Biological information detector, biological information processing device, and biological information processing method

Abstract

To provide a biological information detector, a biological information processing device, and a biological information processing method that can reduce the influence of the body motion noise contained in sensing data of biological information and detect the biological information with high accuracy.SOLUTION: A biological information detector includes: a biological information sensor for measuring biological information; multiple body motion information sensors for measuring body motion information; and a detector for detecting the biological information on the basis of output from the biological information sensor and output from the multiple body motion information sensors.SELECTED DRAWING: Figure 1A

Description

[Technical Field]

[0001] The present invention relates to a biological information detection device, a biological information processing device, and a biological information processing method. [Background technology]

[0002] When biological information during daily life is measured as an observation signal using a sensor (e.g., a wearable device), the observation signal may contain body movement noise due to body movement. It is known that the noise contained in a pulse wave sensor includes body movement noise. For example, in the case of a biological information detection device worn on the wrist of a subject, a movement such as swinging one's arms can cause body movement noise, but this arm swing can be detected by a body movement sensor such as an acceleration sensor. Therefore, if the biological information detection device is operated in single sensor mode and noise reduction processing is performed using body movement information from the body movement sensor, body movement noise caused by arm swinging can be reduced to a certain extent (e.g., if the arm swing is not vigorously or is periodic). The noise reduction processing here is, for example, adaptive filtering.

[0003] For example, Patent Document 1 discloses a device for evaluating biological function that includes a first sensor for sensing biological information and a second sensor for acquiring the external noise, calculates the difference between the first and second sensors, and removes the external noise from the first sensor based on the difference. While the first sensor reliably acquires biological information, the second sensor can accurately acquire the external noise, since the biological information is subject to external noise. Patent Document 2 also discloses a biological function evaluation device that includes a biological signal acquisition unit for acquiring biological signals from a subject and a body movement detection unit for detecting the subject's body movements. Summary of the Invention [Problem to be solved by the invention]

[0004] However, filtering by circuitry alone (for example, Patent Document 1) is difficult to remove body movement noise when the frequency patterns are similar, and the processing becomes complicated. Furthermore, Patent Document 2 does not mention accurately detecting body movement information at the position of the heart rate sensor or pulse wave sensor.

[0005] The present invention has been made in consideration of the above, and aims to provide a biometric information detection device, a biometric information processing device, and a biometric information processing method that can reduce the influence of body movement noise contained in sensing data of biometric information and detect biometric information with high accuracy. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the objectives, the present invention comprises a biometric information sensor that measures biometric information, a plurality of body movement information sensors that measure body movement information, and a detection unit that detects the biometric information based on the output of the biometric information sensor and the output of the plurality of body movement information sensors. [Effects of the Invention]

[0007] According to the present invention, it is possible to reduce the influence of body movement noise contained in sensing data of biological information, and to detect biological information with high accuracy. [Brief explanation of the drawings]

[0008] [Figure 1A] FIG. 1A is a diagram showing an example of the configuration of a body movement noise reduction system to which a biological information detection device according to this embodiment is applied. [Figure 1B] FIG. 1B is a diagram showing an example of device arrangement in the body movement noise reduction system according to this embodiment. [Figure 2] FIG. 2 is a diagram for explaining an example of a process for detecting biological information in the body movement noise reduction system according to this embodiment. [Figure 3] FIG. 3 is a diagram for explaining an example of a process for detecting biological information in the body movement noise reduction system according to this embodiment. [Figure 4] FIG. 4 is a diagram for explaining an example of a process for detecting biological information in the body movement noise reduction system according to this embodiment. [Figure 5] FIG. 5 is a diagram for explaining an example of a process for detecting biological information in the body movement noise reduction system according to this embodiment. [Figure 6] FIG. 6 is a diagram for explaining an example of a process for detecting biological information in the body movement noise reduction system according to this embodiment. [Figure 7] FIG. 7 is a diagram for explaining an example of a process for detecting biological information in the body movement noise reduction system according to this embodiment. [Figure 8] FIG. 8 is a diagram for explaining an example of a detection process of biological information in the body movement noise reduction system according to the first modification. DETAILED DESCRIPTION OF THE INVENTION

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of a biological information detection device, a biological information processing device, and a biological information processing method will be described in detail with reference to the accompanying drawings.

