BLOOD PRESSURE ESTIMATION METHOD AND BIOLOGICAL INFORMATION MEASURING SYSTEM

Abstract

A biological information measurement system (10) is allowed to perform: a step for acquiring a photoplethysmographic signal (53) of a peripheral blood vessel in a user who is a subject by means of a photoplethysmography sensor (211); a step for calculating a peripheral blood pressure index that is a measure for the level of the blood pressure of a peripheral capillary blood vessel or an arteriole on the basis of the steepness of the rising of the photoplethysmographic signal (53); and a step for estimating the level of the blood pressure of the user by employing the peripheral blood pressure index and a de time that indicates the peak time difference between d wave and e wave in an accelerated photoplethysmogram signal (52) that is determined by the second-order differentiation of the photoplethysmographic signal (53).

Description

[Technical field]

[0001] The present invention relates to a blood pressure estimation method for estimating the blood pressure of a subject (user) and a biological information measuring system. [Background technology]

[0002] Pulse waves propagating in the user's arteries are used as an index for estimating the health condition of a user. The pulse waves change according to changes in the user's blood pressure at the measurement location. Patent Document 1 shows a pulse wave measuring device for measuring blood pressure with low burden on the living body. The pulse wave measuring device described in Patent Document 1 estimates blood pressure information of a living body based on the pulse rate of the living body and time information of the pulse wave of the living body. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2015 / 098977 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the estimation of blood pressure information in the pulse wave measuring device described in Patent Document 1 uses the pulse rate of the living body. The correlation between the pulse rate of the living body and blood pressure is not very high. For this reason, the estimation of blood pressure information in the pulse wave measuring device described in Patent Document 1 cannot be performed with high accuracy.

[0005] An object of the present invention is to provide a blood pressure estimation method and a biological information measurement system that can non-invasively estimate blood pressure information of a subject with high accuracy. [Means for solving the problem]

[0006] For this purpose, the present invention provides acquiring a photoplethysmographic signal of a peripheral blood vessel of the subject using a photoplethysmographic sensor; calculating a peripheral blood pressure index, which is an index of blood pressure in peripheral capillaries or arterioles, based on the steepness of the rise of the photoplethysmographic signal; a step of estimating the blood pressure of the subject using the peak time difference between the d wave and the e wave in the accelerated plethysmogram signal obtained by second-order differentiation of the photoplethysmogram signal, and a peripheral blood pressure index; A blood pressure estimation method is configured to execute the above by a vital sign measurement system. Also, a sensing device having a photoplethysmographic sensor for acquiring a photoplethysmographic signal from a peripheral blood vessel of the subject; A computer having a signal processing device that calculates a peripheral blood pressure index, which is an index of the blood pressure of the peripheral capillaries or arterioles, based on the steepness of the rise of the photoelectric pulse wave signal, and estimates the blood pressure of the subject using the de time, which is the peak time difference between the d wave and the e wave in the accelerated pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal, and the peripheral blood pressure index. A biological information measuring system comprising the above components was constructed.

[0007] According to this configuration, a photoelectric pulse wave signal of a subject's peripheral capillaries or arterioles is acquired by a photoelectric pulse wave sensor, and a peripheral blood pressure index, which is an index of the blood pressure of the subject's peripheral capillaries or arterioles, is calculated based on the steepness of the rise of the acquired photoelectric pulse wave signal. The subject's blood pressure is estimated using the calculated peripheral blood pressure index and the de time of the accelerated pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal. The peripheral blood pressure index and the de time used to estimate blood pressure each have a strong correlation with blood pressure. Effect of the Invention

[0008] Therefore, according to the present invention, it is possible to provide a blood pressure estimation method and a biological information measurement system that can non-invasively estimate blood pressure information of a subject with high accuracy. [Brief description of the drawings]

[0009] [Figure 1] 1 is an explanatory diagram showing a configuration of a biological information measuring system according to an embodiment of the present invention; [Diagram 2] 1 is an explanatory diagram showing an external configuration of a sensing device according to an embodiment of the present invention; [Diagram 3] 1 is an explanatory diagram showing an example of a posture of a user when measuring biological information; [Figure 4] FIG. 2 is an explanatory diagram illustrating the acquisition of a photoplethysmographic signal by a sensing device according to one embodiment of the present invention. [Diagram 5] 11 is a graph illustrating the maximum amplitude value of a photoplethysmographic signal. [Figure 6] 1 is a first graph illustrating each waveform element required for calculating a pulse wave feature amount that serves as a peripheral blood pressure index. [Figure 7] 11 is a second graph illustrating each waveform element required for calculating a pulse wave feature amount serving as a peripheral blood pressure index. [Figure 8] 13 is a graph showing the correlation between the steepness of the rising edge of a photoelectric pulse wave signal and each pulse wave feature amount. [Figure 9] 13 is a graph showing the results of calculating the relationship between systolic blood pressure and each of the pulse wave feature quantities 1 / VE0.5, a / S, and (ab) / (ad) from each photoplethysmographic signal measured with green light and near-infrared light when the height of the measurement site is changed and when the vicinity of the measurement site is cooled. [Figure 10] 13 is a graph showing the relationship between the pulse wave feature value 1 / VE0.5 and wrist systolic blood pressure of a diabetic patient and a healthy subject, calculated from each photoplethysmographic signal measured using green light and near-infrared light. [Figure 11] 13 is a graph showing the relationship between the pulse wave feature quantities ab time and bd time and wrist systolic blood pressure of a diabetic patient and a healthy subject, calculated from photoplethysmographic signals measured with green light and near-infrared light. [Figure 12] 13 is a graph showing the relationship between the pulse wave feature quantities de time and ae time and wrist systolic blood pressure of a diabetic patient and a healthy subject, calculated from each photoplethysmographic signal measured with green light and near-infrared light, as well as the relationship between the pulse interval and wrist systolic blood pressure. [Figure 13]1 is a graph showing the relationship between the pulse wave feature (ab) / (ad) and wrist systolic blood pressure of a diabetic patient and a healthy subject, calculated from each photoplethysmographic signal measured with green light and near-infrared light. [Figure 14] 13 is a graph showing the relationship between the pulse wave feature value a / S and the wrist systolic blood pressure of a diabetic patient and a healthy subject, calculated from each photoplethysmographic signal measured with green light and near-infrared light. [Figure 15] This is a graph showing the distribution of the relationship between blood pressure index values ​​calculated for diabetic patients and healthy subjects from a blood pressure index-based equation using the pulse wave feature value 1 / VE0.5 and de time measured from green light and near-infrared light, and wrist systolic blood pressure, and the correlation between the blood pressure index values ​​calculated from the same blood pressure index-based equation and wrist systolic blood pressure. [Figure 16] This is a graph showing the distribution of the relationship of each blood pressure index value calculated for diabetic patients and healthy subjects to wrist systolic blood pressure using a blood pressure index based formula using a pulse wave feature amount 1 / VE0.5 and de time measured using green light, and a blood pressure index based formula using a pulse wave feature amount 1 / VE0.5 and de time measured using near-infrared light, and the correlation between the blood pressure index values ​​calculated from each of these blood pressure index based formulas and the wrist systolic blood pressure. [Figure 17] This graph shows the relationship between each blood pressure index value calculated from a blood pressure index-based formula using the pulse wave feature 1 / VE0.5 and de time measured from green light and near-infrared light and the systolic blood pressure at the wrist when the height of the measurement site from the heart is changed, and the correlation between the blood pressure index value calculated from the same blood pressure index-based formula and the systolic blood pressure at the wrist when the height of the measurement site is standardized to the height of the heart. [Figure 18] 13 is a graph showing the relationship between the pulse wave feature 1 / VE0.5 measured using green light and the systolic blood pressure at the wrist when the height of the measurement site from the heart is changed, and the relationship between the de time measured using near-infrared light and the systolic blood pressure at the wrist. [Figure 19] This is a graph showing the correlation between the blood pressure reduction index value calculated for diabetic patients and healthy subjects from a blood pressure reduction index formula using the pulse wave feature amount 1 / VE0.5 and de time measured using green light and near-infrared light, and the systolic blood pressure at the wrist. [Figure 20] This is a graph showing the distribution of the relationship between the diastolic blood pressure index values ​​calculated for diabetic patients and healthy subjects from a diastolic blood pressure index-based equation using the pulse wave feature value 1 / VE0.5 and de time measured from green light and near-infrared light, and the diastolic blood pressure at the wrist, and the correlation between the diastolic blood pressure index values ​​calculated from the same diastolic blood pressure index-based equation and the diastolic blood pressure at the wrist. [Figure 21] This is a graph showing the distribution of the relationship between the diastolic blood pressure index values ​​calculated for diabetic patients and healthy subjects from a diastolic blood pressure index-based formula using the pulse wave feature value 1 / VE0.5, de time, and ae time measured from green light and near-infrared light, and the diastolic blood pressure at the wrist, and the correlation between the diastolic blood pressure index values ​​calculated from the same diastolic blood pressure index-based formula and the diastolic blood pressure at the wrist. [Figure 22] 1 is a flowchart showing a process flow of a blood pressure estimation method according to one embodiment of the present invention. [Figure 23] 1A to 1C are diagrams illustrating an imaging situation in a first method for estimating the height of a measurement site from the heart from an image of a user captured by an imaging device. [Figure 24] 13A and 13B are diagrams illustrating an imaging situation in a second method for estimating the height of a measurement site from the heart from an image of a user captured by an imaging device. [Diagram 25] 13A and 13B are diagrams illustrating example images in a second method for estimating the height of a measurement site from the heart from an image of a user captured by an imaging device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Here, the same reference numerals denote the same components, and duplicated explanations will be omitted.

[0011] 1 is an explanatory diagram showing the configuration of a biological information measurement system 10 according to an embodiment of the present invention. The biological information measurement system 10 includes a sensing device 20 that measures biological information of a user who is a subject, and a computer 30 that is configured to be able to communicate with the sensing device 20.

[0012] The sensing device 20 is, for example, a wearable device having a structure that can be attached to a peripheral part (for example, a finger) of a user. The sensing device 20 includes a biosensor 21 that measures bioinformation from the peripheral part (for example, a finger) of the user, a control circuit 22 that controls the operation of the biosensor 21, a communication module 23 that transmits the measurement results of the sensing device 20 to a computer 30 via a wireless or wired line, and an acceleration sensor 24 that measures the movement acceleration of the sensing device 20.

[0013] The biosensor 21 includes, for example, a photoelectric pulse wave sensor 211 that measures an index value indicating the peripheral blood pressure of the user. In the present invention, peripheral blood pressure is defined as the blood pressure of peripheral capillaries and arterioles. In the present invention, an index indicating the blood pressure in arterioles and capillaries, particularly in capillaries, is called a peripheral blood pressure index. Here, an arteriole is a thin artery with a diameter of, for example, about 20 to 200 μm, and is a blood vessel that exists between an artery and a capillary. In addition, a capillary is a thin blood vessel with a diameter of, for example, about 10 μm, and is a blood vessel that connects an artery and a vein.

