel that allows the subject to perform touch operations, a voice input receiving unit that receives voice input from the subject, and a button that can be pressed by the subject. The display unit of this embodiment is an example of the user interface 25.

The communication interface 26 is an interface that allows the calculation control unit 20 to communicate with other devices, and uses standards such as Ethernet (registered trademark), FDDI, and Wi-Fi (registered trademark).

When executing the oxygen saturation measurement program, the oxygen saturation measurement device 10 realizes various functions using the above hardware resources. The oxygen saturation measurement device 10 has a pulse wave signal acquisition unit, a regression line calculation unit, an absorbance ratio calculation unit, and an oxygen saturation measurement unit as functional configurations realized by the oxygen saturation measurement device 10. Each functional configuration is realized by the CPU 21 reading and executing the oxygen saturation measurement program stored in the ROM 22 or storage 24.

<Oxygen saturation measurement method>
Next, an example of an oxygen saturation measuring method using the oxygen saturation measuring device 10 according to this embodiment will be described with reference to FIGS.

(Pulse wave signal acquisition process)
First, as shown in step S1 in Fig. 4, the pulse wave signal acquisition unit of the processor 21 projects red light onto the artery using the first light-emitting element LED1. The processor 21 also projects infrared light onto the artery using the second light-emitting element LED2. The processor 21 also projects reference light onto the artery using the third light-emitting element LED3, the reference light having a wavelength that provides a higher signal-to-noise ratio for light reflected from the artery than the red light and infrared light.

Next, as shown in step S2 in FIG. 4, the processor 21 receives reflected light corresponding to the projected red light using the light receiving element PD. The processor 21 also receives reflected light corresponding to the projected infrared light. The processor 21 also receives reflected light corresponding to the projected reference light.

Next, as shown in step S3 in FIG. 4, the processor 21 continuously acquires a first pulse wave signal PS1 corresponding to the light intensity of the received reflected light from the light receiving element PD. The processor 21 also continuously acquires a second pulse wave signal PS2 corresponding to the light intensity of the received reflected light from the light receiving element PD. The processor 21 also continuously acquires a third pulse wave signal PS3 corresponding to the light intensity of the received reflected light from the light receiving element PD. FIG. 5A shows an example of the waveform of the acquired first pulse wave signal PS1, FIG. 5B shows an example of the waveform of the acquired second pulse wave signal PS2, and FIG. 5C shows an example of the waveform of the acquired third pulse wave signal PS3.

(Regression Line Calculation Process)
Next, as shown in step S4 of Fig. 4, the regression line calculation section of processor 21 calculates a first regression line based on the data of first pulse wave signal PS1 and the data of third pulse wave signal PS3. As shown in step S5 of Fig. 4, processor 21 calculates a second regression line based on the data of second pulse wave signal PS2 and the data of third pulse wave signal PS3.

Specifically, as shown in FIG. 6, the processor 21 arranges the data of the first pulse wave signal PS1 and the data of the third pulse wave signal PS3 on the coordinate axes. In this embodiment, the data of the first pulse wave signal PS1 of red light is arranged on the Y axis, and the data of the third pulse wave signal PS3 of the reference light is arranged on the X axis. The processor 21 then performs a least squares method on each arranged data, minimizing the sum of squares of the distance along the Y axis on the side on which the data of the first pulse wave signal PS1 is arranged. The first regression line is calculated by performing the least squares method as a regression analysis.

In addition, in the present disclosure, the data of the first pulse wave signal PS1 of red light may be placed on the X-axis, and the data of the third pulse wave signal PS3 of the reference light may be placed on the Y-axis. When the data of the first pulse wave signal PS1 of red light is placed on the X-axis, the first regression line is calculated by performing the least squares method that minimizes the sum of the squares of the distance along the X-axis on the side where the data of the first pulse wave signal PS1 is placed.

The processor 21 also arranges the data of the second pulse wave signal PS2 and the data of the third pulse wave signal PS3 on the coordinate axes, as shown in FIG. 7. In this embodiment, the data of the second pulse wave signal PS2 of infrared light is arranged on the Y axis, and the data of the third pulse wave signal PS3 of the reference light is arranged on the X axis. The processor 21 then performs a least squares method on each arranged data, minimizing the sum of squares of the distance along the Y axis on the side on which the data of the second pulse wave signal PS2 is arranged. The least squares method is performed as a regression analysis, and a second regression line is calculated.

