Feature quantity acquisition apparatus and feature quantity acquisition method

Abstract

To provide a feature quantity acquisition apparatus and a feature quantity acquisition method capable of suitably acquiring feature quantities from a pulse wave.SOLUTION: A feature quantity acquisition apparatus comprises: an acquisition unit that acquires a pulse wave; and a calculation unit that specifies a first point that is a point of a maximum value in each cycle of the pulse wave and a second point that is a point of a minimum value, detects a maximum peak point that is a point of a maximum value of a first-order differential waveform of the pulse wave in a partial section in a section between a time when the first point appears and a time when the second point appears first after the first point, specifies a point of the pulse wave at the time when a maximum point of the first-order differential waveform appears as a feature point, and calculates a feature quantity related to biometric information based at least on a value and a time of the feature point.SELECTED DRAWING: Figure 7

Description

[Technical Field]

[0001] The present embodiment relates to a feature acquisition device and a feature acquisition method. [Background technology]

[0002] Conventionally, it has been possible to obtain feature quantities related to biological information such as blood pressure from a pulse wave. For example, an index called Augmentation Index (hereinafter, AIx) can be used as a feature quantity. AIx is obtained by dividing the pulse wave value at the second-largest maximum point (referred to as the second maximum point) appearing in one pulse wave cycle by the pulse wave value at the first-largest maximum point (referred to as the first maximum point) appearing in one pulse wave cycle. AIx can be used as an index reflecting the degree of aortic stiffness associated with aging. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-058583 Summary of the Invention [Problem to be solved by the invention]

[0004] However, depending on the type of sensor used to detect the pulse wave and the way the subject uses the pulse wave detection device, it is not always possible to detect a pulse wave with high accuracy. If the accuracy of the detected pulse wave is poor, the second maximum point may not appear in the detected pulse wave. In such cases, it is difficult to obtain feature quantities using the second maximum point, such as AIx.

[0005] An object of the present invention is to provide a feature acquisition device and a feature acquisition method that can suitably acquire feature values ​​from a pulse wave. [Means for solving the problem]

[0006] According to the present invention, a feature acquisition device includes an acquisition unit that acquires a signal including a pulse wave, and a calculation unit that identifies a first point that is a maximum value point and a second point that is a minimum value point in each cycle of the pulse wave, detects a maximum point that is a point of the largest maximum value of a first-order derivative waveform of the pulse wave in a second section that is a part of a first section that is a section between a time when the first point appears and a time when the second point first appears after the first point, identifies a third point that is a point on the pulse wave at the time when the maximum point of the first-order derivative waveform appears, as a feature point, and calculates a feature related to biological information based on at least the value of the feature point and the time. [Effects of the Invention]

[0007] The present invention has an effect of providing a feature acquisition device and a feature acquisition method that can suitably acquire feature values ​​from a pulse wave. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing an example of a waveform of a volume pulse wave. [Figure 2] FIG. 2 is a diagram for explaining changes in the detected volume pulse wave depending on the detection accuracy. [Figure 3] FIG. 3 is an external view of the smart watch according to the embodiment when worn on a human body. [Figure 4] FIG. 4 is a cross-sectional view of the smartwatch and arm according to the embodiment shown in FIG. 3 taken along the YZ plane. [Figure 5] FIG. 5 is a schematic diagram showing an example of the internal configuration of a smartwatch according to an embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of the functional configuration of the microcomputer unit included in the sensor module according to the embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of an algorithm for identifying a feature point corresponding to a second maximum point, which is executed by the calculation unit according to the embodiment. [Figure 8]FIG. 8 is a diagram for explaining a plurality of types of feature amounts calculated by the calculation unit according to the embodiment. [Figure 9] FIG. 9 is a flowchart showing the operation of the microcomputer unit according to the embodiment. [Figure 10] FIG. 10 is a diagram for explaining an example of a method for identifying the feature points FP1 and FP2 according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] A pulse wave is a representation of changes in the volume of blood vessels over time. There are various methods for detecting pulse waves, such as using a photoelectric sensor or a piezoelectric sensor. This pulse wave is also called a volume pulse wave.

[0010] 1 is a diagram showing an example of the waveform of a volume pulse wave VW. The volume pulse wave VW has a waveform in which a maximum point (i.e., the first maximum point shown in FIG. 1) having the largest maximum value and a minimum point (i.e., the first minimum point shown in FIG. 1) having the smallest minimum value appear periodically within one cycle of the waveform.

[0011] In this specification, the time interval from a first minimum point to the next first minimum point is treated as one cycle of the volume pulse wave VW. However, the definition of a cycle is not limited to this. The interval from a first maximum point to the next first maximum point may also be treated as one cycle of the volume pulse wave VW. Hereinafter, one cycle of the volume pulse wave VW will be referred to as one cycle interval.