[0014] Peripheral blood pressure may be used to mean the blood pressure at the wrist or ankle measured with a cuff-type sphygmomanometer, but in that case it is a measurement in a large artery (such as the radial artery) and is different from the blood pressure in the arterioles and capillaries in the present invention. The blood pressure in a large artery is generally the blood pressure measured with a cuff-type sphygmomanometer, and the blood pressure in the blood vessels decreases as it progresses from the artery to the arterioles and capillaries. The degree of the blood pressure drop varies depending on the measurement site, the individual's vascular condition (such as arteriosclerosis), mental state (such as the autonomic nervous system state), environment (temperature, noise, etc.), clothing, etc.

[0015] The following two points (1) and (2) are expected to be characteristics of peripheral blood pressure indicators. (1) When blood vessels are healthy, and vascular resistance does not change, the peripheral blood pressure index (upper arm or wrist) It is roughly proportional to blood pressure. (2) When the blood vessels are constricted by cooling the area near the measurement site, the peripheral blood pressure index decreases. This means that peripheral vascular resistance increases, so blood pressure in the upper arm and wrist may increase.

[0016] Photoplethysmographic sensor 211 is equipped with three LEDs as light sources, and measures photoplethysmographic signals at three wavelengths (green, red, and near-infrared). Oxygenated hemoglobin is present in arterial blood, and has the property of absorbing incident light. Therefore, photoplethysmographic signals can be measured by sensing the blood flow rate (change in blood vessel volume) that changes with the beating of the heart in a time series manner. The red LED is installed for calculating oxygen saturation, and is not essential for extracting peripheral blood pressure indexes. Photoplethysmographic sensor 211 is equipped with a photodiode (PD) as a light receiving element, and the three LEDs are sequentially made to emit light in a time-division manner and irradiate the skin of the finger with light, and the light that is reflected and scattered and returned is received by the PD.

[0017] The communication module 23 transmits the measurement results of the sensing device 20 (e.g., the photoplethysmographic signal measured by the photoplethysmographic sensor 211 and the acceleration of the sensing device 20 measured by the acceleration sensor 24) to the computer 30 via a wireless or wired line.

[0018] The acceleration sensor 24 measures the movement acceleration of the sensing device 20 when the user changes his / her posture to measure the pulse wave signal. The acceleration sensor 24 is a three-axis acceleration sensor that detects the direction of gravitational acceleration, and its detection signal is used to estimate the height at which the user wears the sensing device 20, the position at which the user wears the sensing device 20 (e.g., the position of the user's heart), and the posture of the user, such as a standing posture (standing position), a sitting posture (sitting position), or a posture lying on one's back (supine position).

[0019] The computer 30 is, for example, a multi-function mobile phone called a smartphone or a general-purpose computer (for example, a notebook computer, a desktop computer, a tablet terminal, a server computer, etc.). The computer 30 includes a communication module 31 that receives the measurement result of the biosensor 21 from the sensing device 20 via a wireless line or a wired line, and a signal processing device 32 that performs processing to estimate the user's bioinformation from the measurement result of the biosensor 21. The signal processing device 32 includes a processor 321, a memory 322, and an input / output interface 323.

[0020] The signal processing device 32 performs first-order differentiation (velocity pulse wave) and second-order differentiation (acceleration pulse wave) of two photoelectric pulse waves (volume pulse wave) measured by the green LED and near-infrared LED, and calculates pulse wave feature values ​​by dividing each of them into beat-by-beat values. Then, the peripheral blood pressure index is calculated based on the pulse wave feature values. Furthermore, the signal processing device 32 estimates the height of the part of the body where the user is wearing the sensing device 20 and the user's posture based on the signal from the acceleration sensor 24.

[0021] FIG. 2 is an explanatory diagram showing the external configuration of a sensing device 20 according to an embodiment of the present invention. The photoplethysmogram may be measured on the wrist, neck, face, ear, etc., but the finger is preferable. The reason for this is that the skin of the finger is relatively thin, making it easy to measure the photoplethysmogram, and the capillary pathway is not complicated compared to the face, etc., so that the value of each feature amount is likely to be stable. A ring-type wearable device equipped with an optical sensor and worn on a finger is preferable as a device for measuring the photoplethysmogram. This is because, when the device is continuously and intermittently measured, there is little discomfort or discomfort even when worn for a long period of time. However, the device is not limited to the finger, and the wearable device may be a wristband type worn on the wrist, a watch type, an earphone type worn on the ear, a patch type attached to the skin, or a neckband type worn on the neck. In addition, the device does not have to be a wearable device, and may be a portable or installed type such as a smartphone, and may be configured to measure by placing a finger on the sensor.

[0022] In this embodiment, the sensing device 20 includes a ring-shaped housing 25 configured to be wearable on a user's finger. For example, in the example shown in FIG. 2, the housing 25 has a hollow cylindrical shape. When the sensing device 20 is worn on a user's finger, the biosensor 21 is attached to the inner peripheral surface of the housing 25 (the inner surface of the hollow cylinder) so that the pad of the user's finger faces the biosensor 21. The shape of the housing 25 is not limited to a hollow cylindrical shape, and may be, for example, a cylindrical shape that fits on the user's finger (for example, the shape of a finger cot), and may or may not have a bottom of the cylinder (a portion that the fingertip abuts against).

[0023] 3 is an example of the posture of the user 40 when the biometric information is measured. In this example, the user 40 has the finger on which the sensing device 20 is attached resting at the position of the heart 41, and the sensing device 20 measures the biometric information from the finger of the user 40. Note that the position (measurement position) of the sensing device 20 when measuring the biometric information is not limited to the position of the chest (heart) 41 of the user 40, but may be the position of the face (forehead) or the position of the abdomen (navel) of the user 40. Furthermore, the posture of the user 40 when measuring the biometric information may be a sitting position or a supine position.

[0024] Acquisition of a photoplethysmographic signal by biosensor 21 will now be described with reference to Fig. 4. Fig. 4 is a schematic cross-sectional view of biosensor 21 attached adjacent to body surface S of a user.

[0025] The biosensor 21 has light-emitting elements 211a and 211b and a light-receiving element 211c. The biosensor 21 irradiates light onto the body surface S and receives light absorbed or reflected by the user's epidermal area EP, a plurality of capillaries CA, and an arteriole AR from which each capillary CA branches. In this embodiment, a case will be described in which one light-receiving element 211c is provided for the light-emitting element 211a, which is the first light source, and the light-emitting element 211b, which is the second light source. Note that a light-receiving element may be provided for each of the light-emitting elements 211a and 211b.

[0026] The light emitting element 211a, which is the first light source, is preferably an LED or laser having a wavelength in the vicinity of blue to yellow-green (preferably a wavelength in the vicinity of 500 to 550 nm), and is a green LED in this embodiment. The light emitting element 211b, which is the second light source, is preferably an LED or laser having a wavelength in the vicinity of red to near infrared (preferably a wavelength in the vicinity of 750 to 950 nm), and is a near infrared LED in this embodiment. The light emitting element 211a irradiates light in a wavelength range that is strongly absorbed in the living body, and the light emitting element 211b irradiates light in a wavelength range that is relatively weakly absorbed in the living body. In the following description, the light emitting element 211a is described as a green LED 211a, and the light emitting element 211b is described as a near infrared LED 211b. The light receiving element 211c uses a photodiode (PD) or a phototransistor. A Si photodiode is preferable.

[0027] The green LED 211a is provided at a position closer to the light receiving element 211c than the near-infrared LED 211b. For example, it is preferable that the distance between the green LED 211a and the light receiving element 211c is about 1 to 3 mm, and the distance between the near-infrared LED 211b and the light receiving element 211c is about 5 to 20 mm. By providing the green LED 211a at a position closer to the light receiving element 211c than the near-infrared LED 211b, the light receiving signal based on the light from the green LED 211a can include more information on the shallow area of ​​the skin than the light receiving signal based on the light from the near-infrared LED 211b.

[0028] The light emitted from the green LED 211a is absorbed by the user's epidermal area EP and the capillaries CA on the epidermal area EP side, and the transmitted light or reflected light is detected by the light receiving element 211c. The light emitted from the near-infrared LED 211b is absorbed by the user's epidermal area EP, the capillaries CA, and the arterioles AR located inside the epidermal area EP, and is detected by the light receiving element 211c. In Fig. 4, the light from the green LED 211a is shown as light along an optical path P1, and the light from the near-infrared LED 211b is shown as light along an optical path P2.

[0029] The graph in Figure 5 shows accelerated pulse wave signal 52 obtained by second-order differentiation of photoelectric pulse wave (photoelectric volume pulse wave) signal 53. The horizontal axis of the graph represents time [sec], and the vertical axis represents the signal strength of accelerated pulse wave signal 52 and photoelectric pulse wave signal 53. As shown in the figure, photoelectric pulse wave signal 53 is obtained by connecting the minimum points with a straight line and correcting the slope so that the slope of the line becomes zero, and the height of the maximum point is taken as the pulse wave height (maximum amplitude value) S.

[0030] As shown in the graph of FIG. 6, the waveform width at half the maximum peak value of velocity pulse wave signal 51 obtained by first-order differentiation of photoelectric pulse wave signal 53 is called VE0.5. The horizontal axis of the graph represents time [sec], and the vertical axis represents the signal strength of the velocity pulse wave signal 51, the acceleration pulse wave signal 52, and the photoelectric pulse wave signal 53. The velocity pulse wave signal 51 and the acceleration pulse wave signal 52 are normalized so that their maximum values ​​are set to 1. The peaks (maximum peaks and minimum peaks) of the acceleration pulse wave signal 52 are called a-wave, b-wave, c-wave, d-wave, and e-wave, respectively, as shown in the figure. The a-wave, c-wave, and e-wave have peaks that are convex on the positive side, and the b-wave and d-wave have peaks that are convex on the negative side. The difference between the d-wave peak time and the e-wave peak time is called de time. The signal strengths of the peak apex of each of the a-wave, b-wave, c-wave, d-wave, and e-wave are called a, b, c, d, and e. As shown in the graph of FIG. 7, the peak difference between the a-wave and the b-wave of the acceleration pulse wave signal 52 is called ab, and the peak difference between the a-wave and the d-wave is called ad. The horizontal and vertical axes of this graph are the same as those of the graph in FIG.

[0031] Pulse wave characteristics that show the above characteristic (1) that peripheral blood pressure index is roughly proportional to blood pressure at the upper arm or wrist The following three pieces were extracted: 1 / VE0.5 a / S (ab) / (ad)

[0032] These pulse wave feature quantities are related to the steepness of the rising edge of the waveform of photoelectric pulse wave signal 53, as shown in Fig. 8. Fig. 8(a) is a graph showing two photoelectric pulse wave signals 53a and 53b which differ in the steepness of the rising edge of the photoelectric pulse wave waveform. The horizontal axis of the graph is time [sec], and the vertical axis is the signal strength of photoelectric pulse wave signal 53. Of these two photoelectric pulse wave signals 53a and 53b, it can be seen that photoelectric pulse wave signal 53a shown by the solid line has a steeper rising edge (greater slope) than photoelectric pulse wave signal 53b shown by the dashed line.

[0033] The graph in FIG. 8(b) shows the change in each value of the pulse wave feature quantity 1 / VE0.5 and the pulse wave feature quantity a / S due to the difference in the slope of the photoelectric pulse wave signals 53a and 53b. The horizontal axis represents the values ​​of the pulse wave feature quantity 1 / VE0.5 and the pulse wave feature quantity a / S, and the horizontal axis represents the light with a small slope. The graph shows that the pulse wave feature quantity 1 / VE0.5 and the pulse wave feature quantity a / S are both photoelectric pulse wave signals with steep slopes. It can be seen that the pulse wave feature amounts for photoelectric pulse wave signal 53a are larger than the pulse wave feature amounts for photoelectric pulse wave signal 53b, which has a smaller slope.