In the present disclosure, the data of the second pulse wave signal PS2 of infrared light may be placed on the X-axis, and the data of the third pulse wave signal PS3 of the reference light may be placed on the Y-axis. When the data of the second pulse wave signal PS2 of infrared light is placed on the X-axis, the second regression line is calculated by performing the least squares method that minimizes the sum of the squares of the distance along the X-axis on the side where the data of the second pulse wave signal PS2 is placed.

(Regarding the slope of the regression line using the least squares method)
Here, as shown in FIG. 8, in the least squares method, when there is variation in variables on both the X-axis and the Y-axis, the overall shape of the scatter diagram representing the distribution of data is an ellipse indicated by a dotted line.

The least squares method uses the least squares method that minimizes the sum of the squares of the distances along one axis, so the regression line found using the least squares method is likely to be biased toward the other axis than the line that represents the true relationship. Figure 8 shows an example where the slope of the solid regression line found using the least squares method to minimize the sum of the squares of the distances along the Y axis is more inclined toward the X axis than the slope of the dashed line of the equation for the line that represents the true relationship.

For this reason, as can be seen from the lengths of the solid and dashed double-headed arrows drawn on the lower left side of the ellipse in Figure 8, the deviation of the regression line from the straight line representing the true relationship due to the variability in the data placed on the X-axis increases. As a result, the slope of the regression line obtained using the least squares method tends to deviate from the slope of the equation of the line representing the true relationship.

On the other hand, as shown in FIG. 9, in this embodiment, data on the pulse wave signal of the received light of the reference light with a high S/N ratio is plotted on the X-axis. In other words, the variability in the pulse wave signal of the received light on the X-axis is significantly suppressed compared to the variability in the pulse wave signal of the received light on the Y-axis.

FIG. 9 illustrates an example in which the regression line, obtained by using the least squares method to minimize the sum of the squares of the distances along the axes, is nearly identical to the line representing the true relationship. The overall shape of the scatter plot representing the data distribution is a dotted parallelogram. For this reason, the variation in the data distribution formed on either side of the regression line in FIG. 9 is nearly symmetrical above and below along the Y-axis. In other words, in this embodiment, deviation from the line representing the true relationship due to variation on the X-axis is unlikely to occur.

For this reason, in this embodiment, the slope of the regression line is unlikely to deviate from the slope of the linear equation that represents the true relationship. Note that in this disclosure, the regression method for finding the regression line is not limited to the least squares method. In this disclosure, any regression method can be used, such as standard principal axis regression or Deming regression.

(First information and second information)
The slope of the first regression line in this embodiment corresponds to the "first information" of the present disclosure. The first information in this embodiment is information about the received light of red light, set based on information about the received light of the reference light. Moreover, the slope of the second regression line in this embodiment corresponds to the "second information" of the present disclosure. The second information in this embodiment is information about the received light of infrared light, set based on information about the received light of the reference light.

In this embodiment, the ratio of the second information to the first information is used as the ratio between the first information and the second information, but in this disclosure, the ratio of the first information to the second information may be used. Furthermore, in this disclosure, the first information and the second information are not limited to a regression line, i.e., a slope derived from a relational equation. The first information and the second information may be, for example, a numerical value other than a slope, a set of numerical values, or a numerical value derived from a relational equation other than a regression line.

(Equation of regression line)
Here, the elements used in calculating the regression line are set as follows:
S _red : Red light absorbance (AC/DC)
S _ir : Infrared light absorbance (AC/DC)
S _green : absorbance of green light Φ1: ratio of absorbance of red light to absorbance of green light Φ2: ratio of absorbance of infrared light to absorbance of green light b1: intercept of first regression line b2: intercept of second regression line

Therefore, as shown in FIG. 6, the equation of the first regression line is

S _red = Φ1 · S _green + b1

It can be set as follows.

As shown in FIG. 7, the equation of the second regression line is

S _ir = Φ2 · S _green + b2

It can be set as follows.

(Absorbance ratio calculation process)
4, the absorbance ratio calculation section of the processor 21 calculates the absorbance ratio of the first pulse wave signal PS1 to the second pulse wave signal PS2 based on the calculated slopes of the first and second regression lines. In other words, the absorbance ratio is found by solving the simultaneous equations of the first and second regression lines.