[0010] First, an example of an overview of a biological information detection device, a biological information processing device, and a biological information processing method according to the present embodiment will be described. Wearable devices that sense sensing data, such as vital data, are affected by body movements associated with human body movement when detecting vital data, which can result in unwanted noise being mixed into the detected vital data. As a result, there are concerns that the measurement accuracy of the sensing data will decrease and stable measurement will be impossible. Furthermore, even if an optimal location for detecting the sensing data can be found to reduce the influence of this body movement noise, the detection sensitivity of the sensing data itself will also decrease, resulting in a trade-off with sensitivity, making stable detection difficult. Furthermore, even if the frequency of body movement noise is reduced using signal processing filtering, it is impossible to remove it if the frequency bands are close to each other.

[0011] Therefore, in this embodiment, multiple devices are arranged adjacent to the sensing target site at a predetermined interval (predetermined dimension) so as to sandwich the device that detects the original biological information, and the body movement noise generated in the device that detects the original biological information can be back-calculated (estimated) from the body movement noise generated in these multiple devices. As a result, the influence of the body movement noise is reduced by the difference between this back-calculated body movement noise and the original biological information, and the biological information is detected with high accuracy. The body movement noise generated by the device that detects the biological information and the multiple devices sandwiching it has different magnitudes. Therefore, this magnitude difference is directly removed by hardware from the difference between the noise generated by the multiple devices and the noise generated by the device that detects the original biological information.

[0012] In other words, in this embodiment, a device that detects biological information such as pulse waves from a living body is attached to the body, and multiple peripheral devices with the same characteristics are arranged at a predetermined interval around the area where the device that detects the biological information actually detects the biological information (preferably an area that hardly contributes to the biological information), and these multiple peripheral devices detect body movement noise that has a similar pattern but different magnitude to the body movement noise added to the actual biological information, and this different magnitude body movement noise is used to remove the body movement noise from the device that detects the actual biological information. Here, even if the peripheral device is close to the device that senses the biological information and the noise from the peripheral device is equal to the noise from the device that senses the biological information, this embodiment can remove the body movement noise from the device that detects the actual biological information.

[0013] Furthermore, in this embodiment, peripheral devices are arranged at a predetermined interval (known dimension) relative to the device for detecting biological information, and the relationship (dimension ratio) calculated from this predetermined interval is used to predict the magnitude of body movement noise on the device that detects the actual biological information, and by taking the difference from the device that detects the actual biological information, the body movement noise can be efficiently removed with a simple hardware configuration. Here, even if the peripheral device is close to the device that senses the biological information and the noise on the peripheral device is equal to the noise on the device that senses the biological information, the noise on the peripheral device is added and the peripheral devices are arranged at equal intervals, resulting in a coefficient of 1 / 2, so the noise on the device that senses the biological information is ultimately predicted to be equal to the noise on each of the peripheral devices.

[0014] This allows stable, highly accurate detection of biological information without being affected by body movement noise, even if it is present at a frequency (periodicity) close to that of biological information. Furthermore, the device arrangement and hardware circuitry alone can sufficiently reduce body movement noise with almost no signal processing (or a simple configuration without any ingenuity), enabling highly accurate detection of biological information. Furthermore, real-time processing is possible because complex signal processing is not required.

[0015] Furthermore, since it is possible to predict body movement noise on a device that detects biological information almost regardless of the direction in which the body movement noise occurs, highly accurate detection of biological information is possible.As an example of application, by subdividing (arraying) devices arranged around a device that detects biological information, it is possible to predict body movement noise added from various directions, reducing the effects of distortion direction and angle, thereby enabling highly accurate removal of body movement noise and achieving highly accurate detection.

[0016] Next, specific examples of a biological information detection device, a biological information processing device, and a biological information processing method according to this embodiment will be described with reference to Figures 1A to 8. Figure 1A is a diagram showing an example of the configuration of a body movement noise reduction system to which a biological information detection device according to this embodiment is applied. Figure 1B is a diagram showing an example of the arrangement of devices in the body movement noise reduction system according to this embodiment. As shown in Figure 1A, the body movement noise reduction system according to this embodiment includes devices A to C, an addition / subtraction circuit 4, a voltage divider circuit 5, a comparison circuit 6, a differential AMP 7, and an A / D conversion circuit 8.