[0034] The graph in Fig. 8(c) shows the change in each value of the pulse wave feature quantity (ab) / (ad) and the pulse wave feature quantity 1 / ab time due to the difference in the slope of the photoelectric pulse wave signals 53a and 53b. The vertical axis of the graph represents each value of the pulse wave feature quantity (ab) / (ad) and the pulse wave feature quantity 1 / ab time, and the horizontal axis is divided into photoelectric pulse wave signal 53b with a small slope and photoelectric pulse wave signal 53a with a large slope. It can be seen from the graph that the pulse wave feature quantity (ab) / (ad) and the pulse wave feature quantity 1 / ab time of the photoelectric pulse wave signal 53a with a large slope are larger than the pulse wave feature quantity of the photoelectric pulse wave signal 53b with a small slope.

[0035] Therefore, the three pulse wave features listed above, 1 / VE0.5, a / S and (ab) / It can be seen that (ad) is related to the steepness of the rising edge of the photoelectric pulse waveform. In other words, the steepness of the rising edge of the photoelectric pulse waveform can be expressed by these pulse wave feature quantities, and these pulse wave feature quantities are assumed to be pulse wave feature quantities that indicate the characteristic (1) above. As another feature related to the steepness of the rise of the pulse wave, the pulse wave feature 1 / ab time is added for comparison.

[0036] These pulse wave features, 1 / VE0.5, a / S and (ab) / , which are the basis of peripheral blood pressure indices, (ad) may be used alone, but the peak values ​​a, b, c and d of the a-wave, b-wave, c-wave and d-wave are easily affected by the state of pressure of the photoelectric pulse wave sensor 211 against the skin and by body movement noise, and there is also a large variation due to individual differences. Therefore, since 1 / VE0.5 is a feature that can be acquired relatively stably among the above pulse wave feature quantities, it is desirable to use 1 / VE0.5 alone, or to use other feature quantities as a supplement using 1 / VE0.5 as a base. Furthermore, it is also possible to use values ​​obtained by weighting and averaging each of these pulse wave feature amounts, or to use values ​​obtained by normalizing the magnitude of each pulse wave feature amount and averaging the normalized magnitude.

[0037] In this embodiment, we attempted to derive a blood pressure estimation formula that can estimate the user's blood pressure value by performing calculations. In order to create this blood pressure estimation formula, the following data was collected to extract pulse wave features that are likely to be causally related to blood pressure. Hereinafter, unless otherwise specified, blood pressure refers to wrist systolic blood pressure. (A) An experiment was conducted in which the blood pressure was intentionally changed by changing the height of the blood pressure measurement site from the heart, and correlation data between the above-mentioned pulse wave feature values ​​and blood pressure obtained by changing the height of the blood pressure measurement site from the heart was collected. In addition, correlation data between the above-mentioned pulse wave feature values ​​and blood pressure obtained by forcibly contracting blood vessels by cooling the vicinity of the blood pressure measurement site was collected. (B) In addition, with the cooperation of the hospital, we obtained correlation data between each pulse wave feature and blood pressure for diabetic patients and healthy individuals, and collected extreme correlation data that differed greatly depending on the user.

[0038] First, as an experiment to intentionally change blood pressure as described above in (A), the following experiment was conducted on healthy subjects.

[0039] That is, a finger-worn sensing device 20 shown in FIG. 2 equipped with a photoelectric pulse wave sensor 211 was prepared, a wrist-type cuff blood pressure monitor was attached to the left wrist (or right hand) of the user 40, and the sensing device 20 was attached to the index finger (or other finger) of the same left hand. Then, in a resting sitting position, the left hand with the sensing device 20 attached was held at the height of the abdomen (navel), chest, and face (forehead), respectively, and the photoelectric pulse wave and blood pressure were measured. The measurement site for the photoelectric pulse wave was the ventral side of the fingertip (distal phalanges). Since the blood flow of the finger is obstructed by the cuff when the photoelectric pulse wave and blood pressure are measured simultaneously, the blood pressure was measured after the measurement of the photoelectric pulse wave was completed. Next, the elbow of the left hand was cooled with an ice pack while the left hand was held at chest height. After cooling for several minutes, the photoelectric pulse wave and blood pressure were measured. From the photoelectric pulse wave measured in this way, the feature amount of the pulse wave showing the above features (1) and (2) of the peripheral blood pressure index was calculated as follows.

[0040] FIG. 9 shows the relationship between systolic blood pressure and each pulse wave feature when the height of the measurement site (finger) from the heart is changed, as measured by the above-mentioned measurement method, and the relationship between systolic blood pressure and each pulse wave feature when cooling the area near the elbow of the arm on the side where the finger is located at chest height. Also, FIG. 9(a), (c), and (e) show the relationship between systolic blood pressure and each pulse wave feature when the height of the measurement site (finger) is changed from the heart height to the elbow of the arm on the side where the finger is located, as measured by the above-mentioned measurement method. 9(b), (d), and (f) show the results calculated from the photoelectric pulse wave signal measured with green light emitted from the green LED 211a for the pulse wave feature quantities 1 / VE0.5, a / S, and (ab) / (ad), respectively, when the near-infrared LED 211 The results calculated from the photoplethysmographic signal measured using near-infrared light emitted from b are shown.

[0041] The horizontal axis of each graph is the systolic blood pressure [mmHg] measured at the wrist, and the vertical axis is the magnitude of each pulse wave feature. Measurements were performed for three users, A, B, and C, and characteristic line A obtained by connecting the triangular plots shows the measurement results for user A, characteristic line B obtained by connecting the circular plots shows the measurement results for user B, and characteristic line C obtained by connecting the rectangular plots shows the measurement results for user C when the height of the measurement site (finger) from the heart was changed. Each plot drawn with a dashed line shows the measurement results when the vicinity of the measurement site was cooled at chest height.

[0042] The pulse wave feature values ​​shown in Fig. 9 (a), (c), and (e) calculated from the photoelectric pulse wave signal measured with green light show a tendency for the systolic blood pressure and each pulse wave feature value to be nearly proportional when the height of the measurement site (finger) from the heart is changed, as can be seen from the characteristic lines A, B, and C. As the height of the measurement site (finger) from the heart increases from the abdomen to the chest to the face, the systolic blood pressure decreases almost in proportion to the decrease in each pulse wave feature value. In addition, when the vicinity of the measurement site is cooled, the magnitude of each pulse wave feature value decreases, and the tendency for the systolic blood pressure to increase can be confirmed from each plot shown by the dashed line. This is consistent with the above-mentioned characteristics (1) and (2) of the expected peripheral blood pressure index.

[0043] On the other hand, the results of calculating the pulse wave features shown in Figures 9(b), (d) and (f) from the photoelectric pulse wave signal measured almost simultaneously with near-infrared light and green light show that the above-mentioned trends are not as clear when compared with the results calculated from green light. Therefore, it is presumed that the photoelectric pulse wave signal obtained with green light is more suitable as a peripheral blood pressure index than that obtained with near-infrared light. From this experiment, a peripheral blood pressure index was created from the pulse wave feature values ​​1 / VE0.5, a / S and (ab) / (ad). did.

[0044] In addition, as an experiment to collect significantly different extreme correlation data as described above in (B), the following experiment was conducted in collaboration with a hospital on diabetic patients.

[0045] That is, a wrist-cuff blood pressure monitor was attached to the left wrist (or the right hand) of a diabetic user 40, and a finger-worn sensing device 20 shown in FIG. 2 was attached to the index finger (or other finger) of the same left hand. Then, in a sitting position at rest, the left hand with the sensing device 20 attached was held at the height of the abdomen (navel), chest, and face (forehead), and the photoplethysmogram and blood pressure were measured. The photoplethysmogram was measured on the ventral side of the fingertip (distal phalanges). Since the cuff would obstruct blood flow to the finger if the photoplethysmogram and blood pressure were measured simultaneously, the blood pressure was measured after the photoplethysmogram measurement was completed.

[0046] From the photoplethysmogram thus measured, the relationship between the pulse wave feature value 1 / VE0.5 and the systolic blood pressure was calculated, as shown in the graphs in Figure 10 (a) and (b). The horizontal axis of each graph is the wrist. The vertical axis is the systolic blood pressure of the patient, and the vertical axis is the magnitude of the pulse wave feature value 1 / VE0.5. The graph in Figure 10(a) shows ,The pulse wave feature value calculated from the photoelectric pulse wave signal measured using green light 1 / VE0.5,Figure 10( Graph b) shows the pulse wave feature value 1 / VE0.5 calculated from the photoelectric pulse wave signal measured using near-infrared light. For comparison, the data of the above-mentioned healthy subjects are also plotted in the same graph. The data for diabetic patients are shown as circular plots and the data for healthy subjects as triangular plots.

[0047] In the graph of Figure 10, it can be seen that the higher the blood pressure, the smaller the pulse wave feature value 1 / VE0.5. In Figure 10(a), diabetic patients are concentrated in the low value of the pulse wave feature quantity 1 / VE0.5. It was found that the appearance of the pulse wave feature 1 / VE0.5 was clearly different between healthy subjects and diabetic patients. This is presumably due to the following mechanism.

[0048] In other words, if blood glucose levels remain high for a long time, it will lead to so-called vascular disease, in which blood vessels become fragile and worn out. In this vascular disease, arteriosclerosis progresses in large blood vessels, and small blood vessels are also damaged, causing a decline in vascular function (vascular endothelial function) and poor blood flow. As we move from large arteries to arterioles and capillaries, local blood pressure (peripheral blood pressure) decreases, and it is estimated that when vascular function (vascular endothelial function) decreases, the degree of decrease in peripheral blood pressure increases. It is said that 40 to 60% of diabetic patients also suffer from hypertension, and in Figure 10(a), diabetic patients have relatively higher systolic blood pressure than healthy people, but this tendency is not significant. However, there is a clear tendency for diabetic patients to have a lower pulse wave feature value 1 / VE0.5 (peripheral blood pressure index). This is because This can be explained by the fact that diabetic patients develop peripheral vascular disorders, which make it difficult for blood to flow to the periphery (capillaries), resulting in a drop in peripheral (capillary) blood pressure.

[0049] Figures 11(a)-(d) and Figures 12(e)-(h) are graphs showing the relationship between each pulse wave feature and systolic blood pressure obtained from the above experiment conducted on diabetic patients, and Figure 12(i) is a graph showing the relationship between the pulse interval and systolic blood pressure. For comparison, the data of the healthy subjects mentioned above is also plotted in each of these graphs, with the diabetic patient data shown as circles and the healthy subject data shown as triangles.

[0050] The horizontal axis of each graph in Fig. 11(a)-(d) and Fig. 12(e)-(h) is the systolic blood pressure at the wrist, and the vertical axis is the magnitude of each pulse wave feature. The horizontal axis of the graph in Fig. 12(i) is the systolic blood pressure at the wrist, and the vertical axis is the pulse interval. In each graph in Fig. 11(a) and (b), the pulse wave feature is the pulse wave feature ab time calculated from the photoelectric pulse wave signal measured using green light and near-infrared light. In each graph in Fig. 11(c) and (d), the pulse wave feature is the pulse wave feature bd time calculated from the photoelectric pulse wave signal measured using green light and near-infrared light. In each graph in Fig. 12(e) and (f), the pulse wave feature is the pulse wave feature de time calculated from the photoelectric pulse wave signal measured using green light and near-infrared light. In each graph in Fig. 12(g) and (h), the pulse wave feature is the pulse wave feature ae time calculated from the photoelectric pulse wave signal measured using green light and near-infrared light.