Specifically, when the _ratio of the absorbance S red of red light to the absorbance S _ir of infrared light is defined as the absorbance ratio Φ, the following equation is obtained.

Φ=S _red /S _ir =(Φ1·S _green +b1)/(Φ2·S _green +b2)

Here, because the intercepts b1 and b2 pass through the origin due to the linearity between the variables, it can be considered that b1 = b2 = 0. Therefore, the following equation is obtained.

Φ≈(Φ1· _Sgreen )/(Φ2· _Sgreen )=Φ1/Φ2

In other words, in this embodiment, the data of the third pulse wave signal PS3 of the reference light is included in the measurement calculation process to suppress the variation in the values of the red light absorbance and the infrared light absorbance.

(Oxygen saturation measurement process)
4, the oxygen saturation measurement unit of the processor 21 calculates the oxygen saturation of the artery based on the calculated absorbance ratio. The calculated oxygen saturation is displayed on the display unit 18 as a measurement value.

Next, as examples of this embodiment, a first analysis example and a second analysis example performed using simulation analysis will be described with reference to Figures 10 and 11.

(First analysis example)
In the first analytical example, the absorbance ratios calculated in the example according to this embodiment, the first comparative example, and the second comparative example were compared.

Specifically, a triangular wave signal for analysis was generated by simulating a pulse wave signal. The generated triangular wave signal contained random noise in the entire wavelength range, so-called white noise. As shown on the horizontal axis in Figure 10, the S/N ratios of the triangular wave signals were eight patterns: 2, 4, 8, 16, 32, 64, 128, and 256. Then, for each of the eight S/N ratio patterns, the calculation methods of the example, the first comparative example, and the second comparative example were performed to calculate the absorbance ratio Φ.

In the first and second comparative examples, no reference light was used, and the absorbance ratio Φ was calculated using only two lights, red light and infrared light. In the first comparative example, the least squares method was used on the scatter plot of the data of the first pulse wave signal of red light and the data of the second pulse wave signal of infrared light. In the second comparative example, orthogonal distance regression was used on the scatter plot of the data of the first pulse wave signal of red light and the data of the second pulse wave signal of infrared light.

As shown in Figure 10, the absorbance ratio Φ calculated in the embodiment was close to the true value for all eight S/N ratio patterns, as in the second comparative example of orthogonal distance regression. In particular, the absorbance ratio Φ in the embodiment was close to the true value, as in orthogonal distance regression, even for patterns with relatively low S/N ratios such as 2 or 4. The first analysis example showed that the embodiment can achieve the same level of measurement accuracy as orthogonal distance regression.

(Second analysis example)
In the second analysis example, the processing time required to calculate the absorbance ratio of each of the example according to the present embodiment, the first comparative example, and the second comparative example was compared. The CPU used in the second analysis example was an Intel Xeon (number of cores: 8, frequency: 2.20 GHz). The other analysis conditions in the second analysis example were the same as those in the first analysis example.

As shown in Figure 11, in the second comparative example of orthogonal distance regression, the amount of repeated calculations is greater than in the least squares method, and therefore the processing time is longer. On the other hand, the processing time required to calculate the absorbance ratio in the example was close to the true value for all eight patterns of S/N ratios, and was shorter than the second comparative example of orthogonal distance regression. In particular, the processing time in the example was less than half that of the second comparative example, even for patterns with relatively low S/N ratios such as 2, 4, or 6. The second analysis example shows that the example can achieve a processing time shorter than that of orthogonal distance regression.

(First Modification)
Next, modified examples of the oxygen saturation measuring device according to the present embodiment will be described. In the oxygen saturation measuring device according to the first modified example, in addition to the calculation means for measuring the oxygen saturation described in the present embodiment, a different calculation means capable of measuring the oxygen saturation is installed. Therefore, the processor 21 can calculate multiple oxygen saturations based on the multiple calculation means installed. In the first modified example, the processor 21 is configured to determine one oxygen saturation from the multiple calculated oxygen saturations as the arterial oxygen saturation based on a preset criterion.