[0017] Device A is an example of a biometric information sensor that measures (detects) biometric information. Devices B and C are examples of multiple body movement information sensors that measure (detect) body movement noise (body movement information). Devices B and C are arranged on either side of device A. This allows accurate estimation of body movement noise at the position of device A based on the outputs of devices B and C.

[0018] Here, devices A to C are, for example, body movement sensors, heart rate sensors, pulse wave sensors, etc. The body movement sensors are, for example, acceleration sensors, pressure sensors, etc., and are attached to the forehead, ears, neck, etc. of the person being measured to monitor the person's movements. Movements to be monitored include swallowing saliva, sneezing, yawning, deep breathing, and dozing off while rowing a boat. The body movement sensors may be wearable sensors such as hairbands, neckbands, and patches.

[0019] The heart rate sensor and pulse wave sensor can be of any type that measures electrocardiograms or pulse waves. Examples include an electrocardiograph, which places two or more electrodes in contact with the body surface to obtain an electrocardiogram from the potential difference, and a photoplethysmograph, which irradiates light onto the skin surface and measures reflected or transmitted light. Alternatively, a wearable sensor can be used, which measures pulse waves by attaching an acceleration sensor or pressure sensor to the skin directly above an artery.

[0020] Wearable pulse wave sensors include clip-on types that are attached to the fingertips, wrist-wrapped types that are worn around the wrist, earring-type types that are attached to the earlobes, and patch-type types that are attached to the temples.

[0021] 1B, an example of the arrangement of device A and device B will be described. Here, an example of the arrangement of device A and device B will be described, but device A and device C may also be arranged in a similar manner.

[0022] For example, the body movement noise reduction system may place an absorber or convex medium that does not easily transmit distortion caused by pulse waves, etc., between device A and device B. This reduces noise caused by the structure of the device. Alternatively, for example, the body movement noise reduction system may place a concave groove between device A and device B, and place an absorber that does not easily transmit distortion within the concave groove.

[0023] Furthermore, device A and devices B and C may be components separated from or integrated into the same device. It is also desirable that device A and devices B and C have the same sensitivity and temperature characteristics. This allows devices B and C to adapt to temperature changes in device A, variations between elements, and aging, thereby achieving highly accurate and stable detection. Furthermore, the influence of differences in detection sensitivity due to distortion caused by body movement can be significantly reduced.

[0024] The adder-subtractor circuit 4 adds the output of device B and the output of device C. Alternatively, the adder-subtractor circuit 4 calculates the difference between the output of device B and the output of device C.

[0025] The voltage divider circuit 5 divides the sum of the output of device B and the output of device C based on the distance or the ratio of the distances from device A to devices B and C. For example, the voltage divider circuit 5 is a variable resistor that adjusts the output (signal level) of the adder / subtractor circuit 4.

[0026] Comparison circuit 6 is an example of an estimation means for estimating body movement noise at the position of device A based on the outputs of devices B and C. In this embodiment, comparison circuit 6 estimates body movement noise at the position of device A based on the distance or distance ratio from device A to each of devices B and C. This makes it possible to accurately estimate body movement noise at the position of device A based on the distance or distance ratio from device A to each of devices B and C.

[0027] The differential AMP 7 is an example of a detection means that detects biological information based on the output of device A and the body movement noise estimated by the comparison circuit 6. This allows accurate detection of biological information by estimating body movement noise at the position of device A based on the outputs of devices B and C. The differential AMP 7 is also an example of a correction unit that detects the difference between the output of device A and the outputs of devices B and C at predetermined intervals and corrects the output of device A. This allows devices B and C to follow changes over time in device A. Specifically, by configuring elements (e.g., resistors) of circuits such as the differential AMP 7 to be variable and configuring a calibration configuration, the effects of changes over time and positional deviations in devices A to C can be reduced relative to the initial values, allowing stable and highly accurate detection of biological information.