[0051] Here, the ab time is the difference between the a-wave peak time and the b-wave peak time of the acceleration pulse wave signal 52 shown in FIG. 6, the bd time is the difference between the b-wave peak time and the d-wave peak time, and the ae time is the difference between the a-wave peak time and the e-wave peak time.

[0052] In each graph of Fig. 11(a)-(d) and Fig. 12(e)-(h), the pulse wave feature values ​​that were correlated with the systolic blood pressure were the de time shown in Fig. 12(e) and (f), which showed a negative correlation, the bd time shown in Fig. 11(c) and (d), which showed a positive correlation, and the ab time shown in Fig. 11(a) and (b), which showed a weak negative correlation. The ae time shown in Fig. 12(g) and (h), and the pulse interval shown in Fig. 12(i) did not show any correlation with the systolic blood pressure. In addition, the pulse wave feature value that showed a difference between healthy subjects and diabetic patients was the de time, which tended to be larger in diabetic patients, but no clear tendency was confirmed for the other feature values.

[0053] The mechanism by which the de time changes is presumed to be as follows. It can be seen from FIG. 7 that the d wave peak time is close to the time of the maximum value of the photoelectric pulse wave signal 53. The position where the photoelectric pulse wave signal 53 reaches its maximum value may be near the b wave. The waveform near the b wave is considered to be the ejection wave from the heart, and the waveform near the d wave is considered to be a reflected wave from the periphery. The concave portion of the photoelectric pulse wave signal 53 after the photoelectric pulse wave signal 53 reaches its maximum value at around 0.4 sec in FIG. 7 is called the incisal notch. The tendency for the de time to become shorter as blood pressure increases means that the d wave position moves backward (towards the e wave peak), since there is no clear trend with blood pressure in the ae time.

[0054] An increase in blood flow means an increase in the ejection wave and the reflected wave, and therefore it is presumed that the convex part (near the b-wave to d-wave) of the photoplethysmogram signal 53 spreads backward, and as a result the d-wave position moves backward. In other words, it is presumed that the blood flow increases due to the increase in blood pressure, and the increase in blood flow shortens the de time. Also, from FIG. 12(f), it can be seen that the de time tends to be longer in diabetic patients than in healthy subjects, so that the d-wave position tends to approach the e-wave as blood pressure increases, and is further away from the e-wave in diabetic patients than in healthy subjects, that is, the blood flow tends to be less than in healthy subjects.

[0055] From the above speculation, it can be inferred that blood flow is low in diabetic patients. This does not contradict the above speculation that peripheral blood pressure is lowered in diabetic patients, making blood flow more difficult.

[0056] From the above, the pulse wave feature values ​​in which clear differences were confirmed between diabetic patients and healthy subjects were the pulse wave feature value 1 / VE0.5, measured using green light for photoplethysmography, and de time.

[0057] In Figures 11(a) and (c), several circular plots can be seen on the horizontal time axis, which indicates that the b-wave could not be detected. All of these plots are from diabetic patients. As shown here, in people with poor peripheral circulation such as diabetics, the b-wave becomes smaller and is often difficult to detect.

[0058] The graph in Figure 13 shows the correlation between the pulse wave feature value (ab) / (ad) and (wrist) systolic blood pressure. The horizontal axis of the graph is the wrist systolic blood pressure, and the vertical axis is the magnitude of the pulse wave feature value (ab) / (ad). The graph in Figure 13(a) shows the correlation between blood pressure and the pulse wave feature value (ab) / (ad) calculated from the photoplethysmographic signal measured using green light, and the graph in Figure 13(b) shows the correlation between blood pressure and the pulse wave feature value (ab) / (ad) calculated from the photoplethysmographic signal measured using near-infrared light.

[0059] The tendency for the pulse wave feature value (ab) / (ad) to become smaller as the blood pressure increases is the same as that for the pulse wave feature value 1 / VE0.5. ) clearly separates diabetic patients from healthy controls. In this graph, too, there are some circular plots on the horizontal time axis, which indicate that b-waves could not be detected.

[0060] The graph in Fig. 14 shows the relationship between the pulse wave feature value a / S and (wrist) systolic blood pressure. The horizontal axis of the graph is wrist systolic blood pressure, and the vertical axis is the magnitude of the pulse wave feature value a / S. The graph in Fig. 14(a) shows the correlation between blood pressure and the pulse wave feature value a / S calculated from the photoelectric pulse wave signal measured using green light, and the graph in Fig. 14(b) shows the correlation between blood pressure and the pulse wave feature value a / S calculated from the photoelectric pulse wave signal measured using near-infrared light. The above-mentioned tendency for the pulse wave feature value a / S to decrease in magnitude as blood pressure increases is not clear. This is because there is a large variability in the calculation results of the pulse wave feature value for diabetic patients. It is presumed that the cause of the variability is that the values ​​of a and S are easily affected by various factors.

[0061] From the above data collection results, the pulse wave features that showed differences between diabetic patients and healthy subjects were 1 / VE0.5 and (ab) / (ad), which are peripheral blood pressure indices, and de time. It is estimated that the pulse wave feature value is highly likely to be causally related to blood pressure.

[0062] Next, based on these pulse wave feature values, we will first create a blood pressure index base formula. Ultimately, we plan to use a large amount of data based on this base formula to adjust the parameters and improve the estimation accuracy. Below, we will present the proposed blood pressure index base formula, focusing on the pulse wave feature value 1 / VE0.5 and de time. Create.

[0063] First, the basic specifications of the blood pressure index-based equation were set as follows: (a) Estimate blood pressure values ​​when the measurement site is at chest (heart) height. This is because even if it is possible to estimate wrist blood pressure values ​​when the measurement site is other than at chest height, this is of no value to the user. (b) The measurement site will be limited to the base of the finger. For ease of use, a ring device will be used.

[0064] Therefore, the ring device is designed to be able to estimate the blood pressure value when it is held at chest (heart) height. If the measurement is performed with the ring device shifted from the height of the heart, the desired specification of the blood pressure index-based formula is that the blood pressure value at the height of the heart can always be estimated, and it is not that the estimated blood pressure value becomes lower (higher) according to the head difference when the ring device becomes higher (lower) from the height of the heart. However, since it is difficult to estimate the blood pressure value at the height of the heart regardless of the height of the ring device from the heart, the estimation accuracy when the ring device is shifted from the height of the heart is not taken into consideration, that is, it is not guaranteed. If the measurement site is 10 cm higher than the height of the heart, the blood pressure will be 7 to 8 mmHg lower. In other words, if the height range considered to be equivalent to the height of the heart is ±10 cm, the blood pressure value will vary by ±7 to 8 mmHg.

[0065] The blood pressure index base equation created based on the above idea is shown in the following equation (1).

number

[0066] Here, the subscripts a and b represent green light and near-infrared light, respectively, and represent the color of the light emitted by the light source for measuring the photoplethysmographic signal used to calculate the pulse wave feature quantity 1 / VE0.5 or de time. The exponents α and β, which indicate the power, are positive values. When the calculation result of the formula (1) is used as the estimated blood pressure value, the blood pressure index value calculated by the above formula (1) is further multiplied by a proportional coefficient, and a constant term is added as necessary.

[0067] An example of the relationship between the calculated value of formula (1) and the (wrist) systolic blood pressure is shown in the graph of Fig. 15. In this graph, the calculation was performed with the subscript a in formula (1) representing green light, b representing near-infrared light, and the exponent α = β = 0.5. In addition, a wrist-cuff blood pressure monitor was attached to the left wrist (or the right hand) of user 40, and the finger-worn sensing device 20 shown in Fig. 2 was attached to the index finger (or other finger) of the same left hand. In a resting sitting position, the left hand with the sensing device 20 attached was held at chest height, and the photoelectric pulse wave and blood pressure were measured.

[0068] The graph in Figure 15(a) shows the distribution of blood pressure index values ​​for diabetic patients and healthy subjects, while the graph in Figure 15(b) shows the correlation between the calculated value of formula (1) and (wrist) systolic blood pressure. The horizontal axis of each graph is wrist systolic blood pressure, and the vertical axis is the calculated value of formula (1). Assuming that the calculated value of formula (1) is proportional to the systolic blood pressure for both diabetic patients and healthy subjects as a whole, the linear approximation equation between the calculated value of formula (1) and the systolic blood pressure is expressed as y = 0.0108x as shown in Figure 15(b), and the coefficient of determination R of this approximation equation is 2 The result was approximately 0.55 (=0.5481). The correlation coefficient is the coefficient of determination R 2 Since the square root of this is 0.74, it can be said that there is a strong correlation between the calculated value of equation (1) and the systolic blood pressure.

[0069] An example of this blood pressure index-based formula (a: green light, b: near-infrared light, α=β=0.5) is expressed as the pulse wave feature value 1 / VE0.5 (green light) of the photoelectric pulse wave signal measured with green light, as shown in the following formula (2). ) and the reciprocal of the geometric mean of the de time (near-infrared light) of the photoelectric pulse wave signal measured with near-infrared light.

number

[0070] It is estimated that the peripheral blood pressure index calculated from the pulse wave feature value decreases as peripheral vascular function declines, but this formula (2) may indicate that the de time (near infrared light) increases as peripheral vascular function declines. Note that the number of data used to calculate the graph in Figure 15 was 19 data for 17 subjects with diabetes patients, 7 data for 7 subjects with healthy subjects, and 26 data for a total of 24 subjects, which is statistically insufficient.

[0071] 16(a) and (b) show examples of calculations in which the subscripts a and b in formula (1) represent green light and the exponents α=β=0.5. In these graphs, we also assume that the calculated value of formula (1) is proportional to the systolic blood pressure for both diabetic patients and healthy subjects. As shown in FIG. 16(b), the linear approximation between the calculated value of formula (1) and the systolic blood pressure is expressed as y=0.01x, and the coefficient of determination R of the approximation is 2 The result was approximately 0.35 (=0.3509).

[0072] 16(c) and (d) show examples of calculations in which the subscripts a and b in formula (1) represent near-infrared light and the exponents α=β=0.5. In these graphs, we also assume that the value calculated using formula (1) is proportional to the systolic blood pressure for both diabetic patients and healthy subjects. As shown in FIG. 16(d), the linear approximation between the value calculated using formula (1) and the systolic blood pressure is expressed as y=0.0101x, and the coefficient of determination R 2 The result was approximately 0.32 (=0.3173).

[0073] The coefficients of determination for both the approximation equations in the graphs of Figures 16(b) and (d) are lower than that for the approximation equation in the graph of Figure 15(b). One reason for the large variability in the diabetic patient data in the graph of Figure 16(b) is the large variability in the de time (green light) calculated from the photoplethysmogram measured with green light (see Figure 12(e)). Also, one reason for the large variability in the diabetic patient data in the graph of Figure 16(d) is the large variability in the pulse wave feature value 1 / VE0.5 (near-infrared light) calculated from the photoplethysmogram measured with near-infrared light (see Figure 10(b)). )reference).