Specifically, for example, the processor 21 can calculate different oxygen saturations by performing oxygen saturation measurement processes in parallel using oxygen saturation calculation means such as a method of calculation based on the maximum and/or minimum values of the pulse wave or a regression method. Of the multiple calculated oxygen saturations, one value can be determined so as to exclude, for example, an oxygen saturation that is considered to have been calculated with a larger number of outliers. In other words, the magnitude relationship of the outliers is used as a criterion.

Furthermore, from among the multiple calculated oxygen saturations, a single value may be determined so as to exclude oxygen saturations that are considered to be less accurate based on criteria such as the signal-to-noise ratio of the measured pulse wave signal or the magnitude of baseline fluctuation. Alternatively, a single value may be determined by selecting multiple oxygen saturations that are considered to be more accurate and finding the average or median value. Other criteria may include, for example, a certain range set according to actual values obtained in past measurements of the subject, and in the present disclosure, criteria can be set as appropriate.

(Second Modification)
In the oxygen saturation measuring device according to the second modification, the processor 21 is configured to calculate a first regression line by excluding outliers not related to arterial pulsation from the data of the first pulse wave signal PS1 and the data of the third pulse wave signal PS3 output by the light receiving element PD. The processor 21 also calculates a second regression line by excluding outliers not related to arterial pulsation from the data of the second pulse wave signal PS2 and the data of the third pulse wave signal PS3 output by the light receiving element PD.

Specifically, the processor 21 determines, from among the multiple data output by the light receiving element PD, data that satisfies a preset threshold as an outlier. The threshold set in the calculation of the first regression line is set based on the relationship between the data of the first pulse wave signal PS1 and the data of the third pulse wave signal PS3. Furthermore, the threshold set in the calculation of the second regression line is set based on the relationship between the data of the second pulse wave signal PS2 and the data of the third pulse wave signal PS3.

In the present embodiment, the process of calculating the regression line excluding outliers is illustrated as being executed in both the calculation of the first regression line and the calculation of the second regression line, but in the present disclosure, it is sufficient that the process is executed in the calculation of at least one of the regression lines.

(Threshold)
In this embodiment, as an example of the threshold value of the present disclosure for detecting an outlier, for example, a first threshold value and a second threshold value can be set. Note that in the present disclosure, the threshold value for detecting an outlier is not limited to the first threshold value and the second threshold value, and can be set arbitrarily.

(First threshold)
The pulse wave signal includes a fluctuating component (AC) and a fixed component (DC) that does not fluctuate. Data on the ratio of the fluctuating component to the fixed component (AC/DC) is calculated from each of the first pulse wave signal of red light and the second pulse wave signal of infrared light.

In a scatter plot of data in which the AC/DC data of the first pulse wave signal is the objective variable and the AC/DC data of the second pulse wave signal is the explanatory variable, the correlation between the AC/DC data of the first pulse wave signal and the AC/DC data of the second pulse wave signal is relatively low. For this reason, as shown in FIG. 12, the area of overlap between the distribution of data related to pulsation and the distribution of outliers due to disturbances is relatively large. As a result, it is difficult to separate the distribution of data related to pulsation and the distribution of outliers due to disturbances, i.e., it is difficult to detect outliers.

On the other hand, in a scatter plot of data in which the AC/DC data of the first pulse wave signal is the objective variable and the AC/DC data of the third pulse wave signal of the reference light is the explanatory variable, the correlation between the AC/DC data of the first pulse wave signal and the AC/DC data of the third pulse wave signal is relatively high. This makes it easier to separate the distribution of data related to pulsation from the distribution of outliers due to disturbances.

Specifically, for example, a preset index that indicates a relative distance from the distribution of data, such as the Mahalanobis distance, is set as the first threshold. For example, by setting data that is further from the reference value than the set first threshold as data that is not related to heartbeats, outliers can be easily detected. In FIG. 13, the dotted ellipse illustrates an example of a Mahalanobis distance that includes approximately 95% of all data. In this embodiment, for example, data that does not fall within the range of the ellipse in FIG. 13 can be excluded as an outlier.

(Second Threshold)
When the AC/DC data of the first pulse wave signal of red light and the AC/DC data of the second pulse wave signal of infrared light are rearranged in order of signal strength of the third pulse wave signal of reference light acquired successively in time, it is expected from the linearity of each color that the red light and infrared light will be arranged in order of signal strength.