[0028] The A / D conversion circuit 8 performs A / D conversion processing on the waveform of the biological information detected by the differential AMP 7 .

[0029] That is, the adding / subtracting circuit 4, the voltage dividing circuit 5, the comparing circuit 6, and the differential AMP 7 are an example of a detecting unit that detects biological information based on the output (biological information) of device A and the outputs (body movement noise) of devices B and C. This makes it possible to accurately detect biological information based on the output of device A and the outputs of devices B and C. In this embodiment, the detecting unit is realized by a circuit unit including the adding / subtracting circuit 4, the voltage dividing circuit 5, the comparing circuit 6, and the differential AMP 7, but it can also be realized by a computer.

[0030] 2 and 3 are diagrams for explaining an example of a detection process of biological information in a body movement noise reduction system according to this embodiment. In this embodiment, as shown in Fig. 3, the body movement noise reduction system has a device A that detects biological information (for example, a device that detects biological information at the carotid artery), and multiple (for example, two) devices B and C that are arranged adjacent to and sandwiching device A with respect to a sensing target site (for example, the carotid artery) that is a target site for detecting biological information.

[0031] By arranging devices B and C at a predetermined distance from device A and sandwiching device A between devices B and C, strain is generated in the sensing target area. The body motion noise reduction system estimates the body motion noise present in the sensing target area (e.g., the carotid artery) using the distance attenuation of the adjacent distance (between device B and device C) in the direction in which near-surface displacement occurs due to stress deformation caused by the strain, and calculates the difference between the estimated body motion noise and the sensing target (biological information) (e.g., biological information detected by differential AMP7). This reduces the effects of body motion noise using only the hardware device configuration.

[0032] The body movement noise reduction system is also configured to back-calculate the noise level of device A, which detects biological information, from the stress propagation loss caused by devices B and C that sandwich device A, and to subtract the body movement noise using only the addition / subtraction circuit 4 and the parameter constants of that circuit. The example shown in Figure 2 is for a case where devices A and B and devices A and C are arranged at equal intervals, and the body movement noise reduction system estimates half of the sum of the outputs of devices B and C as the body movement noise present on device A, parameterizes it as a circuit constant, subtracts the body movement noise from the biological information using differential AMP 7, and outputs only the original biological information as sensing data.

[0033] That is, the body movement noise reduction system combines the outputs of device B and device C in the first stage addition / subtraction circuit 4, then divides the voltage by a factor of 1 / 2 in voltage divider circuit 5, and calculates the difference with the output of device A in differential AMP 7, thereby subtracting and eliminating body movement noise in hardware.

[0034] When distortion occurs from the device B side, the displacement (sensitivity) due to distortion over distance attenuates in the order of device B, device A, and device C, and the displacement occurring in the output of device A is calculated backward from the displacement of the outputs of devices B and C. This can be shown in a circuit by adding the displacement of the output of device B and adding the displacement of the output attenuated from device B to device C, then dividing the voltage and introducing it as Vout0' along with the output of device A to differential AMP7, thereby subtracting only body movement noise using only the configuration of devices A to C and the hardware circuit. Here, Vout is waveform data containing only biological information.

[0035] In this way, by using a simple hardware circuit configuration and devices A to C that detect multiple pieces of biometric information arranged at predetermined intervals, it is possible to reduce the effects of body movement noise without performing complex digital or signal processing on the biometric information.

[0036] Furthermore, external (body movement) noise, which is unnecessary when detecting biological information, has a frequency (periodicity) close to the frequency of the biological information signal, and simple filtering alone cannot sufficiently remove the noise, forcing signal processing in a complex time domain to be performed, which makes it impossible to keep up with real-time processing and reduces the detection performance of the biological information.In contrast, in this embodiment, highly accurate and stable real-time processing can be achieved with just a hardware configuration consisting of a simple addition / subtraction circuit and multiple devices A to C that detect biological information.

[0037] Fig. 4 is a diagram for explaining an example of the detection process of biological information in the body movement noise reduction system according to this embodiment. In the example shown in Fig. 2, regardless of the direction of stress, half of the sum of the output of device B and the output of device C is output as the noise level of device A, and body movement noise is removed based on the difference from the output of device A. The example shown in Fig. 4 is a circuit configuration of the body movement noise reduction system in the case where multiple adjacent devices B and C are not arranged symmetrically on either side of device A, which senses biological information (where they are arranged asymmetrically).

[0038] The body movement noise reduction system calculates the difference between the output of device B and the output of device C, then divides this difference by a coefficient ratio (coefficient value at the interval ratio) according to the device interval between devices B and C, offsets the output of device B by the difference (waveform) after division, and finally outputs the difference between the output of device B and the output of device A. Although real-time performance is slightly reduced, it becomes possible to move device B as far away from device A as necessary when device A, which detects biological information, is affected by bodily movement, particularly individual differences between people, and device B is more affected by the biological information of device A than device C.

[0039] Specifically, the body movement noise reduction system divides the output after the differential CB between devices C and B by a ratio (N:1) based on the distance between devices B and C, and outputs the result. The waveform of device B is added to this output as an offset to obtain an output waveform (Vout), and by calculating the difference between this output and the output of device A, the body movement noise contained in the output of device A is reduced and removed. The flow of electricity is as follows: SWB and SWC are turned ON, then immediately after that SWC is turned OFF, and SWA, SWB, and SWC are turned ON.

[0040] FIG. 5 is a diagram illustrating an example of the detection process of biological information in the body movement noise reduction system according to this embodiment. As shown in FIG. 5, when the center of device A detecting biological information is shifted relative to the sensing target body part, the positions of the multiple devices B and C sandwiching it are also shifted relatively. According to the body movement noise reduction system according to this embodiment, the noise itself can be reduced, so there is little decrease in S / N due to the shift. In this case, although the relative sensitivity changes depending on the direction of the shift, it is possible to back-calculate the noise on device A as the noise determined by the distance between devices B and C relative to device A, and ultimately remove the noise based on the difference from device A. However, the S / N will be slightly reduced.

[0041] Fig. 6 is a diagram for explaining an example of the detection process of biological information in the body movement noise reduction system according to this embodiment. As shown in Fig. 6, even if there is no device A for detecting biological information, and only peripheral devices B and C are configured, biological information can be detected. However, in this case, digital processing is the main method, which necessitates complex signal processing, and real-time processing becomes difficult, making stable measurement of anything other than SN difficult.

[0042] FIG. 7 is a diagram illustrating an example of a detection process for biological information in a body movement noise reduction system according to this embodiment. As shown in FIG. 7, when only device B exists near device A, which is the device that is supposed to detect the biological information, it is possible to detect the biological information by simply detecting the difference between device A and device B. However, with only the simple difference between device A and device B, if the noise levels of device A and device B are equal, the S / N ratio is good. However, since the level of body movement noise caused by distortion varies depending on the location (distance), the S / N ratio is almost never equal. Even if the biological information can be detected, the S / N ratio decreases. Furthermore, with respect to deviations, the sensing level of the biological information further decreases, and the noise becomes asymmetric, resulting in a further decrease in the S / N ratio.

[0043] In this way, according to the body movement noise reduction system of this embodiment, by estimating the body movement noise at the position of device A based on the outputs of devices B and C, the influence of body movement noise contained in the sensing data of the biometric information can be reduced, and the biometric information can be detected with high accuracy.

[0044] (Variation 1) Fig. 8 is a diagram for explaining an example of the detection process of biological information in the body movement noise reduction system according to Modification 1. As shown in Fig. 8, the body movement noise reduction system according to this modification has a configuration in which a plurality of arrayed and subdivided devices B1, B2, C1, and C2 of the same elements are arranged around device A that detects biological information, so as to sandwich the device A, thereby being able to respond to the directionality of body movement due to body movement.

[0045] Depending on the directionality of strain on the skin surface and superficial muscles due to body movement, the sensitivity of devices B and C, which are arranged around device A, changes differently depending on the position at which strain is applied. Therefore, in order to accurately detect the sensitivity of parts depending on the directionality of strain, devices B and C, which have the same elements, are finely divided and placed around device A, which detects biological information, to improve the detection sensitivity and accuracy by part.

[0046] For example, aspects of the present invention are as follows. <1> a biological information sensor that measures biological information; a plurality of body movement information sensors for measuring body movement information; a detection unit that detects the biological information based on an output of the biological information sensor and outputs of the plurality of body movement information sensors; A biological information detection device comprising: <2> The detection unit an estimation means for estimating the body movement information at the position of the biological information sensor based on outputs of the plurality of body movement information sensors; a detection means for detecting the biological information based on an output of the biological information sensor and the body movement information estimated by the estimation means; Equipped with <1> The biological information detection device described. <3> two of the body movement information sensors included in the plurality of body movement information sensors are arranged so as to sandwich the biological information sensor; <2> The biological information detection device described. <4> the estimation means estimates the body movement information at the position of the biological information sensor based on the distance from the biological information sensor to each of the two body movement information sensors or the ratio of the distances. <3> The biological information detection device described. <5> The biological information sensor and the body movement information sensor are components separated from or integrated into a single device. <1> from <4> 10. The biological information detection device according to claim 9, wherein <6> a correction unit that detects a difference between the output of the biological information sensor and the output of the body movement information sensor at predetermined intervals and corrects the output of the biological information sensor; <1> from <5> 10. The biological information detection device according to claim 9, wherein <7> an estimation means for estimating body movement information at positions of the biological information sensors that measure the biological information based on outputs of the body movement information sensors that measure the body movement information; a detection means for detecting the biological information based on an output of the biological information sensor and the body movement information estimated by the estimation means; A biological information processing device comprising: <8> A biometric information processing method executed by a biometric information processing device that processes biometric information, an estimation step of estimating body movement information at positions of biological information sensors that measure biological information based on outputs of the body movement information sensors that measure the body movement information; a detecting step of detecting the biological information based on an output of the biological information sensor and the body movement information estimated by the estimation means; A biometric information processing method comprising: [Explanation of symbols]

[0047] 4 Addition / subtraction circuit 5 Voltage divider circuit 6 Comparison circuit 7 Differential AMP 8 A / D conversion circuit A, B, C devices [Prior art documents] [Patent documents]

[0048] [Patent Document 1] Japanese Patent Application Laid-Open No. 2016-129635 [Patent Document 2] Japanese Patent Publication No. 2020-92817

Claims

1. a biological information sensor that measures biological information; a plurality of body movement information sensors for measuring body movement information; a detection unit that detects the biological information based on an output of the biological information sensor and outputs of the plurality of body movement information sensors; A biological information detection device comprising:

2. The detection unit an estimation means for estimating the body movement information at the position of the biological information sensor based on outputs of the plurality of body movement information sensors; a detection means for detecting the biological information based on an output of the biological information sensor and the body movement information estimated by the estimation means; The biological information detection device according to claim 1 , further comprising:

3. The biological information detection device according to claim 2 , wherein two of the body movement information sensors included in the plurality of body movement information sensors are arranged so as to sandwich the biological information sensor.

4. 4. The biological information detection device according to claim 3, wherein the estimation means estimates the body movement information at the position of the biological information sensor based on distances from the biological information sensor to each of the two body movement information sensors or a ratio of the distances.

5. 2. The biological information detection device according to claim 1, wherein the biological information sensor and the body movement information sensor are components separated from or integrated into a single device.

6. The biological information detecting device according to claim 1 , further comprising a correction unit that detects a difference between an output of the biological information sensor and an output of the body movement information sensor at predetermined intervals and corrects the output of the biological information sensor.

7. an estimation means for estimating body movement information at positions of the biological information sensors that measure the biological information based on outputs of the plurality of body movement information sensors that measure the body movement information; a detection means for detecting the biological information based on an output of the biological information sensor and the body movement information estimated by the estimation means; A biological information processing device comprising:

8. A biometric information processing method executed by a biometric information processing device that processes biometric information, an estimation step of estimating body movement information at positions of biological information sensors that measure biological information based on outputs of the body movement information sensors that measure the body movement information; a detecting step of detecting the biological information based on an output of the biological information sensor and the estimated body movement information; A biometric information processing method comprising:

Images