[0074] The blood pressure index-based formula (2) was applied to data measured over a long period of time for the same subject. In other words, 24 sets of measurements were taken over a 20-day period, with one set being data taken at measurement sites with heights of navel-chest-forehead. Measurements were taken in the morning, afternoon, or evening, and 9, 12, and 3 sets of data were obtained, respectively.

[0075] The graphs in Figures 17(a) and (b) show the relationship between wrist systolic blood pressure and the blood pressure index value calculated from equation (2) when the height of the measurement site (finger) from the heart is changed in this way. The horizontal axis of each graph is wrist systolic blood pressure, and the vertical axis is the blood pressure index value calculated from the blood pressure index base equation in equation (2). The triangular plots are the measurement results for the navel, the square plots are the chest, and the circular plots are the forehead.

[0076] In the graph of FIG. 17(a), blood pressure index values ​​calculated from formula (2) for the photoplethysmogram measured at each height are plotted against the wrist systolic blood pressure measured at each height. In the graph of FIG. 17(b), blood pressure index values ​​calculated from formula (2) for each wrist systolic blood pressure measured at the navel and forehead heights are plotted, all unified at chest height, by replacing the systolic blood pressures measured at the navel and forehead heights with measurements at chest height. Note that the measurement order is photoplethysmogram (navel) → wrist blood pressure (navel) → photoplethysmogram (chest) → wrist blood pressure (chest) → photoplethysmogram (forehead) → wrist blood pressure (forehead), and measurements are not taken simultaneously.

[0077] From the graph in Figure 17(a), we can see that the blood pressure index values ​​at the height of the navel, chest, and forehead are distributed in roughly the same range, although there is some variation. Also, from the graph in Figure 17(b), we can see that if the blood pressure index values ​​at the height of the navel, chest, and forehead are all standardized to those measured at chest height, the blood pressure index values ​​at the height of the navel, chest, and forehead will roughly overlap.

[0078] The components of the blood pressure index-based formula are the pulse wave feature 1 / VE0.5 (green light) and de time ( The graph in Figure 18(a) shows the relationship between the pulse wave feature value 1 / VE0.5 (green light) and the systolic blood pressure. The graph in Figure 18(b) shows the relationship between de time (near-infrared light) and systolic blood pressure.

[0079] From the graph in Fig. 18(a), the pulse wave feature value 1 / VE0.5 (green light) is plotted as a triangle. The graph in Figure 18(b) shows that the de time (near infrared light) shows a reverse trend. The reason for this is that 1 / VE0.5 (green light) has a positive correlation with blood pressure (as shown in the graph in Figure 9(a)) (normal subjects). This is because, based on the above-mentioned mechanism, the de time (near-infrared light) and the de time (near-infrared light) are negatively correlated with blood flow. Therefore, in the graph of Figure 17 showing the relationship between blood pressure index value and blood pressure, the blood pressure index value did not show a significant change even if the height of the measurement site from the heart changed, which is due to the changes in the pulse wave feature value 1 / VE0.5 (green light) and the de time (near-infrared light). It is assumed that this is because the effects of the two factors were offset to some extent.

[0080] Therefore, by multiplying 1 / VE0.5 (green light) and de time (near infrared light), the formula ( 2) It can be assumed that the blood pressure index value estimated in accordance with the method above will not fluctuate significantly even if the height of the measurement site deviates from the height of the heart.

[0081] What is useful for the user is the blood pressure value at the height of the heart, and from the viewpoint of usability, it is desirable to be able to estimate the blood pressure value at the height of the heart even if the height of the measurement site (finger) deviates from the height of the heart. The above-mentioned blood pressure index-based formula of the present invention is useful from the viewpoint of this usability. However, in diabetic patients with reduced vascular function, the 1 / VE0.5 ratio to the change in blood pressure is Therefore, the above assumption that the pulse wave features are offset to some extent does not hold true, and for users with reduced peripheral vascular function, the measurement site needs to be kept at heart height.

[0082] In addition, if the blood pressure drop index is defined as the blood pressure index / peripheral blood pressure index, which is an index showing how much blood pressure has dropped in the capillaries from the wrist, then this blood pressure drop index can be expressed by the following equation (3).

number

[0083] Here again, the subscripts a and b represent green light and near-infrared light, respectively, and represent the emission color of the measurement light source of the photoelectric pulse wave signal used to calculate the pulse wave feature amount 1 / VE0.5 or de time. The exponents α and β, which indicate the powers, are positive values. It is inferred that the larger the value of the blood pressure drop index calculated by formula (3), the higher the vascular resistance and the more likely a vascular disorder is occurring.

[0084] The graph in Figure 19 shows an example of measuring the blood pressure drop index and blood pressure by calculating equation (3) with the subscript a representing green light, b representing near-infrared light, and exponents α=β=0.5. The horizontal axis of the graph is the wrist systolic blood pressure, and the vertical axis is the magnitude of the blood pressure drop index calculated by equation (3). It can be seen from the graph that the blood pressure drop index is larger in diabetic patients.

[0085] If an actual measurement value of peripheral blood pressure can be obtained, the actual degree of blood pressure reduction can be calculated by multiplying the blood pressure reduction index by a proportionality coefficient.

[0086] So far, we have explained systolic blood pressure, but diastolic blood pressure can also be estimated using a similar method. A diastolic blood pressure index-based equation was created using the features used in the blood pressure index-based equation shown in equation (1).

[0087] Fig. 20 is a graph showing an example of the relationship between the calculated value of this diastolic blood pressure index-based formula and the measured (wrist) diastolic blood pressure. In this graph, the calculated value was calculated using the diastolic blood pressure index-based formula in which the subscript a in formula (1) is green light, b is near-infrared light, α=0.35, and β=0.85. In addition, a wrist-cuff blood pressure monitor was attached to the left wrist (or the right hand) of user 40, and a finger-worn sensing device 20 shown in Fig. 2 was attached to the index finger (or other finger) of the same left hand. In a resting sitting position, the left hand with the sensing device 20 attached was held at chest height, and the photoelectric pulse wave and diastolic blood pressure were measured.

[0088] The graph in Figure 20(a) shows the distribution of diastolic blood pressure index values ​​for diabetic patients and healthy subjects, while the graph in Figure 20(b) shows the correlation between the calculated value of the diastolic blood pressure index based formula based on the above formula (1) and the (wrist) diastolic blood pressure. The horizontal axis of each graph is the wrist diastolic blood pressure, and the vertical axis is the calculated value of the diastolic blood pressure index based formula based on formula (1). Assuming that the calculated value of the diastolic blood pressure index based formula based on formula (1) is proportional to the diastolic blood pressure for both diabetic patients and healthy subjects as a whole, the linear approximation equation between the calculated value of the diastolic blood pressure index based formula based on formula (1) and the diastolic blood pressure is expressed as y = 0.0576x as shown in Figure 20(b), and the coefficient of determination R of this approximation equation is 2 The result was approximately 0.49 (=0.4873). The correlation coefficient was 0.70, which means that there is a strong correlation between the calculated value of the diastolic blood pressure index-based formula based on formula (1) and the diastolic blood pressure.

[0089] The diastolic pressure index-based formula is 1 / VE0.5 (green) compared to the systolic pressure index-based formula. The absolute value of the exponent of de time (near-infrared light) becomes larger.

[0090] The blood pressure index-based equation, which adds the ae time to equation (1), is shown in the following equation (4).

number

[0091] Here, the subscripts a, b, and c represent green light or near-infrared light, respectively, and indicate the emission of the light source for measuring the photoplethysmographic signal used to calculate the pulse wave feature quantity 1 / VE0.5 or the de time or ae time. It represents the color. The exponents α, β, and γ, which indicate the power, are positive numbers.

[0092] Fig. 21 is a graph showing an example of the relationship between the calculated value of the diastolic blood pressure index-based formula and the measured (wrist) diastolic blood pressure when the calculation is performed using the diastolic blood pressure index-based formula in which the subscripts a in formula (4) are green light, b and c are near-infrared light, and α = 0.35, β = 0.8, and γ = 0.4. The photoplethysmogram and diastolic blood pressure were measured by attaching a wrist-cuff blood pressure monitor to the left wrist (or right hand) of user 40, attaching finger-worn sensing device 20 shown in Fig. 2 to the index finger (or other finger) of the same left hand, and sitting still with the left hand with sensing device 20 attached held at chest height.

[0093] The graph in Figure 21(a) shows the distribution of diastolic blood pressure index values ​​for diabetic patients and healthy subjects, while the graph in Figure 21(b) shows the correlation between the calculated value of the diastolic blood pressure index based formula based on formula (4) and the (wrist) diastolic blood pressure. The horizontal axis of each graph is the wrist diastolic blood pressure, and the vertical axis is the calculated value of the diastolic blood pressure index based formula based on formula (4). Assuming that the calculated value of the diastolic blood pressure index based formula based on formula (4) is proportional to the diastolic blood pressure for both diabetic patients and healthy subjects as a whole, the linear approximation equation between the calculated value of the diastolic blood pressure index based formula based on formula (4) and the diastolic blood pressure is expressed as y = 0.0850x as shown in Figure 21(b), and the coefficient of determination R of this approximation equation is 2 The correlation coefficient of the diastolic blood pressure index-based equation based on equation (4) is 0.71, which is an improvement over the correlation coefficient of the diastolic blood pressure index-based equation based on equation (1).

[0094] In the diastolic blood pressure index base equation based on equation (4) used to create the graph in Figure 21, the ae time of near-infrared light was used, but since there is no significant difference in the ae time between near-infrared light and green light, using the ae time of green light does not have a significant effect on the correlation coefficient.

[0095] The notch of the photoelectric pulse wave signal 53, which is the depression after the photoelectric pulse wave signal 53 reaches its maximum value, is said to be the end of the systole, and the e wave corresponds to the notch. Since no significant difference was observed, it is assumed that the e wave is less affected by the state of blood vessels, etc. A long e time means that the left ventricle is contracting for a long time. Therefore, it can be inferred that the ae time is positively correlated with the stroke volume. Equation (4) also means that the diastolic blood pressure is negatively correlated with the ae time. Therefore, it can be inferred that as the stroke volume increases, the diastolic blood pressure decreases.

[0096] It is said that when systolic blood pressure rises, a reflex reaction occurs that opens the peripheral blood vessels, reducing peripheral vascular resistance and lowering diastolic blood pressure. Since systolic blood pressure increases when stroke volume increases, it is thought that diastolic blood pressure will decrease through the above mechanism, so it is reasonable that diastolic blood pressure is negatively correlated with ae time, as indicated by formula (4).

[0097] When the calculation result of each diastolic blood pressure index based formula based on the above formula (1) and formula (4) is used as a blood pressure estimated value, the diastolic blood pressure index value calculated by each diastolic blood pressure index based formula is further multiplied by a proportional coefficient and a constant term is added as necessary. In addition, the blood pressure index based formula shown in formula (4) can also be used as a systolic blood pressure index based formula by appropriately selecting the values ​​of the exponents α, β, and γ indicating the power.

[0098] 22 is a flowchart showing an example of processing in the blood pressure estimation method according to the embodiment of the present invention. The processing by the biological information measurement system 10 is performed, for example, by the sensing device 20 and the computer 30 each having an information processing device such as a processor, executing a program stored in a non-temporary storage area of ​​the sensing device 20 and the computer 30.

[0099] In step S1101, sensing device 20 of biological information measurement system 10 measures a photoplethysmographic signal from the finger of a user wearing sensing device 20. Specifically, photoplethysmographic sensor 211 measures photoplethysmographic signal 53 using green light emitted by green LED 211a, and also measures photoplethysmographic signal 53 using near-infrared light emitted by near-infrared LED 211b.

[0100] In step S1102, the sensing device 20 transmits the measurement result to the computer 30 of the biological information measurement system 10. In step S1103, the computer 30 receives the measurement result of the sensing device 20.

[0101] In step S1104, the computer 30 calculates the peripheral blood pressure index of the user. For example, the computer 30 calculates the pulse wave feature quantities 1 / VE0.5, a / S and (ab) / (ad) from the photoelectric pulse wave signal 53 measured by the biosensor 21, and calculates the peripheral blood pressure index from the calculated pulse wave feature quantities. The user's peripheral blood pressure index and de time are calculated.

[0102] In step S1105, the computer 30 calculates a blood pressure index value using the above-mentioned blood pressure index-based formula based on the peripheral blood pressure index and de time stored in a storage unit such as the memory 322, and estimates the user's blood pressure from the calculated blood pressure index value.

[0103] An exemplary embodiment of the present invention has been described above. The blood pressure estimation method described in this embodiment includes the steps of acquiring a photoelectric pulse wave signal 53 of a peripheral blood vessel of a user who is a subject using a photoelectric pulse wave sensor 211, calculating a peripheral blood pressure index that is an index of the blood pressure of a peripheral capillary or arteriole based on the steepness of the rise of the photoelectric pulse wave signal 53, and estimating the blood pressure of the user using the peak time difference de between the d wave and the e wave in the accelerated pulse wave signal 52 obtained by second-order differentiation of the photoelectric pulse wave signal 53 and the peripheral blood pressure index, which are executed by the biological information measurement system 10.

[0104] According to this configuration, photoelectric pulse wave signal 53 of the user's peripheral capillaries or arterioles is acquired by photoelectric pulse wave sensor 211, and a peripheral blood pressure index serving as an index of the blood pressure of the user's peripheral capillaries or arterioles is calculated based on the steepness of the rising edge of acquired photoelectric pulse wave signal 53. The user's blood pressure is estimated using the calculated peripheral blood pressure index and de time in accelerated pulse wave signal 52 obtained by second-order differentiation of photoelectric pulse wave signal 53. The peripheral blood pressure index and de time used to estimate blood pressure each have a strong correlation with blood pressure.

[0105] Therefore, according to this configuration, it is possible to provide a blood pressure estimation method that can non-invasively estimate a user's blood pressure information with high accuracy.

[0106] Moreover, in the above blood pressure estimation method, the peripheral blood pressure index is calculated from the photoplethysmographic signal 53 acquired by the photoplethysmographic sensor 211 for at least the peripheral capillaries.

[0107] The peripheral blood pressure index has a stronger correlation with blood pressure when there is more capillary information. Therefore, according to this configuration, the peripheral blood pressure index having a stronger correlation with blood pressure is used to estimate the user's blood pressure, so that the user's blood pressure information can be estimated with higher accuracy.

[0108] Moreover, in the above blood pressure estimation method, the de time is calculated from the photoplethysmographic signal 53 acquired by the photoplethysmographic sensor 211 for at least the peripheral arteriole.

[0109] The more information on the arterioles, the stronger the correlation between the de time and blood pressure. Therefore, according to this configuration, the de time, which has a stronger correlation with blood pressure, is used to estimate the user's blood pressure, so that the user's blood pressure information can be estimated with higher accuracy.

[0110] In the above blood pressure estimation method, as shown in equation (1), the blood pressure of the user is estimated from the product of the power of the peripheral blood pressure index and the power of de time.

[0111] According to this configuration, the user's blood pressure can be easily estimated by performing calculations using a simple formula.

[0112] In addition, in the above blood pressure estimation method, the exponent of the peripheral blood pressure index and the exponent of the de time are negative values.

[0113] Both the peripheral blood pressure index and the de time have a strong negative correlation with blood pressure. Therefore, according to this configuration, the peripheral blood pressure index and the exponent of the power of the de time are set to negative values, and the user's blood pressure can be easily estimated with high accuracy.

[0114] Moreover, the above blood pressure estimation method preferably includes a step of determining whether the measurement site of the user where photoplethysmographic signal 53 is measured by photoplethysmographic sensor 211 is at the height of the heart.

[0115] Although blood pressure varies depending on the height from the heart, blood pressure at the height of the heart is medically useful. Therefore, with this configuration, it is possible to make medical decisions by adopting the user's blood pressure estimated using the photoelectric pulse wave signal 53 when the measurement site is at the height of the heart, and it is possible to provide a useful estimated blood pressure of the user.

[0116] Moreover, the above blood pressure estimation method preferably includes a step of acquiring the height from the heart of the measurement part of the user where photoplethysmographic signal 53 is measured by photoplethysmographic sensor 211.

[0117] According to this configuration, it is possible to determine the height of the measurement site relative to the heart at which the estimated blood pressure of the user was estimated using the photoelectric pulse wave signal 53. Therefore, if the estimated blood pressure of the user was estimated using the photoelectric pulse wave signal 53 at which the measurement site was significantly shifted from the height of the heart, it is possible to determine that the blood pressure estimation accuracy is poor or not to output the blood pressure estimate. In addition, it is possible to notify the user that the measurement site is significantly shifted from the height of the heart and to prompt the user to adjust the height of the measurement site.

[0118] A method for estimating the height of the measurement site from the heart will be described below assuming that the computer 30 is a portable control unit such as a multi-function mobile phone terminal called a smartphone, which is equipped with a photographing device that photographs the user 40, a display device that displays the image photographed by the photographing device, an inclination sensor that detects the inclination of the portable control unit, and a control device that controls the photographing device, display device, and inclination sensor. If the height of the measurement site from the heart can be estimated, it can be determined that the measurement site is at the height of the heart.

[0119] First, a first method for estimating the height of a measurement site from the heart from an image of user 40 captured by an imaging device will be described.

[0120] As shown in FIG. 23, the display device presents to the user 40, who is holding the portable control unit 300 in one hand (e.g., the right hand), an instruction to move the other hand (e.g., the left hand) on which the biosensor 21 is attached to a measurement position estimated to be at the height of the heart, and an instruction to photograph the other hand (e.g., the left hand) on which the biosensor 21 is attached and the face 41 of the user 40 with an imaging device when the other hand (e.g., the left hand) on which the biosensor 21 is attached is located at the measurement position, and displays the image captured by the imaging device.

[0121] For example, the control device distinguishes and recognizes the face 41 of the user 40 from the other hand (e.g., the left hand) on which the biosensor 21 is attached, from the image captured by the image capture device. The control device estimates the difference between the height of the heart and the height of the measurement site by comparing the relative positional relationship between the other hand (e.g., the left hand) on which the biosensor 21 is attached and the face 41, which is geometrically determined from the image captured by the image capture device, with the statistical positional relationship between the heart and the face 41. The control device outputs the estimated result of the difference between the height of the heart and the height of the measurement site to the signal processing device 32 as the height of the measurement site from the heart.

[0122] By estimating the statistical positional relationship between the hand and face 41 of user 40 from information indicating physical characteristics of user 40 such as height and weight, it is possible to improve the accuracy of estimating the height of the measurement site from the heart from the relative positional relationship between the hand and face 41 in the image.

[0123] Also, for example, the control device distinguishes and recognizes the face 41 of the user 40 from the biosensor 21 from the image captured by the imaging device. The control device compares the relative positional relationship between the biosensor 21 and the face 41, which is geometrically determined from the image captured by the imaging device at the measurement position, with the statistical positional relationship between the heart and the face 41, to estimate the difference between the height of the heart and the height of the measurement site as the height of the measurement site from the heart. The control device outputs the estimated result of the height of the measurement site from the heart to the signal processing device 32.

[0124] Next, a second method for estimating the height of the measurement site from the heart from an image of user 40 captured by an imaging device will be described.

[0125] As shown in FIG. 24, the display device presents to the user 40, who is holding the portable control unit 300 in the hand (e.g., the right hand) on which the biosensor 21 is attached, an instruction to move the hand (e.g., the right hand) on which the biosensor 21 is attached to a measurement position estimated to be at the height of the heart, and an instruction to photograph the face 41 of the user 40 with a photographing device when the hand (e.g., the right hand) on which the biosensor 21 is attached is located at the measurement position, and displays the image captured by the photographing device.

[0126] The control device estimates the difference between the height of the heart and the height of the measurement site by comparing the relative positional relationship between the heart and face 41, which is geometrically determined based on the positional relationship between the face 41 of the user 40 and the portable control unit 300 and the inclination of the portable control unit 300 relative to a predetermined reference line (e.g., a vertical line) from an image captured by the imaging device at the measurement position, with the statistical positional relationship between the heart and face 41. The inclination sensor detects the inclination of the portable control unit 300 relative to a predetermined reference line (e.g., a vertical line) when the user 40 changes his / her posture at the measurement position to measure a pulse wave signal.

[0127] As shown in Fig. 25, the display device may graphically display a display target range 60 indicating the target position and display target size of the face 41 so as to be superimposed on the face 41 displayed on the display device 301. By adjusting the positional relationship between the face 41 and the display device 301 so that the display position and display size of the face 41 match the target position and display target size of the face 41, respectively, it is possible to estimate the difference between the height of the heart and the height of the measurement site as the height of the measurement site from the heart based on the positional relationship between the face 41 of the user 40 and the portable control unit 300 and the inclination of the portable control unit 300 with respect to a predetermined reference line (e.g., a vertical line) from an image captured by the imaging device. The control device outputs the estimated result of the height of the measurement site from the heart to the signal processing device 32.

[0128] By estimating the size of the user's 40 face (total head height, head width, etc.) from information indicating the physical characteristics of the user 40, such as the height and weight, it is possible to improve the accuracy of estimating the height of the measurement site from the heart from the size of the face in the image.

[0129] In addition, the above blood pressure estimation method preferably includes a step of correcting the estimated blood pressure value of the user based on the acquired height of the measurement part of the user from the heart.

[0130] According to this configuration, the blood pressure estimation accuracy can be improved by correcting the estimated blood pressure value when the measurement site is shifted from the height of the heart. In addition, since the estimated blood pressure value of the user can be corrected and blood pressure can be estimated even if the measurement site is not kept at the height of the heart, the blood pressure of the user can be estimated continuously or intermittently.

[0131] The signal processing device 32 performs a process to correct the estimated blood pressure of the user by taking into account the effect of hydrostatic pressure. In general, when the blood pressure is measured at a position higher than the heart, the measured blood pressure is lower by the pressure difference of hydrostatic pressure in the blood vessel caused by gravity. Conversely, when the blood pressure is measured at a position lower than the heart, the measured blood pressure is higher by the pressure difference of hydrostatic pressure in the blood vessel.

[0132] Signal processing device 32, for example, calculates pulse wave feature amounts from photoelectric pulse wave signal 53 measured by photoelectric pulse wave sensor 211 at each of at least two measurement positions that are different heights from the user's heart, and performs processing to estimate blood pressure from the pulse wave feature amounts. The posture in which the user measures photoelectric pulse wave signal 53 at at least two measurement positions that are different heights from the user's heart may be a sitting posture or a supine posture.

[0133] The signal processing device 32 determines the correlation between the user's blood pressure and the pulse wave feature amount from the heights of at least two measurement positions that are different from the user's heart and the changes in the pulse wave feature amount at the at least two measurement positions. For example, the correlation between the blood pressure and the pulse wave feature amount can be determined from the changes in the pulse wave feature amount when the blood pressure changes from a low state to a high state (when the measurement position changes from a high state to a low state).

[0134] In the process of determining the correlation between the user's blood pressure and the pulse wave feature amount, it is sufficient to know the tendency of the change in the pulse wave feature amount relative to the change in blood pressure. In the process of determining the tendency of the change in the pulse wave feature amount relative to the change in blood pressure, the height difference between the two measurement positions is determined, and the difference in blood pressure corresponding to this height difference is taken into consideration, so that the tendency of the change in the pulse wave feature amount relative to the change in blood pressure can be accurately estimated. Based on this estimation, the signal processing device 32 performs a process of correcting the estimated blood pressure of the user from the accurately calculated pulse wave feature amount.

[0135] In the above blood pressure estimation method, the peripheral blood pressure index is expressed as the reciprocal 1 / VE0.5 of the width at half the peak value of the waveform of the velocity pulse wave signal 51 obtained by first-order differentiation of the photoelectric pulse wave signal 53. It is preferable that the pulse wave characteristic amount is calculated from the pulse wave characteristic amount.

[0136] According to this configuration, the peripheral blood pressure index is calculated based on the pulse wave feature value 1 / VE0.5, and the noise This index is less affected by individual differences in the peripheral blood pressure and photoplethysmogram waveforms, and blood pressure calculated using the peripheral blood pressure index can be estimated for a wide range of users with less influence from noise and individual differences.

[0137] In the above blood pressure estimation method, the peripheral blood pressure index is preferably calculated from a pulse wave feature value expressed as a / S obtained by dividing peak value a of the a-wave of accelerated pulse wave signal 52 obtained by second-order differentiation of photoelectric pulse wave signal 53 by maximum amplitude value S of photoelectric pulse wave signal 53.

[0138] According to this configuration, the peripheral blood pressure index is calculated based on the pulse wave feature value a / S. Therefore, the peripheral blood pressure index can be used to estimate the user's blood pressure using a simple calculation method.

[0139] In the above blood pressure estimation method, the peripheral blood pressure index is preferably calculated from a pulse wave feature value expressed by a value calculated by the formula (ab) / (ad) when the peak values ​​of the a-wave, b-wave, c-wave and d-wave of the accelerated pulse wave signal 52 obtained by second-order differentiation of the photoelectric pulse wave signal 53 are a, b, c and d, respectively.

[0140] According to this configuration, the peripheral blood pressure index is calculated based on the pulse wave feature amount (ab) / (ad). Therefore, according to this configuration, the peripheral blood pressure index can be used to estimate the user's blood pressure using a simple calculation method.

[0141] In the above blood pressure estimation method, it is preferable that the photoplethysmographic sensor 211 emits light in a wavelength band from blue to yellow-green from the first light source and emits light in a wavelength band from red to near-infrared from the second light source.

[0142] According to this configuration, light in a wavelength band from blue to yellow-green that is strongly absorbed by the living body is emitted from the first light source of the photoplethysmographic sensor 211 to the living body of the user. Therefore, a photoplethysmographic signal 53 containing a lot of information on capillaries in a living body region shallow from the skin surface of the living body is acquired by the photoplethysmographic sensor 211. Also, light in a wavelength band from red to near-infrared that is relatively less absorbed by the living body is emitted from the second light source to the living body of the user. Therefore, a photoplethysmographic signal 53 containing a lot of information on arterioles in a living body region deep from the skin surface of the living body is acquired by the photoplethysmographic sensor 211. Therefore, the peripheral blood pressure index and de time are calculated using the photoplethysmographic signal 53 measured by the first light source and the photoplethysmographic signal 53 measured by the second light source, so that the blood pressure of the user can be accurately estimated.

[0143] In the above blood pressure estimation method, it is preferable that the photoelectric pulse wave sensor 211 has a distance between the first light source and the light receiving element that receives the reflected light of the light emitted from the first light source set to 1 to 3 mm, and a distance between the second light source and the light receiving element that receives the reflected light of the light emitted from the second light source set to 5 to 20 mm.

[0144] According to this configuration, since the distance between the first light source and the light receiving element of the photoelectric pulse wave sensor 211 is small, a photoelectric pulse wave signal 53 containing more information on the shallow biological region of the skin, i.e., information on the peripheral capillaries, is acquired. Also, since the distance between the second light source and the light receiving element is large, a photoelectric pulse wave signal 53 containing more information on the deep biological region of the skin, i.e., information on the peripheral arterioles, is acquired. Therefore, the peripheral blood pressure index and de time are calculated using the photoelectric pulse wave signal 53 measured by the first light source and the photoelectric pulse wave signal 53 measured by the second light source, so that the user's blood pressure can be estimated more accurately.

[0145] In the above blood pressure estimation method, the photoplethysmographic sensor 211 is preferably mounted on the sensing device 20 that is worn on the user's finger.

[0146] According to this configuration, photoplethysmographic signal 53 can be acquired stably, continuously or intermittently, from the user's finger by photoplethysmographic sensor 211 mounted on sensing device 20. This allows the user's blood pressure to be estimated stably.

[0147] Moreover, the above blood pressure estimation method preferably further comprises a step of determining whether the user is in a resting state by measuring photoplethysmographic signal 53 by photoplethysmographic sensor 211.

[0148] When the measurement site is moving, inertia is applied to the blood in the blood vessels, and the pulse waveform of the photoelectric pulse wave signal 53 measured by the photoelectric pulse wave sensor 211 also fluctuates. Although blood pressure increases during exercise, the blood pressure at rest is medically useful. When the measurement site is moving, the contact state between the photoelectric pulse wave sensor 211 and the user's skin may change, and when this contact state changes, noise (body movement noise) is generated. Therefore, with this configuration, the acceleration sensor 24, gyro sensor, etc. are used to determine the user's resting state, and blood pressure estimation is performed only when the user is at rest, making it possible to estimate the user's useful blood pressure at rest.

[0149] In addition, in the above blood pressure estimation method, each step may be performed continuously or intermittently while the user is sleeping.

[0150] In healthy individuals, blood pressure decreases during sleep and increases during wakefulness, but those whose blood pressure does not decrease or increases during sleep (nocturnal hypertension) are said to be at higher risk of cardiovascular disease and cerebrovascular disease. It is known that the risk of cerebrovascular disease increases when blood pressure is almost the same during sleep and wakefulness (non-dipper type), when blood pressure increases during sleep (riser type), or when blood pressure is excessively low during sleep (extreme dipper type) compared to dipper type, in which blood pressure during sleep is lower than during wakefulness. With this configuration, photoplethysmography signal 53 is measured continuously or intermittently while the user is sleeping to estimate the user's blood pressure, and by grasping the change in the estimated blood pressure, nocturnal hypertension can be detected.

[0151] The blood pressure estimation method may further include a step of determining whether or not the user is asleep.

[0152] It is known that eating, drinking alcohol, caffeine intake, and smoking affect blood pressure. In addition, exercise, walking, physical work (cleaning, etc.), bathing, conversation, mental tension, noisy and vibrating environments, and cold environments also affect blood pressure. These events occur frequently during wakefulness, and it is difficult to determine when they occurred. On the other hand, during sleep, the influence of such events can be reduced, making it suitable for stable blood pressure measurement. With this configuration, by providing a step of determining whether the user is sleeping based on the amount of activity, body surface temperature, pulse rate, etc., it is possible to easily determine whether the blood pressure of the user is increasing during sleep. Therefore, with this configuration, the accuracy of blood pressure estimation can be improved by distinguishing between the user's wakefulness and sleep states and estimating blood pressure in the sleep state.

[0153] The determination of sleep will be explained. When the acceleration of the biosensor 21 detected by the acceleration sensor 24 exceeds a predetermined value, it is determined that there is body movement, and when the number of body movements within a predetermined time falls below a threshold, it is determined that the person is asleep. Even during sleep, the acceleration of the biosensor 21 may suddenly increase due to turning over in bed, but the frequency of such increases is lower than when the person is awake. The fingers move more frequently during wakefulness than other places such as the waist, breast pocket, and wrist where the activity meter is attached. Therefore, a method may be used in which the person is simply determined to be asleep when the average value of the acceleration of the biosensor 21 over a predetermined time falls below a threshold. In addition, the temperature of the fingers increases during sleep, and the circadian rhythm may be estimated from the body surface temperature of the fingers, and the sleep determination accuracy may be improved by combining this with the detection of the acceleration of the biosensor 21. In addition, the pulse rate decreases during sleep, and the pulse rate is more likely to be affected by respiratory fluctuations, so the pulse rate trend may be added to improve the sleep determination accuracy.

[0154] In addition, the above blood pressure estimation method may further include a step of estimating the degree of drop in blood pressure in a peripheral capillary or arteriole from the blood pressure of an artery upstream of the arteriole as a blood pressure drop index obtained by dividing the arterial blood pressure index by the peripheral blood pressure index 1 / VE0.5 (the product of the power of 1 / VE0.5 and the power of de time) as shown in equation (3).

[0155] By estimating the blood pressure drop index using this configuration, it is possible to estimate how much peripheral (capillary) blood pressure has dropped from the blood pressure of the upper arm, etc. The larger the value of this blood pressure drop index, the higher the vascular resistance, and it can be estimated that a vascular disorder is occurring.

[0156] In addition, in the above blood pressure estimation method, the exponent of the blood pressure drop index, 1 / VE0.5, and , the exponent of the power of de time is a negative value.

[0157] Both the peripheral blood pressure index 1 / VE0.5 and de time have a strong negative correlation with blood pressure. Therefore, according to this configuration, the peripheral blood pressure index 1 / VE0.5 and the power of de time By performing the calculation with a negative exponent, the user's blood pressure can be estimated easily and accurately.

[0158] To summarise the above, the present invention can be expressed as follows.

[0159] <1> acquiring a photoplethysmographic signal of a peripheral blood vessel of the subject using a photoplethysmographic sensor; calculating a peripheral blood pressure index serving as an index of blood pressure in the peripheral capillaries or arterioles based on the steepness of a rise in the photoelectric pulse wave signal; a step of estimating the blood pressure of the subject using the peak time difference between the d wave and the e wave in an accelerated pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal, and the peripheral blood pressure index; A blood pressure estimation method performed by a vital information measuring system. <2> The peripheral blood pressure index is calculated from the photoelectric pulse wave signal acquired by the photoelectric pulse wave sensor for at least the capillaries in the periphery, and the de time is calculated from the photoelectric pulse wave signal acquired by the photoelectric pulse wave sensor for at least the arteriole in the periphery. <1> The blood pressure estimation method according to claim 1 . <3> The magnitude of the subject's blood pressure is estimated from the power of the peripheral blood pressure index and the power of the de time. <1> or <2> The blood pressure estimation method according to claim 1 . <4> The blood pressure of the subject is estimated by further using the ae time, which is the peak time difference between the a wave and the e wave in an acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal. <1> from <3> 13. The blood pressure estimation method according to claim 12, <5> The blood pressure of the subject is a systolic blood pressure. <1> from <4> 13. The blood pressure estimation method according to claim 12, <6> The blood pressure of the subject is a diastolic blood pressure. <1> from <4> 13. The blood pressure estimation method according to claim 12, <7> The method includes the steps of: acquiring a height from the heart of a measurement site of a subject for which a photoelectric pulse wave signal is measured by the photoelectric pulse wave sensor; and correcting an estimated blood pressure value of the subject based on the acquired height from the heart of the measurement site of the subject. <1> from <6> 13. The blood pressure estimation method according to claim 12, <8> The peripheral blood pressure index includes information on the width of a peak that appears first within one beat of the waveform of the velocity pulse wave signal obtained by first differentiating the photoelectric pulse wave signal, or information on the peak value of the a-wave of the acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal and the maximum amplitude value of the photoelectric pulse wave signal, or information on a peak difference (ab) and a peak difference (ad) when the peak values ​​of the a-wave, b-wave, c-wave and d-wave of the acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal are a, b, c and d, respectively. <1> from <7> 13. The blood pressure estimation method according to claim 12, <9> The photoplethysmographic sensor is characterized in that a first light source emits light in a wavelength band from blue to yellow-green, and a second light source emits light in a wavelength band from red to near-infrared. <1> from <8> 13. The blood pressure estimation method according to claim 12, <10> The photoplethysmographic sensor is characterized in that the distance between the first light source and a light receiving element that receives reflected light of the light emitted from the first light source is set to 1 to 3 mm, and the distance between the second light source and a light receiving element that receives reflected light of the light emitted from the second light source is set to 5 to 20 mm. <9> The blood pressure estimation method according to claim 1 . <11> The photoplethysmography sensor is mounted on a device that is worn on the subject's finger. <1> from <10> 13. The blood pressure estimation method according to claim 12, <12> The method further comprises the step of determining a resting state of a subject whose photoelectric pulse wave signal is measured by the photoelectric pulse wave sensor. <1> from <11> 13. The blood pressure estimation method according to claim 12, <13> Each of the steps is performed continuously or intermittently while the subject is sleeping. <1> from <12> 13. The blood pressure estimation method according to claim 12, <14> The method further comprises a step of determining whether the subject is in a sleep state. <1> from <13> 13. The blood pressure estimation method according to claim 12, <15> The method further comprises a step of estimating a degree of decrease in blood pressure of the peripheral capillary or arteriole from the blood pressure of the artery upstream of the arteriole as a blood pressure decrease index calculated from the arterial blood pressure index and the peripheral blood pressure index. <1> from <14> 13. The blood pressure estimation method according to claim 12, <16> The blood pressure reduction index is calculated from the power of the peripheral blood pressure index and the power of the de time, and each exponent of the power is a negative value. <15> The blood pressure estimation method according to claim 1 . <17> a sensing device having a photoplethysmographic sensor for acquiring a photoplethysmographic signal from a peripheral blood vessel of a subject; a computer having a signal processing device which calculates a peripheral blood pressure index which is an index of the blood pressure of the peripheral capillaries or arterioles based on the steepness of the rise of the photoelectric pulse wave signal, and estimates the blood pressure of the subject using the peripheral blood pressure index and a peak time difference de between the d wave and the e wave in an accelerated pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal; A biological information measuring system comprising: <18> The signal processing device calculates the peripheral blood pressure index from the photoelectric pulse wave signal acquired by the photoelectric pulse wave sensor for at least the capillaries in the periphery, and calculates the de time from the photoelectric pulse wave signal acquired by the photoelectric pulse wave sensor for at least the arteriole in the periphery. <17> The biological information measuring system according to claim 1 . <19> The signal processing device is characterized in that it estimates the blood pressure of the subject from the power of the peripheral blood pressure index and the power of de time. <18> The biological information measuring system according to claim 1 . <20> The signal processing device is characterized in that it estimates the blood pressure of the subject by further using the ae time, which is the peak time difference between the a wave and the e wave in an acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal. <17> from <19> 13. A biological information measuring system according to claim 12, wherein [Explanation of symbols]

[0160] 10... Biometric information measuring system, 20... Sensing device, 21... Biometric sensor, 211... Photoplethysmographic sensor, 211a... Green LED (first light source), 211b... Near-infrared LED (second light source), 211c... Light receiving element, 22... Control circuit, 23... Communication module, 24... Acceleration sensor, 25... Housing, 30... Computer, 31... Communication module, 32... Signal processing device Cross-reference to related applications

[0161] This application claims priority based on Patent Application No. 2022-063117 filed with the Japan Patent Office on April 5, 2022, and Patent Application No. 2022-128972 filed with the Japan Patent Office on August 12, 2022, the entire disclosures of which are incorporated by reference in their entirety herein.

Claims

1. acquiring a photoplethysmographic signal of a peripheral blood vessel of the subject using a photoplethysmographic sensor; calculating a peripheral blood pressure index, which is an index of blood pressure in the peripheral capillaries or arterioles, based on steepness characterized by information on the width of the first peak that appears within one beat of the waveform of the velocity pulse wave signal obtained by first differentiating the photoelectric pulse wave signal of the rising edge of the photoelectric pulse wave signal, or information on the peak value of the a-wave of the acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal and the maximum amplitude value of the photoelectric pulse wave signal, or information on the peak difference (a-b) and peak difference (a-d) when the peak values ​​of the a-wave, b-wave, c-wave and d-wave of the acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal are a, b, c and d, respectively; estimating the blood pressure of the subject using the de time, which is the peak time difference between the d wave and the e wave in an accelerated pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal, and the peripheral blood pressure index, based on the relationship that the blood pressure increases as the de time and the peripheral blood pressure index decrease; A blood pressure estimation method performed by a vital information measuring system.

2. 2. The blood pressure estimation method according to claim 1, wherein the peripheral blood pressure index is calculated from the photoelectric pulse wave signal acquired by the photoelectric pulse wave sensor for at least the capillaries in the periphery, and the de time is calculated from the photoelectric pulse wave signal acquired by the photoelectric pulse wave sensor for at least the arterioles in the periphery.

3. 3. The blood pressure estimation method according to claim 1, further comprising estimating the magnitude of the subject's blood pressure from the power of the peripheral blood pressure index and the power of de time.

4. 3. The blood pressure estimation method according to claim 1, further comprising: estimating the blood pressure of the subject based on a relationship that the blood pressure increases as the ae time decreases, further using an ae time, which is the peak time difference between the a-wave and the e-wave in an acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal,

5. 3. The blood pressure estimation method according to claim 1, wherein the blood pressure of the subject is a systolic blood pressure.

6. 3. The blood pressure estimation method according to claim 1, wherein the blood pressure of the subject is a diastolic blood pressure.

7. 3. The blood pressure estimation method according to claim 1, further comprising the steps of: acquiring a height from the heart of a measurement site of the subject at which the photoelectric pulse wave signal is measured by the photoelectric pulse wave sensor; and determining a correlation between the subject's blood pressure and the pulse wave feature amount from at least two measurement positions that are at different heights from the heart of the subject based on the acquired heights of the measurement site of the subject from the heart and from changes in the pulse wave feature amount at the at least two measurement positions, and correcting the subject's blood pressure estimate using the determined correlation.

8. 3. The blood pressure estimation method according to claim 1, wherein the peripheral blood pressure index includes information regarding the width of a peak that appears first within one beat of a waveform of a velocity pulse wave signal obtained by first differentiating the photoelectric pulse wave signal, or information regarding the peak value of the a-wave of an acceleration pulse wave signal obtained by second differentiating the photoelectric pulse wave signal and a maximum amplitude value of the photoelectric pulse wave signal, or information regarding a peak difference (a-b) and a peak difference (a-d) when the peak values ​​of the a-wave, b-wave, c-wave and d-wave of an acceleration pulse wave signal obtained by second differentiating the photoelectric pulse wave signal are a, b, c and d, respectively.

9. 3. The blood pressure estimation method according to claim 1, wherein the photoelectric pulse wave sensor emits light in a wavelength band from blue to yellow-green from a first light source and emits light in a wavelength band from red to near-infrared from a second light source.

10. 10. The blood pressure estimation method according to claim 9, wherein in the photoelectric pulse wave sensor, a distance between the first light source and a light receiving element that receives reflected light of the light emitted from the first light source is set to 1 to 3 mm, and a distance between the second light source and a light receiving element that receives reflected light of the light emitted from the second light source is set to 5 to 20 mm.

11. 3. The blood pressure estimation method according to claim 1, wherein the photoelectric pulse wave sensor is mounted on a device that is worn on a finger of the subject.

12. 3. The blood pressure estimation method according to claim 1, further comprising a step of determining a resting state of the subject whose photoplethysmographic signal is measured by the photoplethysmographic sensor.

13. 3. The blood pressure estimation method according to claim 1, wherein each of said steps is performed continuously or intermittently while the subject is sleeping.

14. 3. The blood pressure estimation method according to claim 1, further comprising a step of determining whether the subject is in a sleeping state.

15. The blood pressure estimation method according to claim 1 or 2, further comprising a step of estimating the degree of drop in blood pressure of the peripheral capillaries or arteriole from the blood pressure of the artery upstream of the arteriole as a blood pressure drop index calculated from the arterial blood pressure index and the peripheral blood pressure index.

16. 16. The method for estimating blood pressure according to claim 15, wherein the blood pressure drop index is calculated from the power of the peripheral blood pressure index and the power of the de time, and the exponents of the respective powers are negative values.

17. a sensing device having a photoplethysmographic sensor for acquiring a photoplethysmographic signal from a peripheral blood vessel of a subject; a computer having a signal processing device which calculates a peripheral blood pressure index which is an index of blood pressure in the peripheral capillaries or arterioles based on steepness characterized by information on the width of a peak which appears first within one beat of the waveform of a velocity pulse wave signal obtained by first differentiating the photoelectric pulse wave signal at the rising edge of the photoelectric pulse wave signal, or information on the peak value of the a-wave of an acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal and the maximum amplitude value of the photoelectric pulse wave signal, or information on a peak difference (a-b) and a peak difference (a-d) when the peak values ​​of the a-wave, b-wave, c-wave and d-wave of an acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal are a, b, c and d, respectively, and which estimates the blood pressure of a subject using a de time which is the peak time difference between the d wave and the e wave in an acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal, and the peripheral blood pressure index, based on the relationship that the blood pressure increases as the de time and the peripheral blood pressure index decrease; A biological information measuring system comprising:

18. The bioinformation measuring system according to claim 17, characterized in that the signal processing device calculates the peripheral blood pressure index from the photoelectric pulse wave signal acquired by the photoelectric pulse wave sensor for at least the capillaries in the periphery, and calculates the de time from the photoelectric pulse wave signal acquired by the photoelectric pulse wave sensor for at least the arterioles in the periphery.

19. 19. The biological information measuring system according to claim 17, wherein the signal processing device estimates the blood pressure of the subject from the power of the peripheral blood pressure index and the power of de time.

20. The signal processing device according to claim 17 or 18, further using an ae time, which is the peak time difference between the a wave and the e wave in an acceleration pulse wave signal obtained by second-order differentiation of the photoelectric pulse wave signal, to estimate the subject's blood pressure based on the relationship that as the ae time becomes shorter, the blood pressure becomes higher.

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