However, as shown in FIG. 14, outliers due to disturbances do not have the linearity of red light and infrared light, and therefore even if the third pulse wave signal is sorted in order of signal strength, the difference between the expected rank and the actual rank becomes large. For this reason, a second threshold value is set to the difference between the predetermined expected rank and the actual rank. For example, by setting data whose actual rank deviates from the expected rank by more than the set second threshold value as data that is not related to heartbeats, outliers can be easily detected.

(Action and Effect)
In this embodiment, a first regression line is calculated based on the data of the first pulse wave signal PS1 and the data of the third pulse wave signal PS3, and a second regression line is calculated based on the data of the second pulse wave signal PS2 and the data of the third pulse wave signal PS3. The third pulse wave signal PS3 is a pulse wave signal corresponding to reference light having a wavelength at which the signal-to-noise ratio of light received from an artery is higher than that of red light and infrared light.

Then, the absorbance ratio of the first pulse wave signal PS1 to the second pulse wave signal PS2 is calculated based on the slope of the first regression line and the slope of the second regression line, and the arterial oxygen saturation is measured based on the calculated absorbance ratio.

In other words, in this embodiment, the wavelength of the reference light projected onto the artery is a wavelength at which the absorption coefficients of oxygenated hemoglobin and reduced hemoglobin are higher than those of red light and infrared light. Therefore, the signal-to-noise ratio of the third pulse wave signal PS3 corresponding to the reference light is higher than those of red light and infrared light. In other words, the signal-to-noise ratio of the pulse wave signal of the received light depends on the wavelength of the projected light. In the oxygen saturation calculation algorithm, a reference light is included as a third light other than the two lights of red light and infrared light. The inclusion of the reference light prevents the slope of the regression line from deviating from the slope of the linear equation that represents the true relationship, compared to when the absorbance ratio is calculated using only the two lights of red light and infrared light. Therefore, the measurement accuracy of the oxygen saturation can be improved, compared to when the absorbance ratio is calculated using only the two lights of red light and infrared light.

In this embodiment, the data of the first pulse wave signal PS1 and the data of the third pulse wave signal PS3 are arranged on the coordinate axes. The first regression line is calculated by performing the least squares method on each arranged data, which minimizes the sum of the squares of the distance along the axis on the side on which the data of the first pulse wave signal PS1 is arranged.

The data of the second pulse wave signal PS2 and the data of the third pulse wave signal PS3 are arranged on the coordinate axes. The second regression line is calculated by performing the least squares method on each arranged data, which minimizes the sum of the squares of the distances along the axis on the side on which the data of the second pulse wave signal PS2 is arranged. In other words, the only type of regression method used to calculate the first regression line and the second regression line is the least squares method.

Here, the calculation algorithm for principal component regression, such as orthogonal distance regression, is more complicated than the least squares method, and therefore the overall amount of calculation is greater. This causes problems such as an increase in the calculation load, such as an increase in the power consumption of the measuring device or a longer processing time. For this reason, in this embodiment, in which only the least squares method is used, the overall amount of calculation can be reduced compared to when orthogonal distance regression or the like is used, and therefore the calculation load can be suppressed.

In addition, in this embodiment, the first and second regression lines are first calculated by using the data of the third pulse wave signal PS3, and then the first and second regression lines are indirectly calculated using the slopes of the first and second regression lines. The wavelength of the reference light of the third pulse wave signal PS3 is a wavelength at which the absorption coefficients of oxygenated hemoglobin and reduced hemoglobin are higher than those of red light and infrared light, and therefore the signal-to-noise ratio of the light received from the artery is higher than that of red light and infrared light. Therefore, even if the least squares method is not performed to minimize the sum of squares of the distance along the axis on the side where the data of the third pulse wave signal PS3 is placed, the effect on the slope of the regression line caused by the data of the third pulse wave signal PS3 can be suppressed.

Therefore, even if only the least squares method is used as the regression method, the accuracy of the slope calculation can be improved compared to when the absorbance ratio of red light to infrared light is directly calculated using only two types of light, red light and infrared light. As a result, it is possible to improve the measurement accuracy of oxygen saturation while reducing the calculation load.

In addition, in this embodiment, as in the first modified example, one of the multiple calculated oxygen saturations is determined as the arterial oxygen saturation based on a preset criterion. By incorporating multiple calculation methods with different characteristics, it is possible to improve the robustness of the oxygen saturation measurement and further improve the measurement accuracy of the oxygen saturation.