[0012] The volume pulse wave VW in one cycle section includes multiple types of feature points, such as a first maximum point and a second maximum point. A feature point is a point whose coordinate value is a feature amount, or a point whose value calculated based on the coordinate value is a feature amount. These feature amounts are related to biological information and can therefore be used to estimate biological information.

[0013] However, if the detection accuracy of the volume pulse wave VW is low, the second maximum point among the multiple types of feature points may not be observed, which may result in the feature amount, such as AIx, that should be obtained using the value of the volume pulse wave at the second maximum point not being obtained.

[0014] A decrease in the accuracy of detecting the volume pulse wave can be caused by various factors, such as when the sensitivity of the sensor that detects the volume pulse wave is not high, or when the user of the sensor does not use the sensor properly and the sensor is misaligned when worn.

[0015] 2 is a diagram illustrating changes in the detected volume pulse wave depending on the detection accuracy, showing a volume pulse wave VW1 in one cycle obtained when the detection accuracy is high, a volume pulse wave VW3 in one cycle obtained when the detection accuracy is low, and a volume pulse wave VW2 in one cycle obtained when the detection accuracy is medium.

[0016] The volume pulse wave VW1 clearly shows a first maximum point P1 and a second maximum point P2. The first maximum point P1 is a peak caused by the pressure generated when blood is pumped out by the heartbeat. The second maximum point P2 is a peak of a composite wave generated when the pressure that generated the first maximum point P1 is reflected back from the periphery.

[0017] The first maximum point P1 appears in the volume pulse wave VW2. However, at the time when the second maximum point P2 should appear, a point P2' appears instead, which is a blunted, downward-sloping point.

[0018] The first maximum point P1 appears in the volume pulse wave VW3. However, no distinctive change appears in the waveform around the time when the second maximum point P2 should appear. In other words, the volume pulse wave VW3 does not indicate the presence of the second maximum point P2.

[0019] According to the embodiment, even if the second maximum point P2 in the volume pulse wave appears as a point P2' with a right-shoulder sloping downward due to a decrease in detection accuracy, the feature acquisition device identifies the point P2' with a right-shoulder sloping downward as the feature point corresponding to the second maximum point P2. A specific method for identifying the feature point corresponding to the second maximum point P2 will be described later.

[0020] Hereinafter, a smartwatch in which a feature acquisition device according to an embodiment is implemented will be described as an example. Note that the feature acquisition device is not limited to a smartwatch and may be implemented in any device.

[0021] FIG. 3 is an external view of the smart watch 1 according to the embodiment when worn on a human body.

[0022] The smartwatch 1 comprises a flat housing 10, a display device 11 attached to the surface of the housing, and a band 12 attached to the side of the housing. The housing 10 consists of a top surface, a bottom surface, and a side surface connecting the periphery of the top surface and the periphery of the bottom surface. In the figure, the housing is an approximately rectangular parallelepiped, with four side surfaces.

[0023] A band 12 is attached to one side and the other side of the housing 10. The band 12 is wrapped around the wearer's arm 200, thereby fixing the bottom of the housing 10 to the arm 200. A display device 11 is provided on the top surface of the housing 10, and the smart watch 1 outputs various types of image information to the display device 11. The wearer can visually confirm the various types of image information output to the display device 11.

[0024] In the following description, the direction in which the arm extends will be referred to as the +X axis direction, the direction from the bottom to the top of the two surfaces of the housing 10 will be referred to as the +Z axis direction, and the axis perpendicular to both the X axis and the Z axis will be referred to as the Y axis.

[0025] FIG. 4 is a cross-sectional view of the smartwatch 1 and wrist 200 shown in FIG. 3 in the YZ plane.

[0026] A radius 211 and an ulna 212 extend in the X-axis direction inside the arm 200. A radial artery 213 runs below the radius 211, and an ulnar artery 214 runs below the ulna 212. A tendon 215 runs subcutaneously at the lowest part of the cross section of the arm 200.

[0027] A sensor module 13 that detects a volume pulse wave is provided on the underside of the housing 10. Here, the sensor module 13 is assumed to be a type that detects a volume pulse wave using a photoelectric sensor.

[0028] The sensor module 13 includes a sensor substrate 130, one or more light receiving elements 131, and one or more light emitting elements 132. As an example, when the smartwatch 1 is worn, one light receiving element 131 is provided at the center of the surface of the sensor substrate 130 that faces the skin, and one light emitting element 132 is provided at a position away from the light receiving element 131 in the positive direction of the Y axis and at a position away from the light receiving element 131 in the negative direction. In other words, two light emitting elements 132 are provided at positions surrounding the light receiving element 131.

[0029] The number of light receiving elements 131 and the number of light emitting elements 132 provided on sensor substrate 130, and the arrangement of each element are not limited to the above example. In the example shown in Fig. 4, light receiving element 131 and two light emitting elements 132 are configured to come into contact with skin 201 when worn, but light receiving element 131 and two light emitting elements 132 may be covered with a light-transmitting member such as glass or transparent resin so as not to come into direct contact with skin 201.

[0030] Each light-emitting element 132 emits light selected from a wavelength band that is easily absorbed by hemoglobin in blood, for example, a wavelength band from green to near-infrared. Each light-emitting element 132 emits light of the same wavelength. The light-receiving element 131 can detect the light emitted by the light-emitting elements 132.

[0031] When the smartwatch 1 is worn by a wearer, the two light-emitting elements 132 emit light toward the skin 201. The light-receiving element 131 detects light that penetrates beneath the skin 201 and is incident on the light-receiving element 131, including light that has been reflected or scattered by subcutaneous tissue and returned. Because blood vessels, including the radial artery 213, are present beneath the skin, the amount of light received by the light-receiving element 131 increases or decreases due to the influence of the vascular volume pulse wave. The sensor module 13 acquires the volume pulse wave based on the change over time in the amount of light received by the light-receiving element 131. In other words, the sensor module 13 detects the volume pulse wave.

[0032] The sensor module 13 acquires various feature quantities related to biological information from the detected volume pulse wave, and outputs the acquired various feature quantities.

[0033] The sensor module 13 is an example of a feature acquisition device according to the embodiment.

[0034] FIG. 5 is a schematic diagram showing an example of the internal configuration of the smartwatch 1 according to the embodiment.

[0035] In addition to the display device 11 and the sensor module 13, the smart watch 1 also includes a processor 14 and a memory 15. The processor 14, the memory 15, the sensor module 13, and the display device 11 are electrically connected to a bus 16.

[0036] The sensor module 13 includes a light receiving element 131, two light emitting elements 132, a microcomputer unit 133, and a gain circuit .

[0037] The gain circuit 134 amplifies the signal from the light receiving element 131 .

[0038] The microcomputer unit 133 is an example of a processor according to the embodiment. The microcomputer unit 133 turns on the light-emitting element 132, stores the time transition of the signal received from the light-receiving element 131 via the gain circuit 134, and acquires a volume pulse wave based on the time transition of the stored signal.

[0039] Furthermore, the microcomputer unit 133 acquires various characteristic quantities from the volume pulse wave and outputs the acquired various characteristic quantities.

[0040] The memory 15 stores computer programs and data and functions as a work area for the processor 14. The memory 15 is, for example, a combination of volatile memory and nonvolatile memory. The volatile memory is, for example, a random access memory (RAM) and can function as a work area for the processor 14. The nonvolatile memory is, for example, a storage memory such as a solid state drive (SSD) or a hard disk drive (HDD) and can store computer programs and data in a nonvolatile manner. Note that the configuration of the memory 15 is not limited to this example.

[0041] The processor 14 is an arithmetic unit that implements various functions in accordance with a computer program, and is, for example, a CPU (Central Processing Unit).

[0042] The processor 14 controls the smartwatch 1 by executing a computer program pre-stored in the memory 15. As part of the control of the smartwatch 1, the processor 14 may calculate biometric information of the wearer (e.g., pulse rate, arteriosclerosis level, blood pressure, etc.) based on various feature quantities output from the sensor module 13. The processor 14 may display the biometric information obtained by the calculation on the display device 11.

[0043] FIG. 6 is a diagram showing an example of the functional configuration of the microcomputer unit 133 included in the sensor module 13 according to the embodiment.

[0044] The microcomputer unit 133 includes an acquisition unit 1330 , a calculation unit 1331 , and an output unit 1332 .

[0045] The acquisition unit 1330 acquires a signal including the volume pulse wave of the wearer of the smart watch 1 based on the time progression of the signal received from the light receiving element 131 via the gain circuit 134.

[0046] The calculation unit 1331 identifies multiple types of feature points, including the feature point corresponding to the second maximum point P2, based on the volume pulse wave acquired by the acquisition unit 1330. Then, the calculation unit 1331 calculates various feature amounts related to the biometric information based on the multiple types of feature points identified. The algorithm for identifying the feature point corresponding to the second maximum point P2 will be described later.

[0047] The output unit 1332 outputs the multiple types of feature amounts obtained by the calculations performed by the calculation unit 1331. In one example, the output unit 1332 outputs the multiple types of feature amounts to the processor 14.

[0048] FIG. 7 is a diagram for explaining an example of an algorithm for identifying a feature point corresponding to the second maximum point P2, which is executed by the calculation unit 1331 according to the embodiment.

[0049] In FIG. 7, the volume pulse wave VW in one cycle section is shown by a solid line. The vertical axis represents the signal value, e.g., voltage value. The signal value may be positive or negative. Section SC0 represents one cycle section. The maximum value of the volume pulse wave VW in one cycle section SC0 is a first maximum point P1. In this embodiment, the first maximum point P1 is one of multiple types of feature points. When describing the feature points, the first maximum point P1 will be referred to as feature point FP1.

[0050] The points at both ends of the volume pulse wave VW in one cycle section SC0 are first minimum points. In the embodiment, these first minimum points are also included in the multiple types of feature points. When describing feature points, the first minimum points are referred to as feature points FP2. Furthermore, when referring to the waveforms VW and DW in one cycle section SC0, the feature point FP2 at the beginning of that one cycle section SC0 is referred to as feature point FP2a, and the feature point FP2 at the end of that one cycle section SC0 is referred to as feature point FP2b.

[0051] Note that the feature point FP1 exists between the feature points FP2a and FP2b, and therefore the feature point FP2b can be considered to be the feature point FP2 that first appears after the feature point FP1 appears.

[0052] The calculation unit 1331 performs first-order differentiation on the volume pulse wave VW to obtain a differential waveform DW, which is the first-order differentiated volume pulse wave VW.

[0053] In Figure 7, the differentiated waveform DW is shown as a dotted line. The differentiated waveform DW rises sharply immediately after the time of characteristic point FP2a, reaches the maximum point P10 in one cycle section SC0, and then falls sharply. After the differentiated waveform DW reaches the maximum point P10, the signal value changes from positive to negative. Hereinafter, the change in the positive / negative state of the signal value is referred to as a zero crossing. At the time when the differentiated waveform DW crosses zero from the positive side to the negative side, a characteristic point FP1, which is the first maximum point P1, appears in the volume pulse wave VW.

[0054] 7, after feature point FP1, a point appears in the volume pulse wave VW where the second maximum point P2 is dulled and has a right-shoulder sloping shape. When such a point appears where the second maximum point P2 is dulled and has a right-shoulder sloping shape, a maximum point P11 appears at the same time in the differentiated waveform DW. The calculation unit 1331 detects the maximum point P11 that appears in the differentiated waveform DW, thereby identifying feature point FP3 corresponding to the second maximum point P2.

[0055] Note that multiple local maxima, including local maxima P11, can appear in the differential waveform DW. As mentioned above, the second local maxima P2 is a peak that occurs when the pressure that caused the first local maxima P1 is reflected back from the periphery. Therefore, the period in which the second local maxima P2 can appear, relative to the time when the first local maxima P1 appeared, is generally fixed, although this varies from person to person.

[0056] Therefore, the calculation unit 1331 sets a part of the section from the time when the first maximum point P1 appeared to the feature point FP2b, which is the feature point FP2 that appeared first after the feature point FP1 appeared, in which the maximum point P11 may appear but in which other maximum points besides the maximum point P11 are unlikely to appear, as the judgment valid section SCset in which the detection of the maximum point P11 is performed.

[0057] Specifically, the calculation unit 1331 sets, as the determination valid section SCset, a section of the section SC1 from the time when feature point FP1 appears to the time when feature point FP2b appears, excluding the section SCf of the first set percentage on the front side and the section SCb of the second set percentage on the rear side. In other words, the calculation unit 1331 specifies, as the determination valid section SCset, a time from the beginning of the section SC1 a time (also referred to as the first time) that is the first set percentage of the length of the section SC1, and a time from the end of the section SC1 a time (also referred to as the second time) that is the second set percentage of the length of the section SC1. The first set percentage and the second set percentage are time proportions based on the length of the section SC1. In other words, the ratio of the first time divided by the length of the section SC1 is the first set percentage, and the ratio of the second time divided by the length of the section SC1 is the second set percentage. The first time and the second time are shorter than the section SC1.

[0058] 7, the first set percentage is 10 percent, and the second set percentage is 50 percent. However, examples of the first set percentage and the second set percentage are not limited thereto. For example, the first set percentage may be 30 percent or less, 20 percent or less, 10 percent or less, or 15 percent or less. For example, the second set percentage may be 60 percent or less, or 40 percent or less.

[0059] The first set percentage and the second set percentage are set, for example, by the manufacturer of sensor module 13. The manufacturer of sensor module 13 detects the volume pulse wave of one or more subjects and acquires a differential waveform from the detected volume pulse wave, and, based on the acquired differential waveform, identifies a section of section SC1 in which maximum point P11 is likely to appear and in which other maximum points besides maximum point P11 are unlikely to appear. The manufacturer then determines the first set percentage and the second set percentage so that the identified section can be set as the valid determination section SCset.

[0060] The method for determining the first set percentage and the second set percentage is not limited to this. The first set percentage and the second set percentage may also be determined by a person other than the manufacturer of the sensor module 13, such as the manufacturer of the smartwatch 1 or the wearer of the smartwatch 1.

[0061] Here, the calculation unit 1331 is configured to determine the determination valid period SCset based on a set percentage with the interval SC1 as a reference. The interval used as a reference for determining the determination valid period SCset is not limited to the interval SC1. The calculation unit 1331 may be configured to determine the determination valid period SCset based on a set percentage with the interval SC0 as a reference.

[0062] Note that the length of the section from feature point FP2a to feature point FP1 is subject to individual differences and measurement variations. Therefore, when the determination valid period SCset is determined based on a set percentage with the section SC1 as the reference, the effects of individual differences and measurement variations on the length of the section from feature point FP2a to feature point FP1 can be eliminated. In other words, accuracy is improved compared to when the determination valid period SCset is determined based on a set percentage with a longer section before the section SC1 (for example, the section SC0) as the reference.

[0063] When the maximum point P11 of the differential waveform DW appears in the effective judgment section SCset, the maximum point P11 may be greater than 0 or may be less than 0.

[0064] 7, when a point with a right-shoulder-sloping shape resulting from the second maximum point P2 being dulled appears in the volume pulse wave VW, the maximum point P11 of the differentiated waveform DW is smaller than 0. When the maximum point P11 of the differentiated waveform DW is smaller than 0, the calculation unit 1331 identifies the point of the volume pulse wave VW at the time when the maximum point P11 appears in the differentiated waveform DW as the characteristic point FP3.

[0065] When the second maximum point P2 clearly appears in the volume pulse wave VW, the maximum point P11 of the differentiated waveform DW that appears in the valid judgment section SCset becomes greater than 0. When the maximum point P11 of the differentiated waveform DW is greater than 0, the calculation unit 1331 identifies, as the characteristic point FP3, the point on the volume pulse wave VW at the time when the differentiated waveform DW first crosses zero after the first maximum point P11 appears in the differentiated waveform DW.

[0066] The calculation unit 1331 may perform any processing when the maximum point of the differential waveform DW that appears in the judgment valid section SCset is equal to 0. In the following description, as an example, when the maximum point of the differential waveform DW that appears in the judgment valid section SCset is equal to 0, the calculation unit 1331 will perform the same processing as when the maximum point is less than 0.

[0067] The calculation unit 1331 calculates the feature amount based on at least the value of the feature point FP3 and the time. Here, as an example, the calculation unit 1331 calculates multiple types of feature amounts based on the values ​​of the feature points FP1, FP2, and FP3 and the time.

[0068] FIG. 8 is a diagram for explaining a plurality of types of feature amounts calculated by the calculation unit 1331 according to the embodiment.

[0069] A first feature amount FA1, a second feature amount FA2, a third feature amount FA3, a fourth feature amount FA4, a fifth feature amount FA5, and a sixth feature amount FA6 will be described as examples of multiple types of feature amounts acquired by calculation by the calculation unit 1331. The time axis is represented as the x-axis, the axis indicating the intensity of the volume pulse wave VW is represented as the y-axis, and the coordinates of feature point FP1 are represented as (x1, y1), the coordinates of feature point FP2a are represented as (x2, y2), and the coordinates of feature point FP3 are represented as (x3, y3).

[0070] The first feature amount FA1 indicates the height of the feature point FP1. The calculation unit 1331 acquires the first feature amount FA1 by the calculation shown in the following equation (1). FA1=y1-y2 (1)

[0071] The second feature amount FA2 indicates the height of the feature point FP3. The calculation unit 1331 obtains the second feature amount FA2 by the calculation shown in the following equation (2). FA2=y3-y2 (2)

[0072] The third feature amount FA3 indicates the time interval from the feature point FP2a to the feature point FP1. The calculation unit 1331 obtains the third feature amount FA3 by the calculation shown in the following equation (3). FA3=x1-x2 (3)

[0073] The fourth feature amount FA4 indicates the time interval from the feature point FP2a to the feature point FP3. The calculation unit 1331 obtains the fourth feature amount FA4 by the calculation shown in the following equation (4). FA4=x3-x2 (4)

[0074] The fifth feature amount FA5 indicates the time interval from the feature point FP1 to the feature point FP3. The calculation unit 1331 obtains the fifth feature amount FA5 by the calculation shown in the following equation (5). FA5=x3-x1 (5)

[0075] The sixth feature amount FA6 is a feature amount obtained by dividing the second feature amount FA2 by the first feature amount FA1. The calculation unit 1331 obtains the sixth feature amount FA6 by the calculation shown in the following equation (6). FA6 = FA2 / FA1 (6)

[0076] The sixth feature amount is the above-mentioned AIx.

[0077] Next, the operation of the microcomputer unit 133 will be described.

[0078] 9 is a flowchart showing the operation of the microcomputer unit 133 according to this embodiment. Here, the operation of acquiring a feature amount from a volume pulse wave VW already acquired by the acquiring unit 1330 will be described.

[0079] First, the calculation unit 1331 performs filtering on the raw data of the volume pulse wave VW (S101). The type of filtering is not limited to a specific type. For example, the calculation unit 1331 performs noise removal as filtering. From S101 onwards, unless otherwise specified, the volume pulse wave VW refers to the volume pulse wave VW after filtering.

[0080] The calculation unit 1331 obtains a differential waveform DW by performing first-order differentiation on the filtered volume pulse wave VW (S102).

[0081] Next, the calculation unit 1331 identifies the feature points FP1 and FP2 (S103) and identifies each one-cycle section SC0 (S104).

[0082] The method for identifying the feature points FP1 and FP2 and the method for identifying each one-cycle section SC0 are arbitrary. An example of the method for identifying the feature points FP1 and FP2 and the method for identifying each one-cycle section SC0 will be described with reference to FIG. 10 .

[0083] The calculation unit 1331 first identifies each local maximum point P10 from the differential waveform DW. Since each local maximum point P10 is significantly larger than other local maximum points that appear in the differential waveform DW, it is easy to detect each local maximum point P10. For example, the calculation unit 1331 detects all local maximum points included in the differential waveform DW by performing peak detection on the differential waveform DW. Then, the calculation unit 1331 detects, from among the detected local maximum points, a local maximum point whose height is equal to or greater than a predetermined threshold as the local maximum point P10. Note that the method for detecting each local maximum point P10 is not limited to this.

[0084] Next, the calculation unit 1331 identifies the sections separated by each maximum point P10 as sections SC2. Then, the calculation unit 1331 identifies the point taking the maximum value in each section SC2 as feature point FP1, and the point taking the minimum value in each section SC2 as feature point FP2.

[0085] Then, the calculation unit 1331 identifies the section divided by the characteristic point FP2 as a one-cycle section SC0.

[0086] Returning to Fig. 9, following the process of S104, the calculation unit 1331 acquires the feature amount for each one-cycle section SC0.

[0087] Specifically, for example, the calculation unit 1331 first selects one one-cycle section SC0 (S105). The selected one-cycle section SC0 is referred to as a target section.

[0088] The calculation unit 1331 identifies a determination valid section SCset within the target section (S106). As described with reference to Fig. 7, the calculation unit 1331 identifies, within the section SC1 from feature point FP1 to feature point FP2b within the target section, a section that is a first set percentage of the length of section SC1 from the beginning of section SC1 and a second set percentage of the length of section SC1 from the end of section SC1 as the determination valid section SCset.

[0089] Next, the calculation unit 1331 detects the maximum points of the differential waveform DW in the determination valid section SCset (S107), and then determines whether the number of detected maximum points of the differential waveform DW is one (S108).

[0090] The determination valid section SCset is set so that only one maximum point appears in the differential waveform DW in the determination valid section SCset. However, for example, if no characteristic change appears in the volume pulse wave VW around the time when the second maximum point P2 should appear, as in the volume pulse wave VW3 in Figure 2, the differential waveform DW may monotonically decrease or increase in the determination valid section SCset, and therefore no maximum point of the differential waveform DW may be detected in the determination valid section SCset. Furthermore, there may be cases where zero or more maximum points are detected in the determination valid section SCset due to other causes.

[0091] Therefore, if the number of detected maximum points in the differential waveform DW is 0 or 2 or more, the calculation unit 1331 considers it an error and skips the process of calculating the feature amount from the target section. If the number of detected maximum points in the differential waveform DW is 1, the calculation unit 1331 continues the process of calculating the feature amount from the target section. This makes it possible to prevent erroneous detection of feature point FP3 when no characteristic change appears in the volume pulse wave VW around the time when the second maximum point P2 should appear, as in the volume pulse wave VW3 in FIG. 2.

[0092] If the number of detected maximum points of the differential waveform DW is not one (S108: No), the control proceeds to S113, which will be described later.

[0093] If the number of detected maximum points of the differential waveform DW is one (S108: Yes), the calculation unit 1331 determines whether the detected maximum point of the differential waveform DW is greater than 0 (S109). Hereinafter, the detected maximum point of the differential waveform DW will be referred to as a target maximum point.

[0094] If the number of maximum points of the differential waveform DW detected in S107 is two or more, the process of calculating the feature amount from the target section does not necessarily have to be skipped. If the number of maximum points of the differential waveform DW detected is one or more, the calculation unit 1331 may regard the point with the largest maximum value in the target section as the target maximum point and execute the processes from S109 onwards.

[0095] If the target maximum point is not greater than 0 (S109: No), the calculation unit 1331 identifies the point on the volume pulse wave VW at the time the target maximum point appears as the characteristic point FP3 (S110). If the target maximum point is greater than 0 (S109: Yes), the calculation unit 1331 identifies the point on the volume pulse wave at the first zero crossing of the differential waveform DW after the target maximum point appears as the characteristic point FP3 (S111).

[0096] After the process of S110 or S111, the calculation unit 1331 calculates a plurality of types of feature amounts related to the volume pulse wave VW in the target section, that is, feature amounts FA1 to FA6, based on the feature points FP1, FP2, and FP3 (S112).

[0097] The calculation unit 1331 determines whether or not there are any one-cycle intervals SC0 remaining that have not yet been selected as target intervals (S113). If there are any one-cycle intervals SC0 remaining that have not yet been selected as target intervals (S113: Yes), the calculation unit 1331 sets one of the one-cycle intervals SC0 that have not yet been selected as target intervals as the target interval (S114). Then, control proceeds to S106.

[0098] If there is no one cycle section SC0 that has not yet been selected as a target section (S113: No), the calculation unit 1331 detects a portion where the value is saturated in the RAW data of the volume pulse wave (S115).

[0099] Then, the calculation unit 1331 excludes the feature calculated using the saturated value and calculates the average of the feature over the entire one cycle section SC0 for each type (S116). The output unit 1332 outputs the feature of each type obtained by averaging (S117), and the operation ends.

[0100] 9, the calculation unit 1331 averages each type of feature quantity over multiple one-cycle intervals SC0. The calculation unit 1331 does not necessarily have to calculate the average. For example, the calculation unit 1331 may acquire multiple types of feature quantities from one one-cycle interval SC0, and the output unit 1332 may output the multiple types of feature quantities acquired from the one one-cycle interval SC0.

[0101] The above describes an example in which the feature acquisition device according to the embodiment is applied to the sensor module 13. The device to which the feature acquisition device according to the embodiment is applied is not limited to the sensor module 13. The feature acquisition device according to the embodiment may be applied to, for example, a smart watch 1. The processor 14 of the smart watch 1 may function as the acquisition unit 1330, the calculation unit 1331, and the output unit 1332.

[0102] In the example described above, the volume pulse wave was detected by the sensor module 13, which is a photoelectric sensor. The method for detecting the volume pulse wave is not limited to the photoelectric sensor method. The feature acquisition device according to the embodiment can be applied to a device that acquires a volume pulse wave detected by any method.

[0103] As described above, according to the embodiment, the calculation unit 1331 identifies a first feature point FP1, which is the maximum local maximum point, and a second feature point FP2, which is the minimum local minimum point, in each cycle of the volume pulse wave VW (see, for example, FIGS. 7 and S103 in FIG. 9, and FIG. 10). The calculation unit 1331 detects a local maximum point P11 of the differential waveform DW in a determination effective section SCset, which is a section between the time when the first feature point FP1 appears and the time when feature point FP2b, which is the first feature point FP2 to appear after the appearance of feature point FP1, appears. The calculation unit 1331 identifies the point of the volume pulse wave VW at the time when the local maximum point P11 appears as feature point FP3. The calculation unit 1331 calculates a feature amount related to biological information based on at least feature point FP3.

[0104] Therefore, even if the detection accuracy of the volume pulse wave VW is poor, if a point P2' appears that is a dull, downward-sloping shape of the second maximum point P2, it is possible to obtain a feature quantity such as AIx using the second maximum point P2. In other words, it is possible to suitably obtain a feature quantity from the volume pulse wave VW.

[0105] According to an embodiment, the calculation unit 1331 identifies the interval between a time that is a first set percentage of the length of interval SC1 from the beginning of interval SC1 and a time that is a second set percentage of the length of interval SC1 from the end of interval SC1 as the valid judgment interval SCset.

[0106] By setting the first set percentage and the second set percentage so that a portion of the section SC1 in which the maximum point P11 may appear and in which other maximum points of the maximum point P11 are unlikely to appear can be identified as the judgment valid section SCset, it becomes easier to identify the characteristic point FP3.

[0107] Specifically, the calculation unit 1331 calculates the feature value when the number of maximum points appearing in the judgment valid section SCset is one, and does not calculate the feature value when the number of maximum points appearing in the judgment valid section SCset is not one.

[0108] The method for determining the first and second set percentages is not limited to the above. For example, the first and second set percentages may be set so that the maximum point P11 takes the maximum value in the determination valid section SCset. When the first and second set percentages are set in this manner, the calculation unit 1331 can identify the point at which the differential waveform DW takes the maximum value in the determination valid section SCset as the maximum point P11.

[0109] Furthermore, according to the embodiment, when the local maximum point P11 of the differential waveform is smaller than 0, the calculation unit 1331 identifies the point of the volume pulse wave VW at the time when the local maximum point P11 appears as the characteristic point FP3 (see, for example, S110 in FIG. 9). When the local maximum point P11 of the differential waveform is larger than 0, the calculation unit 1331 identifies the point of the volume pulse wave VW at the time when the differential waveform DW crosses zero for the first time after the local maximum point P11 appears as the characteristic point FP3 (see, for example, S111 in FIG. 9).

[0110] Therefore, even when the second maximum point P2 clearly appears in the volume pulse wave VW, it is possible to identify the second maximum point P2 as the characteristic point FP3.

[0111] Moreover, according to the embodiment, the calculation unit 1331 calculates AIx based on the feature points FP1, FP2, and FP3 as examples of various feature amounts.

[0112] Therefore, it is possible to obtain biological information as an index of the degree of aortic sclerosis based on AIx.

[0113] The first set percentage is, for example, 30 percent or less, but is not limited to this.

[0114] Although an embodiment of the present invention has been described, this embodiment is presented as an example and is not intended to limit the scope of the invention. This novel embodiment can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. This embodiment and its modifications are included within the scope and spirit of the invention, and are also included in the invention described in the claims and their equivalents. [Explanation of symbols]

[0115] 1 sensor module, 10 housing, 11 display device, 12 band, 13 sensor module, 14 processor, 15 memory, 16 bus, 130 sensor board, 131 light receiving element, 132 light emitting element, 133 microcomputer unit, 134 gain circuit, 200 arm, 211 radius, 212 ulna, 213 radial artery, 214 ulnar artery, 215 tendon, 1330 acquisition unit, 1331 calculation unit, 1332 output unit, DW differential waveform, VW volume pulse wave, FA1 to FA6 feature amount, FP1, FP2a, FP2b, FP3 feature points, P1 first maximum point, P2 second maximum point, P10, P11 maximum points, P2' point, SC0 1 cycle section, SC1, SC2, SCb, SCf section, SCset Validity period

Claims

1. an acquisition unit that acquires a signal including a pulse wave; a calculation unit that identifies a first point which is a maximum value point and a second point which is a minimum value point in each cycle of the pulse wave, detects a maximum point which is a point of the maximum maximum value of a first derivative waveform of the pulse wave in a second section which is a part of a first section which is a section between a time when the first point appears and a time when the second point first appears after the first point, identifies a third point which is a point on the pulse wave at the time when the maximum point of the first derivative waveform appears as a feature point, and calculates a feature amount related to biological information based on at least the value of the feature point and the time; A feature acquisition device comprising:

2. the calculation unit specifies, as a second interval, an interval including a time that is a first time period later than the start of the first interval, the first time period being shorter than the first interval, and a time that is a first time period earlier than the end of the first interval, the first time period being shorter than the first interval; The feature acquisition device according to claim 1 .

3. The calculation unit If the value of the maximum point of the first-order differential waveform is smaller than 0, the third point is identified as the characteristic point; If the value of the maximum point of the first-order derivative waveform is greater than 0, a point on the pulse wave at which the value of the first-order derivative waveform first switches between positive and negative after the appearance of the maximum point of the first-order derivative waveform is identified as the characteristic point.

3. The feature acquisition device according to claim 1.

4. The calculation unit If the number of maximum points appearing in the pulse wave in the second section is one, the feature amount is calculated; If the number of maximum points appearing in the pulse wave in the second section is not one, the calculation of the feature amount is not performed.

3. The feature acquisition device according to claim 1.

5. the calculation unit identifies a point in the second section at which the first-order differential waveform takes a maximum value as the local maximum point of the first-order differential waveform.

3. The feature acquisition device according to claim 1.

6. the calculation unit calculates an Augmentation Index, which is the feature amount, based on the first point, the second point, and the feature point; 3. The feature acquisition device according to claim 1.

7. The ratio of the first time period divided by the first interval is 30% or less. The feature acquisition device according to claim 2 .

8. acquiring a signal including a pulse wave; Identifying a first point which is a maximum value point and a second point which is a minimum value point in each cycle of the pulse wave; detecting a maximum point, which is a point of the maximum maximum value of a first-order differential waveform of the pulse wave, in a second section, which is a part of a first section, which is a section between a time when the first point appears and a time when the second point first appears after the first point; identifying a third point, which is a point on the pulse wave at a time when the maximum point of the first-order derivative waveform appears, as a feature point; calculating biometric information based on at least the feature point values ​​and the time; A feature acquisition method including:

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