In addition, in this embodiment, as in the second modified example, outliers that are not related to arterial pulsation are removed in the calculation of the first regression line and the second regression line, so the accuracy of measuring oxygen saturation can be further improved.

In addition, this embodiment makes it possible to realize a wearable device that can have a longer lifespan by reducing the computational load.

<Other embodiments>
Although the present disclosure has been described with reference to the above disclosed embodiments, the descriptions and drawings forming a part of this disclosure should not be construed as limiting the present disclosure.

In the present disclosure, for example, the first information may be an average value of the ratio between the intensity of the third pulse wave signal and the intensity of the first pulse wave signal. Also, the second information may be an average value of the ratio between the intensity of the third pulse wave signal and the intensity of the second pulse wave signal. Then, the oxygen saturation level may be accurately calculated based on the ratio between the first information and the second information, both of which are average values of ratios. The oxygen saturation level can be accurately calculated using the first information and the second information, both of which are average values of ratios.

Furthermore, for example, since the signal-to-noise ratio of the third pulse wave signal of the reference light is relatively higher than that of red light or infrared light, it can be used to control the emission timing of red light or infrared light. Specifically, for example, the emission timing can be synchronized with the timing at which the maximum and minimum values of the pulse wave are obtained, or the emission timing can be limited to within a certain period depending on the timing at which the maximum and minimum values are obtained. By selectively controlling the emission timing based on the timing at which the maximum and minimum values of the pulse wave are obtained, the number of times each of the first and second light-emitting elements emits light can be reduced, and as a result, low power consumption can be achieved.

Furthermore, if the saved power is returned to the emission intensity of each of the red light and the infrared light, the signal-to-noise ratio of the amplitude values of each of the first red light pulse wave signal and the second infrared light pulse wave signal can be improved. This makes it possible to selectively collect only data with a high signal-to-noise ratio of the amplitude values, thereby further improving the measurement accuracy.

Furthermore, for example, in the present disclosure, the oxygen saturation measurement process executed by the CPU 21 by reading the software (program) in the above embodiment may be executed by various processors other than the CPU. Examples of processors in this case include a PLD (Programmable Logic Device) such as an FPGA (Field-Programmable Gate Array) whose circuit configuration can be changed after manufacture, and a dedicated electrical circuit such as an ASIC (Application Specific Integrated Circuit) that is a processor having a circuit configuration designed specifically to execute a specific process.

The oxygen saturation measurement process may be executed by one of these various processors, or by a combination of two or more processors of the same or different types (e.g., multiple FPGAs, or a combination of a CPU and an FPGA, etc.). More specifically, the hardware structure of these various processors is an electric circuit that combines circuit elements such as semiconductor elements.

In addition, in each of the above embodiments, the oxygen saturation measurement program is described as being pre-stored (installed) in the ROM 22 or storage 24, but this is not limiting. The program may be provided in a form recorded on a recording medium such as a CD-ROM (Compact Disk Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), or a USB (Universal Serial Bus) memory. The program may also be downloaded from an external device via a network.

This disclosure includes various embodiments not described above, and the technical scope of this disclosure is determined solely by the invention-specific matters of the claims that are appropriate from the above explanation.

The disclosure of Japanese Patent Application No. 2022-167841, filed on October 19, 2022, is incorporated herein by reference in its entirety.

In addition, all documents, patent applications, and technical standards described in this specification are incorporated by reference into this specification to the same extent as if each individual document, patent application, and technical standard was specifically and individually indicated to be incorporated by reference.

Claims (9)

1. a sensor unit having: a first light-emitting element which projects red light onto an artery; a second light-emitting element which projects infrared light onto the artery; a third light-emitting element which projects reference light onto the artery, the reference light having a wavelength at which the absorption coefficients of oxygenated hemoglobin and reduced hemoglobin are higher than those of red light and infrared light; and a light-receiving element which receives transmitted light or reflected light corresponding to the projected red light, the infrared light, and the reference light, respectively, as received light, and outputs a first pulse wave signal corresponding to the light intensity of the received red light, a second pulse wave signal corresponding to the light intensity of the received infrared light, and a third pulse wave signal corresponding to the light intensity of the received reference light;
   a processor electrically connected to the light receiving element, the processor calculating first information based on the intensities of the first pulse wave signal and the third pulse wave signal, calculating second information based on the intensities of the second pulse wave signal and the third pulse wave signal, and calculating an oxygen saturation level based on a ratio between the first information and the second information calculated respectively, thereby measuring an oxygen saturation level of the artery;
   An oxygen saturation measuring device comprising:
2. The processor,
   acquiring the intensity of the first pulse wave signal, the intensity of the third pulse wave signal, and the intensity of the second pulse wave signal successively in time;
   calculating, as the first information, a slope of a first regression line by performing a regression analysis using the intensity of the third pulse wave signal and the intensity of the first pulse wave signal;
   calculating, as the second information, a slope of a second regression line by performing a regression analysis using the intensity of the third pulse wave signal and the intensity of the second pulse wave signal;
   The oxygen saturation measuring device according to claim 1 , configured as follows:
3. The processor,
   Calculating the first regression line and the second regression line only by the least squares method;
   The oxygen saturation measuring device according to claim 2 , configured as follows:
4. The processor,
   acquiring the intensity of the first pulse wave signal, the intensity of the third pulse wave signal, and the intensity of the second pulse wave signal successively in time;
   calculating an average value of a ratio of an intensity of the third pulse wave signal to an intensity of the first pulse wave signal as the first information;
   an average value of a ratio of an intensity of the third pulse wave signal to an intensity of the second pulse wave signal is calculated as the second information.
   The oxygen saturation measuring device according to claim 1 , configured as follows:
5. The processor calculates a plurality of oxygen saturation levels;
   determining one of the calculated oxygen saturations as the oxygen saturation of the artery based on a preset criterion;
   The oxygen saturation measuring device according to any one of claims 1 to 4, configured as described above.
6. The processor,
   Among the first pulse wave signal and the third pulse wave signal outputted by the light receiving element,
   determining, as an outlier not related to the pulsation of the artery, data that satisfies a preset threshold based on a relationship between the first pulse wave signal and the third pulse wave signal;
   Calculating the first information excluding the determined outlier.
   Or,
   Among the second pulse wave signal and the third pulse wave signal outputted by the light receiving element,
   determining, as an outlier not related to the pulsation of the artery, data that satisfies a preset threshold based on a relationship between the second pulse wave signal and the third pulse wave signal;
   Calculating the second information excluding the determined outlier.
   The oxygen saturation measuring device according to any one of claims 1 to 4, configured as described above.
7. It is a wearable device that can be worn by the person being measured.
   The oxygen saturation measuring device according to any one of claims 1 to 4.
8. projecting red light, infrared light, and reference light having wavelengths at which the absorption coefficients of oxygenated hemoglobin and reduced hemoglobin are higher than those of the red light and the infrared light onto the artery;
   receiving, as received light, transmitted light or reflected light corresponding to the projected red light, the infrared light, and the reference light, respectively;
   obtaining a first pulse wave signal corresponding to the intensity of the received red light, a second pulse wave signal corresponding to the intensity of the received infrared light, and a third pulse wave signal corresponding to the intensity of the received reference light;
   calculating first information based on the intensity of the first pulse wave signal and the intensity of the third pulse wave signal;
   calculating second information based on the intensity of the second pulse wave signal and the intensity of the third pulse wave signal;
   measuring the oxygen saturation of the artery by calculating an oxygen saturation based on a ratio between the first information and the second information calculated respectively;
   Oxygen saturation measurement method.
9. a process of projecting red light, infrared light, and reference light having wavelengths at which the absorption coefficients of oxygenated hemoglobin and reduced hemoglobin are higher than those of the red light and the infrared light onto the artery;
   A process of receiving transmitted light or reflected light corresponding to the projected red light, the projected infrared light, and the projected reference light as received light;
   acquiring a first pulse wave signal corresponding to the intensity of the received red light, a second pulse wave signal corresponding to the intensity of the received infrared light, and a third pulse wave signal corresponding to the intensity of the received reference light;
   calculating first information based on the intensity of the first pulse wave signal and the intensity of the third pulse wave signal;
   calculating second information based on the intensity of the second pulse wave signal and the intensity of the third pulse wave signal;
   measuring the oxygen saturation of the artery by calculating the oxygen saturation based on a ratio between the first information and the second information calculated respectively;
   The oxygen saturation measurement program causes the processor to execute the following: