JP2011072674A - Blood vessel state estimating apparatus, blood vessel state estimating method, and blood vessel state estimating program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a blood vessel state estimating apparatus, a blood vessel state estimating method and a blood vessel state estimating program by which the state of a blood vessel can accurately and easily be estimated. <P>SOLUTION: This blood vessel state estimating apparatus includes two optical sensors. Also, the blood vessel state estimating apparatus detects the pulse wave of a human body conforming to the variation amount of light which is detected by synchronizing with the other optical sensor, and converts the pulse wave into an electric signal for each optical sensor. Then, the blood vessel state estimating apparatus executes an n-th differential (n is a natural number) to the electric signal for each optical sensor, and identifies characteristic points included in an n-th differential waveform which is the waveform obtained as the result of the n-th differential. Then, the blood vessel state estimating apparatus calculates a difference for the appearance periods of the characteristic points which have been identified by a characteristic point identifying section for each optical sensor. Then, the blood vessel state estimating apparatus estimates the state of the blood vessel of the human body conforming to the difference which has been calculated for each optical sensor, and outputs an estimation result. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a blood vessel state estimation device, a blood vessel state estimation method, and a blood vessel state estimation program.

  Conventionally, there is an estimation device that estimates the state of a blood vessel based on the fact that the extensibility and elasticity of the blood vessel change with aging. For example, the estimation device estimates how old the blood vessel state corresponds to by using an acceleration pulse wave or a blood pressure pulse wave.

  For example, the case where the state of the blood vessel is estimated using the acceleration pulse wave will be further described. For example, the estimation device detects the fingertip volume pulse wave of the user, and generates the acceleration pulse wave as shown in FIG. 16 by differentiating the detected fingertip volume pulse wave twice. In addition, FIG. 16 is a figure for demonstrating an example of an acceleration pulse wave. The horizontal axis in FIG. 16 represents the time axis, and the vertical axis in FIG. 16 represents the value obtained by differentiating the fingertip volume pulse wave twice. Moreover, ae of FIG. 16 shows each feature point included in the acceleration pulse wave. In the example illustrated in FIG. 16, the estimation device calculates the heights of the feature points a, b, and d with respect to the baseline, and divides the heights of the feature points b and d by the height of the feature point a, respectively. To do. Here, based on the fact that there is a correlation between “b / a” or “d / a”, which is a value obtained by division, and age, the estimation device uses “b / a” or “ The state of the blood vessel is estimated using “d / a”. For example, the estimation device estimates that the blood vessel state of the user is in his twenties.

  Further, the case where the blood vessel state is estimated using the blood pressure pulse wave will be further described. For example, first, cuffs are previously attached to the user's arms and ankles. The estimation device then measures the difference between the time it takes for the blood pressure pulse wave to propagate from the heart to both arms and the time it takes for the blood pressure pulse wave to propagate from the heart to both ankles. Measure the pulse wave velocity, which is the velocity to perform. Then, based on the fact that there is a correlation between the pulse wave propagation speed and the age, the estimation apparatus measures the state of the blood vessel using the measured pulse wave propagation speed.

JP 2006-102250 A JP 2000-511166 A

  However, the technique using the acceleration pulse wave has a problem that accuracy is poor. That is, the pulse wave varies depending on various factors, for example, varies depending on the blood pressure value. In addition, the blood pressure value also changes due to various factors, for example, changes due to the user's breathing. For this reason, in the estimation apparatus using the acceleration pulse wave, the accuracy is poor as a result of the pulse wave changing every measurement. For example, in the estimation apparatus that uses acceleration pulse waves, the range of ages obtained each time processing is performed is large. As described above, the technique using the acceleration pulse wave has a problem that accuracy is poor.

  Further, for example, the technique using blood pressure pulse waves has a problem that it cannot be easily measured. That is, in the estimation apparatus, the user has to wear the cuff in advance. When the cuff is worn, the user's ankle and both arms are tightened, and the load on the user is large. In addition, when using a cuff, it is difficult to reduce the size of the apparatus. As described above, the technique using the blood pressure pulse wave has a problem that it cannot be easily measured.

  The disclosed technology has been made in view of the above, and an object of the present invention is to provide a blood vessel state estimation device, a blood vessel state estimation method, and a blood vessel state estimation program capable of accurately and simply estimating a blood vessel state.

  According to one aspect of the disclosed blood vessel state estimation device, a light emitting element that irradiates light to a human body, and a change amount of light that is emitted from the light emitting element and then passes through the human body, or is emitted from the light emitting element An optical sensor having a light receiving element for detecting a change amount of light reflected by the rear human body is provided. Further, the blood vessel state estimation device has at least two optical sensors. In addition, the blood vessel state estimation device detects a pulse wave of the human body based on a change amount of light detected in synchronization with another optical sensor for each optical sensor, and converts the pulse wave into an electrical signal. A pulse wave detection unit. In addition, the blood vessel state estimation device performs n-order differentiation (n is a natural number) on the electrical signal converted by the pulse wave detection unit for each of the optical sensors, and a waveform obtained as a result of the n-order differentiation. A feature point identifying unit for identifying feature points included in the nth-order differential waveform. In addition, the blood vessel state estimation device includes a difference calculation unit that calculates a difference between appearance times of feature points identified by the feature point identification unit for each of the optical sensors. The blood vessel state estimation device further includes a blood vessel state estimation unit that estimates a blood vessel state of the human body based on the difference calculated for each of the optical sensors by the difference calculation unit and outputs an estimation result.

  According to one aspect of the disclosed blood vessel state estimation device, there is an effect that the blood vessel state can be easily and accurately estimated.

FIG. 1 is a block diagram illustrating an example of the configuration of the blood vessel state estimation device according to the first embodiment. FIG. 2 is a block diagram illustrating an example of the configuration of the blood vessel state estimation device according to the second embodiment. FIG. 3 is a diagram illustrating an example of usage of the optical sensor in the second embodiment. FIG. 4 is a diagram illustrating an example of the structure of the optical sensor according to the second embodiment. FIG. 5 is a diagram illustrating a detailed example of the mounting substrate in the second embodiment. FIG. 6 is a diagram illustrating an example of a waveform indicated by an electrical signal converted by the optical sensor according to the second embodiment. FIG. 7 is a diagram illustrating an example of information stored in the threshold value table according to the second embodiment. FIG. 8 is a diagram illustrating an example of a process for identifying a place where a pulse jump has occurred by the pulse wave interval calculation unit according to the second embodiment. FIG. 9A is a diagram illustrating an example of a second-order differential waveform in the second embodiment. FIG. 9B is a diagram illustrating an example of a second-order differential waveform in the second embodiment. FIG. 10 is a diagram for further explaining the feature point identifying process by the feature point identifying unit in the second embodiment. FIG. 11 is a diagram illustrating an example of a difference calculation process of appearance time by a difference calculation unit according to the second embodiment. FIG. 12A is a diagram for explaining the relationship between the variance of the difference between sensors and the age. FIG. 12B is a diagram for explaining the relationship between the variance of the inter-sensor difference and the age. FIG. 12C is a diagram for explaining the relationship between the variance of differences between sensors and the age. FIG. 13 is a diagram for explaining the relationship between the variance of differences between sensors and the age. FIG. 14 is a flowchart illustrating an example of a process flow performed by the blood vessel state estimation device according to the second embodiment. FIG. 15 is a schematic diagram illustrating an example of a computer that executes a blood vessel state estimation program according to the second embodiment. FIG. 16 is a diagram for explaining an example of the acceleration pulse wave.

  Hereinafter, embodiments of the disclosed vascular state estimation device, vascular state estimation method, and vascular state estimation program will be described in detail with reference to the drawings. Note that the invention disclosed by this embodiment is not limited. Each embodiment can be appropriately combined within a range in which processing contents do not contradict each other.

  An example of the configuration of the blood vessel state estimation apparatus 100 according to the first embodiment will be described with reference to FIG. FIG. 1 is a block diagram illustrating an example of the configuration of the blood vessel state estimation device according to the first embodiment. In the example illustrated in FIG. 1, the blood vessel state estimation device 100 includes an optical sensor 101, an optical sensor 102, a pulse wave detection unit 103, a feature point identification unit 104, a difference calculation unit 105, and a blood vessel state estimation unit 106. Have

  The optical sensor 101 and the optical sensor 102 are a light emitting element that irradiates light to the human body, a change amount of light that is transmitted from the light emitting element and then transmitted through the human body, or light that is reflected from the rear human body that is emitted from the light emitting element. And a light receiving element for detecting a change amount of the light receiving element.

  For each optical sensor, the pulse wave detection unit 103 detects the pulse wave of the human body based on the change amount of light detected in synchronization with the other optical sensors, and converts the pulse wave into an electrical signal. In addition, the feature point identification unit 104 performs n-order differentiation (n is a natural number) on the electrical signal converted by the pulse wave detection unit 103 for each optical sensor, and uses the waveform obtained as a result of the n-order differentiation. A feature point included in a certain nth-order differential waveform is identified.

  The difference calculation unit 105 calculates the difference in appearance time of the feature points identified by the feature point identification unit 104 for each optical sensor. The blood vessel state estimation unit 106 estimates the blood vessel state of the human body based on the difference calculated for each optical sensor by the difference calculation unit 105, and outputs an estimation result.

  Thus, according to Example 1, the state of the blood vessel can be estimated with high accuracy. That is, the pulse wave varies depending on various factors, for example, varies depending on the blood pressure value. In addition, the blood pressure value also changes due to various factors, for example, changes due to the user's breathing. As a result, when the state of the blood vessel was estimated using the height of the feature point when the time axis of the pulse wave was used as a reference, the accuracy was poor. However, according to the first embodiment, based on the fact that the appearance time of each feature point is less susceptible to fluctuation due to the blood pressure value or the like, the state of the blood vessel is estimated based on the difference in the appearance time of the feature point. It is possible.

  Further, according to the first embodiment, it is possible to easily estimate the state of the blood vessel as compared with the method using the cuff.

[Configuration of blood vessel state estimation device]
Next, the blood vessel state estimation device 200 according to the second embodiment will be described. First, an example of the configuration of the blood vessel state estimation apparatus 200 according to the second embodiment will be described with reference to FIG. FIG. 2 is a block diagram illustrating an example of the configuration of the blood vessel state estimation device according to the second embodiment. In the example illustrated in FIG. 2, the blood vessel state estimation device 200 includes an optical sensor 201, an optical sensor 202, an output unit 203, a storage unit 300, and a control unit 400.

  The optical sensor 201 and the optical sensor 202 are connected to the control unit 400. In addition, the optical sensor 201 and the optical sensor 202 are reflected by a light emitting element that irradiates light to the human body and a change amount of light that has been emitted from the light emitting element and transmitted through the human body, or by the rear human body that is emitted from the light emitting element. And a light receiving element for detecting the amount of change in light. In addition, the optical sensor 201 and the optical sensor 202 irradiate light to a portion of a human body having blood vessels with different thicknesses.

  Here, the light emitting element corresponds to, for example, an LED (Light Emitting Diode). The light receiving element corresponds to, for example, PD (Photo Diode). The LED used as the light emitting element irradiates light having a wavelength near 760 nm, for example. In the following description, an example in which an LED used as a light emitting element emits light having a wavelength near 760 nm will be described, but the present invention is not limited to this. For example, an LED used as a light emitting element may irradiate light having a wavelength longer than 760 nm, or irradiate light having a wavelength shorter than 760 nm, and the user selects an arbitrary wavelength. good.

  An example of usage of the optical sensor 201 and the optical sensor 202 will be described with reference to FIG. FIG. 3 is a diagram illustrating an example of usage of the optical sensor in the second embodiment. FIG. 3 shows an example in which the blood vessel state estimation device 200 is a mobile terminal. In the example shown in FIG. 3, the optical sensor 201 has a clip-like shape, and comes into contact with the ear when worn by the user on the earlobe. In the example illustrated in FIG. 3, the optical sensor 201 is connected to the housing of the blood vessel state estimation device 200 via a cable. In the example illustrated in FIG. 3, the optical sensor 202 is provided in the housing of the blood vessel state estimation device 200 and comes into contact with the finger when the finger is pressed by the user.

  In the following, as shown in FIG. 3, a case where the optical sensor 201 is in contact with the ear and the optical sensor 202 is in contact with the finger will be described as an example. However, the present invention is not limited to this. For example, the user may arbitrarily select a location where the optical sensor 201 or the optical sensor 202 contacts.

  In the following description, as shown in FIG. 3, the optical sensor 201 has a clip-like shape and is attached to an ear. However, the present invention is not limited to this. For example, the optical sensor 201 may have a plate shape instead of a clip shape, and the user may select an arbitrary shape.

  In the following, as illustrated in FIG. 3, the optical sensor 201 will be described as an example in which the optical sensor 201 is connected to the housing of the blood vessel state estimation device 200 via a cable, but the present invention is not limited thereto. is not. For example, the optical sensor 201 may be connected to the housing of the blood vessel state estimation device 200 via wireless, and the user may select any connection form. Similarly, the optical sensor 201 may be provided in the housing of the blood vessel state estimation device 100.

  In the following, as illustrated in FIG. 3, the optical sensor 202 is described as an example provided in the housing of the blood vessel state estimation device 200, but the present invention is not limited to this. For example, the optical sensor 202 may be connected to the housing of the blood vessel state estimation device 200 via a cable or wirelessly, and the user may select an arbitrary connection form.

  An example of the structure of the optical sensor 201 will be described with reference to FIG. FIG. 4 is a diagram illustrating an example of the structure of the optical sensor according to the second embodiment. FIG. 4 shows the optical sensor 201 after disassembling each part forming the optical sensor 201. As shown in FIG. 4, in the optical sensor 201, an opening control rubber 501 that is movable in a clip shape as a lid that can be opened and closed is attached to a cover case 504. In addition, on the surface of the opening control rubber 501 on the cover case 504 side, a visible light cut filter 502 for cutting visible light, and a mounting substrate 503 on which an LED (Light Emitting Diode) and a PD (Photo Diode) are mounted. Are sequentially stacked.

  Here, the visible light cut filter 502 blocks the visible light transmitted through the aperture control rubber 501 so that the PD mounted on the mounting substrate 503 does not detect the visible light transmitted through the aperture control rubber 501. . The LED mounted on the mounting substrate 503 corresponds to a light emitting element, and the PD mounted on the mounting substrate 503 corresponds to a light receiving element. Note that the optical sensor 202 is realized, for example, by providing the mounting substrate 503 in the housing of the blood vessel state estimation device 200.

  A detailed example of the mounting substrate 503 will be described with reference to FIG. FIG. 5 is a diagram illustrating a detailed example of the mounting substrate in the second embodiment. In the example illustrated in FIG. 5, the case where the optical sensor 201 is the mounting substrate 503 is illustrated as an example. That is, in the example illustrated in FIG. 5, the case where the mounting substrate 503 is in contact with the ear 507 is illustrated as an example.

  As shown in FIG. 5, a light emitting element 505 such as an LED and a light receiving element 506 such as a PD are provided on the plane of the mounting substrate 503. Further, the mounting substrate 503 is in contact with the ear 507. Here, as shown in FIG. 5, the light receiving element 506 receives the light reflected by the ear 507 among the light emitted from the light emitting element 505, and detects the amount of change in the received light. Alternatively, the light receiving element 506 receives light transmitted through the ear 507 among the light emitted from the light emitting element 505, and detects the amount of change in the received light.

  The optical sensor 201 detects a human body pulse wave based on the amount of change in light detected in synchronization with the optical sensor 202, and converts the pulse wave into an electrical signal. For example, the optical sensor 201 detects a pulse wave with an ear and converts it into an electrical signal. The optical sensor 202 detects a pulse wave of the human body based on the change amount of light detected in synchronization with the optical sensor 201, and converts the pulse wave into an electrical signal. For example, the optical sensor 202 detects a pulse wave with a finger and converts it into an electrical signal.

  Processing for detecting the pulse wave by the optical sensor 201 and the optical sensor 202 will be further described. First, there is a correlation between the blood flow volume at the location where the light emitting element irradiates light and the amount of light received by the light receiving element. Specifically, as the blood flow rate at the location where the light emitting element irradiates light increases, the amount of light absorbed by the blood flow at the location where the light emitting element illuminates increases, and the light receiving element receives light. The amount of light decreases. Next, when the pulse wave generated by the heartbeat arrives, the blood vessels widen, and the blood flow volume at the location where the light emitting element emits light increases. That is, the optical sensor 201 or the optical sensor 202 detects a change in blood flow at a location where the light emitting element emits light by detecting the amount of change in the light received by the light receiving element. As a result, the optical sensor 201 and the optical sensor 202 detect a pulse wave by detecting a change in blood flow.

  An example of a waveform indicated by an electrical signal converted by the optical sensor 201 or the optical sensor 202 will be described with reference to FIG. FIG. 6 is a diagram illustrating an example of a waveform indicated by an electrical signal converted by the optical sensor. Here, (1) of FIG. 6 shows an example of a waveform indicated by the electrical signal converted by the optical sensor 201. FIG. In other words, (1) in FIG. 6 is the waveform for the optical sensor in contact with the ear. FIG. 6 (2) shows an example of a waveform indicated by the electrical signal converted by the optical sensor 202. FIG. In other words, (2) of FIG. 6 is a waveform about the optical sensor in contact with the finger. The horizontal axes of (1) and (2) in FIG. 6 indicate the time axis, and the vertical axes of (1) and (2) in FIG. 6 indicate the amount of light received by the light receiving element. That is, the vertical axis indicates the blood flow volume at the location where the light sensor irradiates light. As a result, in (1) and (2) of FIG. 6, the portion where the blood flow rate is increased indicates that the pulse wave generated by the heartbeat has arrived.

  Returning to the description of FIG. The output unit 203 is connected to the control unit 400. The output unit 203 receives information from the control unit 400 and outputs the received information. The output unit 203 corresponds to, for example, a monitor, a display, a touch panel, or a speaker. The details of the information output by the output unit 203 will be omitted here, and will be described together with the description of each related unit.

  Storage unit 300 is connected to control unit 400. The storage unit 300 stores data used for various processes performed by the control unit 400. The storage unit 300 is, for example, a semiconductor memory device such as a random access memory (RAM), a read only memory (ROM), or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 300 includes a threshold value table 301 in the example illustrated in FIG.

  The threshold value table 301 stores threshold values used by the blood vessel state estimation unit 406, as will be described later. For example, an example of information stored in the threshold value table 301 will be described with reference to FIG. FIG. 7 is a diagram illustrating an example of information stored in the threshold value table according to the second embodiment. In the example shown in FIG. 7, the case where “age” indicating the age corresponding to the state of the blood vessel is stored is shown. Further, “s” included in the “threshold value” in FIG. 7 is a value calculated by the blood vessel state estimation unit 406 as described later. Since the details of “s” in FIG. 7 will be described together with the description of the blood vessel state estimation unit 406, description thereof is omitted here.

  As shown in FIG. 7, the threshold value table 301 stores threshold values in association with ages. For example, in the example illustrated in FIG. 7, the threshold table 301 stores a threshold “0 <s <2” associated with the age “20s” and a threshold “2 <s <2” associated with the age “30s”. 4 "is stored. Further, in the example illustrated in FIG. 7, the threshold value table 301 stores threshold values for the ages “40s” and “50s”. That is, for example, when the blood vessel state estimation unit 406 calculates “s = 1”, the threshold value table 301 stores that the blood vessel state corresponds to “20's”.

  In the following, as illustrated in FIG. 7, the threshold value table 301 is described as an example in which threshold values are stored for each age, but the present invention is not limited to this. For example, the threshold value table 301 may store a threshold value for each age, or may store a threshold value for each range arbitrarily set by the user.

  The control unit 400 is connected to the optical sensor 201, the optical sensor 202, the output unit 203, and the storage unit 300. The control unit 400 includes an internal memory that stores a program that defines various processing procedures and the like, and controls various processes. The control unit 400 is an electronic circuit such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a central processing unit (CPU), or a micro processing unit (MPU). In the example illustrated in FIG. 2, the control unit 400 includes a pulse wave interval calculation unit 401, a pulse wave interval calculation unit 402, an nth-order differentiation processing unit 403, a feature point identification unit 404, a difference calculation unit 405, and a blood vessel. A state estimation unit 406.

  In the example shown in FIG. 2, the pulse wave interval calculation unit 401 and the pulse wave interval calculation unit 402 are described as separate control units. However, the present invention is not limited to this, and is integrated into one unit. It is good also as a control part. Moreover, the pulse wave interval calculation unit 401 and the pulse wave interval calculation unit 402 may be integrated with the optical sensor 201 and the optical sensor 202, respectively.

  The pulse wave interval calculation unit 401 calculates a pulse wave interval between two consecutive pulse waves from the waveform indicated by the electrical signal converted by the optical sensor 201. Specifically, the pulse wave interval calculation unit 401 identifies the maximum point in the waveform indicated by the electrical signal, and calculates the pulse wave interval by calculating the interval between adjacent maximum points. Similarly to the pulse wave interval calculation unit 401, the pulse wave interval calculation unit 402 calculates the pulse wave interval from the waveform indicated by the electrical signal converted by the optical sensor 202.

  Also, the pulse wave interval calculation unit 401 and the pulse wave interval calculation unit 402 each identify a place where a pulse jump has occurred using the pulse wave interval. An example of the process for identifying the place where the pulse jumps will be described with reference to FIG. FIG. 8 is a diagram illustrating an example of a process for identifying a place where a pulse jump has occurred by the pulse wave interval calculation unit according to the second embodiment. (1) in FIG. 8 shows a waveform for the optical sensor 201 and corresponds to (1) in FIG. That is, (1) of FIG. 8 is a waveform about the optical sensor in contact with the ear. (2) in FIG. 8 shows a waveform for the optical sensor 202 and corresponds to (2) in FIG. That is, (2) of FIG. 8 is a waveform about the optical sensor in contact with the finger. The horizontal axes of (1) and (2) in FIG. 8 indicate the time axis, and the vertical axis of (1) and (2) in FIG. 8 indicates the blood flow. Further, description will be made assuming that the horizontal axis of (1) in FIG. 8 and the horizontal axis of (2) in FIG. 8 correspond to each other. In other words, when the horizontal axis is the same position, description will be made assuming that (1) and (2) in FIG. 8 indicate data at the same time. Further, “pulse wave n” (n is a natural number) in FIG. 8 indicates each pulse wave included in the waveform, and “maximum point” in FIG. 8 indicates the maximum point included in each pulse wave. 8 indicates a pulse wave interval calculated by the pulse wave interval calculation unit 401 or the pulse wave interval calculation unit 402.

  Here, in the example shown in (1) of FIG. 8, the pulse wave interval between two continuous pulse waves between pulse waves 1 to 6 is a pulse that is n times (n is a natural number) the other pulse wave intervals. There is no wave interval. In other words, in the example shown in (1) of FIG. 8, all pulse wave intervals have the same value. In this case, the pulse wave interval calculation unit 401 determines that there is no pulse skip. On the other hand, in the example shown in (2) of FIG. 8, the pulse wave interval between the pulse waves 1 and 2 is twice the pulse wave interval between two continuous pulse waves between the pulse waves 2 to 5. become. In this case, the pulse wave interval calculation unit 401 identifies that there is a pulse jump between the pulse waves 1 and 2. Note that the processing result by the pulse wave interval calculation unit 401 is used by the feature point identification unit 404 as described later.

  The n-th order differential processing unit 403 performs n-th order differentiation (n is a natural number) for the waveform indicated by the electrical signal for each optical sensor. Specifically, the nth-order differentiation processing unit 403 performs nth-order differentiation (n is a natural number) on the waveform for the optical sensor 201, and nth-order differentiation (n for the waveform for the optical sensor 202). Is a natural number). Hereinafter, the n-th order differentiation processing unit 403 will be described as an example where the second-order differentiation is performed unless otherwise specified, but the present invention is not limited to this. For example, the nth-order differentiation processing unit 403 may execute first-order differentiation or third-order differentiation, and the user may set an arbitrary number of differentiations.

  For example, the n-th order differential processing unit 403 obtains a second-order differential waveform as shown in FIGS. 9A and 9B when the second-order differentiation is executed. Here, FIG. 9A and FIG. 9B are diagrams for explaining an example of the secondary differential waveform in the second embodiment. 9A shows the waveform of the optical sensor 201, and corresponds to (1) in FIG. 6 and (1) in FIG. That is, (1) of FIG. 9A is a waveform about the optical sensor in contact with the ear. (2) in FIG. 9A is a second-order differential waveform obtained by second-order differentiation with respect to (1) in FIG. 9A. That is, (2) in FIG. 9A is a second-order differential waveform for the ear. (1) in FIG. 9B shows a waveform for the optical sensor 202, and corresponds to (2) in FIG. 6 and (2) in FIG. That is, (1) of FIG. 9B is a waveform about the optical sensor in contact with the finger. (2) in FIG. 9B is a second-order differential waveform obtained by second-order differentiation with respect to (1) in FIG. 9B. That is, (2) in FIG. 9B is a second-order differential waveform for the finger.

  Moreover, the horizontal axis of FIG. 9A and FIG. 9B shows a time axis. Moreover, the vertical axis | shaft of (1) of FIG. 9A and (1) of FIG. 9B shows a blood flow rate. The description will be made assuming that the horizontal axis of (1) in FIG. 9 and the horizontal axis of (2) in FIG. 9 correspond to each other. Moreover, the vertical axis | shaft of (2) of FIG. 9A and (2) of FIG. 9B shows the value obtained by the secondary differentiation.

  The feature point identification unit 404 identifies the feature points included in the secondary differential waveform for each optical sensor. Specifically, the feature point identifying unit 404 identifies a plurality of feature points for each pulse wave included in the secondary differential waveform corresponding to the optical sensor 201. The feature point identifying unit 404 identifies a plurality of feature points for each pulse wave included in the secondary differential waveform corresponding to the optical sensor 202.

  Further, the feature point identifying unit 404 identifies the timing at which the pulse wave is included in both secondary differential waveforms based on the processing result by the pulse wave interval calculating unit 401. The feature point identification unit 404 identifies at least four feature points for each pulse wave included in the identified timing. That is, the feature point identifying unit 404 identifies at least four feature points for each pulse wave included in the secondary differential waveform.

  The feature point identifying process by the feature point identifying unit 404 will be further described with reference to FIG. FIG. 10 is a diagram for further explaining the feature point identifying process by the feature point identifying unit in the second embodiment. In addition, (1) of FIG. 10 is a secondary differential waveform about the ear, and corresponds to (2) of FIG. 9A. Further, (2) in FIG. 10 is a second-order differential waveform for the finger, and corresponds to (2) in FIG. 9B. As shown in (1) of FIG. 10, the secondary differential waveform for the ear has no pulse skipping, and as shown in (2) of FIG. 10, the secondary differential waveform for the finger has pulse wave 1 and pulse. A case where there is a pulse jump between the waves 2 will be described as an example.

  Also, the horizontal axes of (1) and (2) in FIG. 10 indicate the time axis, and the vertical axes of (1) and (2) in FIG. 10 indicate values obtained by the secondary differentiation process. The description will be made assuming that the horizontal axis of (1) in FIG. 10 and the horizontal axis of (2) in FIG. 10 correspond to each other. “Pulse wave n” (n is a natural number) in FIG. 10 indicates each pulse wave included in the waveform, and “feature points a to e” in FIG. 10 are identified for each pulse wave by the feature point identifying unit 404. Indicates feature points. In addition, as shown in “with pulse skip” in FIG. Note that the feature points “a” to “e” are also referred to as the first feature point to the fifth feature point, respectively. The first feature point is a feature point having the first appearance time among the feature points included in the pulse wave. Similarly, the second feature point to the fifth feature point indicate feature points whose appearance times are the second to fifth among the feature points included in the pulse wave, respectively.

  In this case, the feature point identification unit 404 identifies that the pulse wave is also included in the secondary differential waveform shown in (2) of FIG. 10 at the same timing as the pulses 1, 3 to 6 in (1) of FIG. . As a result, the feature point identifying unit 404 identifies feature points for the pulses 1, 3 to 6 in (1) of FIG. Further, the feature point identifying unit 404 identifies feature points for the pulse wave at the same timing as the pulses 1 and 3 to 6. For example, the feature point identifying unit 404 identifies feature points for the pulses 1 to 5 in (1) of FIG. As shown in FIG. 10, pulses 1 and 3 to 6 in (1) in FIG. 10 have the same timing as pulses 1 to 5 in (2) in FIG.

  As shown in FIG. 10, the feature point identifying unit 404 identifies at least four feature points for each pulse. For example, the feature point identifying unit 404 identifies feature points a to e or feature points a to d for each pulse. As shown in (1) and (2) of FIG. 10, the feature points a to d can be identified in most secondary differential waveforms. As shown in (1) of FIG. 10, it is known that there are many cases where the feature point e cannot be identified.

  In the example illustrated in FIG. 10, as illustrated in FIG. 10 (1), the case where the feature point identification unit 404 cannot identify the feature point e in the second-order differential waveform for the ear is illustrated as an example. Further, as shown in (2) of FIG. 10, the case where the feature point identifying unit 404 can identify the feature point e in the secondary differential waveform for the finger is shown as an example. However, the present invention is not limited to this, and the feature point e may be identified in the secondary differential waveform for the ear, and the feature point e can be identified in the secondary differential waveform for the finger. There may be no case.

  The difference calculation unit 405 calculates the difference between the appearance times of the feature points identified by the feature point identification unit 404 for each optical sensor. Specifically, the difference calculation unit 405 calculates a difference for the feature point of the secondary differential waveform corresponding to the optical sensor 201. Further, the difference calculation unit 405 calculates a difference for the feature point of the secondary differential waveform corresponding to the optical sensor 202. Here, the difference in appearance time corresponds to time. For example, the difference in appearance time corresponds to a time such as 1 second or 5 milliseconds.

  For example, for the optical sensor that irradiates light on a blood vessel that is thicker than the other optical sensor, the difference calculation unit 405 includes a first feature point between the third feature point and the fourth feature point for each pulse wave. Calculate the difference. In addition, the difference calculation unit 405 has a second difference between the first feature point and the second feature point for each pulse wave with respect to the optical sensor that irradiates light to a thin blood vessel as compared with the other optical sensor. Calculate the difference.

  This will be further described with reference to FIG. FIG. 11 is a diagram illustrating an example of a difference calculation process of appearance time by a difference calculation unit according to the second embodiment. (1) in FIG. 11 is a second-order differential waveform for the ear, and corresponds to (2) in FIG. 9A and (1) in FIG. Further, (2) in FIG. 11 is a second-order differential waveform for the finger, and corresponds to (2) in FIG. 9B and (2) in FIG. Also, the horizontal axes of (1) and (2) in FIG. 11 indicate the time axis, and the vertical axes of (1) and (2) in FIG. 11 indicate values obtained by the secondary differentiation process. The horizontal axis of (1) in FIG. 11 and the horizontal axis of (2) in FIG. 11 are assumed to correspond to each other. “Pulse wave n” (n is a natural number) in FIG. 11 indicates each pulse wave included in the waveform. “Feature points a to d” in FIG. 11 indicate feature points identified by the feature point identifying unit 404.

  In this case, as shown in “ear difference 1” to “ear difference 5” in (1) of FIG. 11, the difference calculation unit 405 performs the following operations on the pulses 1 and 3 to 6 included in the secondary differential waveform for the ear. The absolute value of the difference between the time when the feature point a appears and the time when the feature point b appears is calculated. Moreover, the difference calculation part 405 is the feature point c about the pulses 1-5 contained in the secondary differential waveform about a finger | toe, as shown to "finger difference 1"-"finger difference 5" of (2) of FIG. The absolute value of the difference between the time when appears and the time when the feature point d appears is calculated.

  In the following, regarding the secondary differential waveform for the ear and the secondary differential waveform for the finger, the difference in the appearance time between the feature points cd and the difference in the appearance time between the feature points ab, respectively. Although the case where it calculates is demonstrated, this invention is not limited to this. For example, the difference calculation unit 405 may calculate a difference in appearance time between feature points ab and a difference in appearance time between feature points bc for the second-order differential waveform for the ear. Further, for example, the difference calculation unit 405 may calculate the difference in appearance time between feature points bc and the difference in appearance time between feature points cd for the secondary differential waveform for the finger. Further, the difference calculation unit 405 may calculate a difference between the same feature points in both the second-order differential waveform for the ear and the second-order differential waveform for the finger.

  The blood vessel state estimation unit 406 estimates the blood vessel state of the human body based on the difference calculated for each optical sensor by the difference calculation unit 405, and outputs an estimation result. Specifically, the blood vessel state estimation unit 406 calculates an inter-sensor difference, which is a difference between differences calculated for each optical sensor, for each of a plurality of differences calculated by the difference calculation unit 405. For example, the blood vessel state estimation unit 406 calculates each inter-sensor difference by calculating a difference between the first difference and the second difference for each pulse wave. If it demonstrates using the example shown in FIG. 10, the blood-vessel state estimation part 406 will calculate the differences 1-5 between sensors by calculating the difference between the ear differences 1-5 and the finger differences 1-5, respectively. To do.

  In addition, although the blood vessel state estimation unit 406 has been described as an example of calculating the difference between the five sensors, the present invention is not limited to this. For example, four or less inter-sensor differences may be calculated, six or more inter-sensor differences may be calculated, and the user may arbitrarily set them.

  In addition, the blood vessel state estimation unit 406 estimates that the age of the blood vessel is higher than the case where the difference between the sensors is widely dispersed than when the difference is narrowly distributed, and the case where the difference between the sensors is narrowly dispersed than the case where the differences are widely dispersed. Also assume that the vascular age is low. The blood vessel age indicates an age corresponding to a blood vessel state. That is, when it is estimated that the blood vessel age is “20s”, it indicates that the blood vessel state is equivalent to the blood vessel state of a person in their 20s.

  The relationship between the variance of the difference between sensors and the age will be described with reference to FIGS. 12A to 12C. 12A to 12C are diagrams for explaining the relationship between the variance of the difference between sensors and the age. FIG. 12A is a diagram illustrating a relationship between finger differences and ear differences calculated from data of users in their thirties. FIG. 12B is a diagram showing a relationship between finger differences and ear differences calculated from data of users in their 40s. FIG. 12C is a diagram illustrating a relationship between finger differences and ear differences calculated from data of users in their 50s. 12A to 12C, the horizontal axis indicates the pulse rate, and the vertical axis indicates the absolute value of the finger difference or the ear difference.

  As shown in FIG. 12A, in the data of a 30-year-old user, the finger difference and the ear difference changed in the same manner as a whole. That is, in the example shown in FIG. 12A, when the finger difference increases, the ear difference also increases, and when the finger difference decreases, the ear difference also decreases. On the other hand, as shown in FIG. 12B, in the data of a 43-year-old user, the finger difference and the ear difference changed in the same way or did not change in the same way. That is, in the example indicated by 601 in FIG. 12B, the ear difference increases when the finger difference increases, and the ear difference decreases when the finger difference decreases. In other words, in the example shown at 601 in FIG. 12B, the finger difference and the ear difference changed in the same way. On the other hand, in the example shown by 602 in FIG. 12B, the ear difference decreases when the finger difference increases, and the ear difference increases when the finger difference decreases. In other words, in the example shown by 602 in FIG. 12B, the finger difference and the ear difference changed in a discontinuous manner. Further, as shown in FIG. 12C, the finger difference and the ear difference changed in a whole manner in the data of a 50-year-old user.

  That is, when the age is low, all the differences between the sensors have the same value, and as a result, the degree of dispersion of the differences among the plurality of sensors is considered to be lower than when the age is high. On the other hand, when the age is high, the difference between the sensors becomes a different value. As a result, the degree of dispersion of the differences between the plurality of sensors is considered to be higher than that when the age is low.

  The relationship between the variance of the difference between sensors and the age will be further described with reference to FIG. FIG. 13 is a diagram for explaining the relationship between the variance of differences between sensors and the age. The horizontal axis of FIG. 13 shows the value of the inter-sensor difference, and the vertical axis of FIG. 13 shows the probability that the corresponding inter-sensor difference value is obtained. That is, the higher the value on the vertical axis, the higher the probability that a corresponding inter-sensor difference value is obtained. In other words, when the blood vessel state estimation unit 406 calculates a plurality of inter-sensor differences, it indicates that there is a high probability that the same inter-sensor difference is calculated.

  As shown in FIG. 13, in the twenties, the value of the vertical axis of the peak is the highest compared to other ages, and the width of the horizontal axis of the peak is the smallest compared to other ages. Further, the value of the vertical axis of the peak decreases with age from the 20s to the 50s, and the width of the horizontal axis of the peak increases with age from the 20s to the 50s.

  As described above, there is a relationship between the variance of the difference between sensors and the age that the degree of variance of the difference between sensors increases as the age increases. Based on this, the blood vessel state estimation unit 406 estimates the blood vessel state and outputs an estimation result. Specifically, the standard deviation range of the inter-sensor difference is calculated in advance for each age by the user and stored in the threshold value table 301. Then, the blood vessel state estimation unit 406 calculates a standard deviation of each inter-sensor difference, determines which threshold value the calculated standard deviation value corresponds to, and determines an age corresponding to the threshold value determined to be applicable. Estimated result. Note that “s” in FIG. 7 indicates the standard deviation of the inter-sensor difference.

  For example, the blood vessel state estimation unit 406 calculates the standard deviation “s” by using the following (Equation 1) and (Equation 2).

  Note that (Equation 1) represents an equation for calculating an average value of “n” calculated inter-sensor differences. “X” in (Expression 1) indicates the value of the difference between sensors. As shown in (Expression 2), the standard deviation “s” is calculated using the average value calculated in (Expression 1).

  That is, the blood vessel state estimation unit 406 calculates a standard deviation for each inter-sensor difference, and acquires the age corresponding to the calculated inter-sensor difference from the threshold table 301. And the acquired age is output to a user as an estimation result. For example, specifically described with reference to the example shown in FIG. 7, the blood vessel state estimation unit 406 estimates that it is “20's” when the calculated standard deviation is “1”. The blood vessel state estimation unit 406 then outputs “20's” as an estimation result to the user via the output unit 203.

  The blood vessel state estimation apparatus 200 may be realized using a known personal computer, workstation, server, mobile phone, PHS (Personal Handyphone System) terminal, mobile communication terminal, or PDA (Personal Digital Assistant). .

  For example, the threshold table 301 shown in FIG. 2 is installed in the server. Further, the server includes a pulse wave interval calculation unit 401, a pulse wave interval calculation unit 402, an nth-order differentiation processing unit 403, a feature point identification unit 404, a difference calculation unit 405, and a blood vessel state estimation unit 406. You may implement | achieve by mounting a function. In this case, for example, when the server receives data from the optical sensor used by the user, the server estimates the state of the blood vessel and outputs the estimation result to the information terminal used by the user.

  Further, for example, the state of the blood vessel may be estimated by distributing and mounting each unit illustrated in FIG. 2 in a plurality of apparatuses. For example, an information terminal (for example, a mobile phone) used by a user may include an optical sensor 201, an optical sensor 202, a pulse wave interval calculation unit 401, and a pulse wave interval calculation unit 402 among the units illustrated in FIG. And an nth-order differentiation processing unit 403, a feature point identification unit 404, and a difference calculation unit 405. In addition, a threshold table 301 and a blood vessel state estimation unit 406 are mounted on the server.

  In this case, the information terminal used by the user transmits the difference data calculated by the difference calculation unit 405 to the server. When the server receives the difference data, the server estimates the state of the blood vessel based on the received difference data. Thereafter, when the estimation process ends, the server transmits the estimation result to the information terminal used by the user. In addition, for example, the server stores the estimation result in a database, and reads and outputs the estimation result from the database when the user accesses the server. In addition, although the case where the information that the information terminal used by the user transmits to the server is a difference calculated by the difference calculation unit 405, the present invention is not limited to this. For example, the information terminal used by the user may calculate the difference between the sensors and transmit it to the server, and which stage data among the processes executed by the pulse wave interval calculation unit 401 to the difference calculation unit 405 may be used. You may send it.

[Processing by blood vessel state estimation device]
Next, an example of the flow of processing performed by the blood vessel state estimation apparatus 200 according to the second embodiment will be described with reference to FIG. FIG. 14 is a flowchart illustrating an example of a process flow performed by the blood vessel state estimation device according to the second embodiment.

  As shown in FIG. 14, when the optical sensor detects a pulse wave of a human body based on the amount of change in light detected in synchronization with another optical sensor (Yes in step S101), the optical sensor converts the pulse wave into an electrical signal. (Step S102). That is, the optical sensor 201 detects the pulse wave of the human body based on the change amount of the light detected in synchronization with the optical sensor 202, and converts the pulse wave into an electrical signal. The optical sensor 202 detects a pulse wave of the human body based on the change amount of light detected in synchronization with the optical sensor 201, and converts the pulse wave into an electrical signal.

  Then, the pulse wave interval calculation unit 401 and the pulse wave interval calculation unit 402 respectively calculate the pulse wave interval for each waveform indicated by the electrical signal converted by the optical sensor (step S103). That is, the pulse wave interval calculation unit 401 identifies the maximum point in the waveform indicated by the electrical signal, and calculates the pulse wave interval by calculating the interval between adjacent maximum points. Then, the pulse wave interval calculation unit 401 and the pulse wave interval calculation unit 402 each identify a place where a pulse jump has occurred using the pulse wave interval (step S104).

  Then, the nth order differential processing unit 403 performs nth order differentiation (n is a natural number) on the waveform indicated by the electrical signal for each optical sensor (step S105). For example, the nth-order differentiation processing unit 403 performs second-order differentiation on the electric signal converted by the optical sensor 201 and performs second-order differentiation on the electric signal converted by the optical sensor 202.

  Then, the feature point identifying unit 404 identifies the feature points included in the nth-order differential waveform that is a waveform obtained as a result of the nth-order differentiation for each optical sensor (step S106). For example, as shown in (1) of FIG. 10, the feature point identifying unit 404 identifies a plurality of feature points for each pulse wave included in the secondary differential waveform for the ear. As shown in (2) of FIG. 10, the feature point identification unit 404 identifies a plurality of feature points for each pulse wave included in the secondary differential waveform for the finger.

  Then, the difference calculation unit 405 calculates the difference in appearance time of the feature points identified by the feature point identification unit 404 for each optical sensor (step S107). For example, as illustrated in (1) of FIG. 11, the difference calculation unit 405 calculates ear differences 1 to 4 for the pulse included in the secondary differential waveform for the ear. Moreover, as shown in (2) of FIG. 11, the difference calculation part 405 calculates the finger differences 1-4 about the pulse contained in the secondary differential waveform about a finger.

  Then, the blood vessel state estimation unit 406 calculates a plurality of inter-sensor differences (step S108). In other words, using the example illustrated in FIG. 10, the blood vessel state estimation unit 406 calculates the difference between the ear differences 1 to 4 and the finger differences 1 to 4, thereby calculating the inter-sensor differences 1 to 4. Is calculated.

  Then, the blood vessel state estimation unit 406 estimates the blood vessel state (step S109). In other words, the blood vessel state estimation unit 406 estimates that the age of the blood vessel is higher than when the inter-sensor differences are widely dispersed, and the case where the inter-sensor differences are widely dispersed, than when the inter-sensor differences are widely dispersed. Also assume that the vascular age is low.

  Then, the blood vessel state estimation unit 406 outputs an estimation result (step S110). For example, the blood vessel state estimation unit 406 outputs an estimation result via the output unit 203 to a user who uses the blood vessel state estimation device 200. For example, the blood vessel state estimation unit 406 outputs that it is “20's”.

  Note that the processing procedure shown in FIG. 14 is not limited to the above-described order, and may be appropriately changed within a range that does not contradict the processing contents. For example, when the blood vessel state estimation device 200 estimates the blood vessel state in step S109, the blood vessel state estimation device 200 may store the estimation result in the storage unit 300 and terminate the process. In this case, for example, when the blood vessel state estimation apparatus 200 separately receives a request for an estimation result from the user, the blood vessel state estimation apparatus 200 reads and outputs the estimation result stored in the storage unit 300. Further, for example, the blood vessel state estimation device 200 may execute steps S104 and S105 or S106 in parallel. In this case, the blood vessel state estimation device 200 executes a process of identifying a pulse skipping portion and executes a secondary differentiation process to identify a feature point. Then, the blood vessel state estimation apparatus 200 calculates the inter-center difference using the processing result that identifies the skipped portion and the identified feature point.

[Effect of Example 2]
As described above, according to the second embodiment, the blood vessel state estimation device 200 includes at least two optical sensors. Moreover, the blood vessel state estimation apparatus 200 detects the pulse wave of a human body based on the variation | change_quantity of the light detected synchronizing with another optical sensor for every optical sensor, and converts a pulse wave into an electrical signal. The blood vessel state estimation apparatus 200 performs an n-order differentiation (n is a natural number) on the electrical signal for each optical sensor, and is included in the n-order differentiation waveform that is a waveform obtained as a result of the n-order differentiation. Identify points. Then, the blood vessel state estimation device 200 calculates the difference in appearance time of feature points for each optical sensor, and estimates the state of the human blood vessel based on the difference calculated for each optical sensor. Then, the blood vessel state estimation device 200 outputs an estimation result. As a result, according to the second embodiment, it is possible to easily and accurately estimate the state of the blood vessel.

  That is, according to the second embodiment, since the appearance time of each feature point is not easily affected by fluctuations due to the blood pressure value or the like, the state of the blood vessel is estimated based on the difference in the appearance time of the feature point. It is possible. Further, according to the second embodiment, the state of the blood vessel can be easily estimated as compared with the method using the cuff.

  Further, according to the second embodiment, the blood vessel state estimation device 200 calculates a plurality of differences for each optical sensor. Then, the blood vessel state estimation device 200 calculates an inter-sensor difference, which is a difference between differences calculated for each optical sensor, for each of a plurality of differences calculated by the difference calculation unit. The blood vessel state estimation apparatus 200 estimates that the age of the blood vessel is higher than when the inter-sensor differences are widely dispersed, and more than when the inter-sensor differences are widely dispersed. Also assume that the vascular age is low. As a result, according to the second embodiment, it is possible to easily and accurately estimate the state of the blood vessel simply by calculating the variance of the difference between the centers.

  Further, according to the second embodiment, at least two photosensors irradiate light to a part of a human body having blood vessels of different thicknesses, so that the state of the blood vessels can be estimated with high accuracy. In other words, if the blood vessel thickness is different, the magnitude of the effect of aging on blood vessel extensibility and elasticity is different. Since the estimation is performed, the state of the blood vessel can be estimated with high accuracy.

  In addition, according to the second embodiment, the blood vessel state estimation device 200 performs secondary differentiation on the electrical signal converted for each optical sensor, and at least four features for each pulse wave included in the secondary differential waveform. Identify points. Then, the blood vessel state estimation device 200 uses the first feature point between the third feature point and the fourth feature point for each pulse wave with respect to the light sensor that irradiates light to a blood vessel that is thicker than the other light sensor. The difference is calculated. In addition, the blood vessel state estimation device 200 uses a second between the first feature point and the second feature point for each pulse wave with respect to an optical sensor that irradiates light to a thin blood vessel as compared with the other optical sensor. The difference is calculated. And the vascular state estimation apparatus 200 calculates each difference between sensors by calculating the difference between a 1st difference and a 2nd difference for every pulse wave. As a result, the state of the blood vessel can be estimated with high accuracy.

  That is, the pulse wave includes a drive wave generated by the heartbeat and a reflected wave generated when the drive wave collides with a blood vessel branch or wall and reflects. For this reason, the pulse wave included in the waveform indicated by the electric signal or the second-order differential waveform includes both components of the drive wave and the reflected wave. Further, if the blood vessels have the same thickness, the more the blood vessels are erased, the stronger the intensity of the reflected wave, and the larger the component occupied by the reflected wave at the peak of the pulse wave. Further, it is considered that the thinner the blood vessel, the stronger the reflected wave, and the larger the component occupied by the reflected wave at the peak of the pulse wave. In addition, when the blood vessel ages, it is considered that the response to the reflected wave becomes worse as a result of the slow return after being stretched (expanded).

  Based on this, the blood vessel state estimation device 200 calculates the difference using the feature points of the places where the influence of the reflected wave that is considered to come after the driving wave is relatively large according to the thickness of the blood vessel. . In the case of using an optical sensor between the ear and the finger, for example, in the case of the ear, the blood vessel is thinner than the finger blood vessel, and the influence of the reflected wave is considered to be stronger than that of the finger. Therefore, the influence of the reflected wave appears near the peak of the pulse waveform. In consideration of this, in the case of the ear, the blood vessel state estimation device 200 calculates a difference using the feature point ab located earlier in the feature points of the secondary differential waveform. In the case of the finger, the blood vessel is thicker than the ear blood vessel. As a result, the influence of the reflected wave is considered to be weaker than that of the ear, and the influence of the reflected wave is behind the peak of the pulse waveform. It is thought to appear. Based on this, the blood vessel state estimation device 200 calculates a difference using the feature point cd at the back. In this way, since the blood vessel state estimation apparatus 200 estimates the blood vessel state using a place where the influence of the reflected wave is considered to be strong, the blood vessel state can be accurately detected and the blood vessel state can be accurately estimated. Is possible.

  Although the first and second embodiments of the present invention have been described so far, the present invention may be implemented in other embodiments in addition to the first and second embodiments described above. Therefore, other embodiments will be described below.

  For example, in the above-described embodiment, the case where the blood vessel state estimation device outputs the age as the estimation result has been described as an example, but the present invention is not limited to this. For example, the blood vessel state estimation device may output whether the blood vessel state is good or not, may output whether the blood vessel age is younger or older than the user's age, and the user can arbitrarily May be set to

[System configuration]
Also, among the processes described in this embodiment, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually can be performed. All or a part can be automatically performed by a known method. For example, in the above-described embodiment, the case where the blood vessel state estimation device 200 estimates the blood vessel state and outputs the estimation result has been described, but the present invention is not limited to this. For example, the blood vessel state estimation apparatus 200 may output only the standard deviation value and the threshold value table for the inter-sensor difference without estimating the blood vessel state.

  In addition, the processing procedures, control procedures, specific names, and information including various data and parameters (FIGS. 1 to 14) shown in the documents and drawings are arbitrarily changed unless otherwise specified. be able to. For example, the data in the threshold table 301 shown in FIG. 3 may be changed by the user to an arbitrary value.

  Further, each component of each illustrated apparatus is functionally conceptual, and does not necessarily need to be physically configured as illustrated. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or a part of the distribution / integration may be functionally or physically distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured. For example, the optical sensor 201, the optical sensor 202, and the output unit 203 may be connected as an external device of the blood vessel state estimation device 200 via a network. Further, the blood vessel state estimation unit 406 and the threshold value table 301 may be provided in different devices, and may be connected via a network to cooperate to realize the above-described function of the blood vessel state estimation device 200.

[Computer]
The various processes described in the above embodiments can be realized by executing a prepared program on a computer such as a personal computer or a workstation. In the following, an example of a computer that executes a blood vessel state estimation program having the same function as that of the above-described embodiment will be described with reference to FIG. FIG. 15 is a schematic diagram illustrating an example of a computer that executes a blood vessel state estimation program according to the second embodiment.

  As illustrated in FIG. 15, the computer 3000 according to the second embodiment includes an operation unit 3001, a microphone 3002, a speaker 3003, a display 3004, an optical sensor 3005, a communication unit 3006, a CPU 3010, a ROM 3011, a HDD (Hard Disk Drive) 3012, a RAM ( Random Access Memory) 3013 is connected by a bus 3009 or the like.

  The ROM 3011 stores a control program that exhibits the same functions as those of the pulse wave interval calculation unit 401 to the blood vessel state estimation unit 406 shown in the second embodiment. In other words, in the example illustrated in FIG. 15, the pulse wave interval calculation program 3011a, the nth-order differentiation processing program 3011b, and the feature point identification program 3011c are stored in advance in the ROM 3011. Further, the ROM 3011 stores a difference calculation program 3011d and a blood vessel state estimation program 3011e in advance. In addition, about these programs 3011a-3011e, you may integrate or isolate | separate suitably like each component of the blood-vessel state estimation apparatus 200 shown in FIG.

  Here, the pulse wave interval calculation program 3011 a is a control program that exhibits the same function as the pulse wave interval calculation unit 402. The n-th order differential processing program 3011b is a control program that exhibits the same function as the n-th order differential processing unit 403. The feature point identification program 3011c is a control program that exhibits the same function as the feature point identification unit 404.

  The CPU 3010 reads out the programs 3011a to 3011b from the ROM 3011 and executes them, thereby functioning as a pulse wave interval calculation process 3010a and an nth-order differentiation process 3010b. In addition, the CPU 3010 functions as an nth-order differentiation process 3011c by reading and executing the programs 3011c to 3011e from the ROM 3011. The CPU 3010 functions as a difference calculation process 3010d and a blood vessel state estimation process 3010e by reading the programs 3011d to 3011e from the ROM 3011 and executing them.

  Each of the processes 3010a to 3010e includes a pulse wave interval calculation unit 401, a pulse wave interval calculation unit 402, an nth-order differential processing unit 403, a feature point identification unit 404, and a difference calculation unit 405 illustrated in FIG. And the blood vessel state estimation unit 406, respectively.

  The HDD 3012 is provided with a threshold table 3012a. Note that the threshold value table 3012a corresponds to the threshold value table 301 illustrated in FIG.

  Then, the CPU 3010 reads the threshold table 3012a and stores it in the RAM 3013. Then, the CPU 3010 uses the threshold data 3013a, the light change amount data 3013b, the electric wave meter data 3013c, the second derivative wave meter data 3013d, and the difference data 3013e stored in the RAM 3013, using the blood vessel. Run the state estimation program.

[Others]
The blood vessel state estimation program described in this embodiment can be distributed via a network such as the Internet. The blood vessel state estimation program can also be executed by being recorded on a computer-readable recording medium such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, or a DVD, and being read from the recording medium by the computer. .

DESCRIPTION OF SYMBOLS 100 Blood vessel state estimation apparatus 101 Optical sensor 102 Optical sensor 103 Pulse wave detection part 104 Feature point identification part 105 Difference calculation part 106 Blood vessel state estimation part 200 Blood vessel state estimation apparatus 201 Optical sensor 202 Optical sensor 203 Output part 300 Storage part 301 Threshold table 400 Control Unit 401 Pulse Wave Interval Calculation Unit 402 Pulse Wave Interval Calculation Unit 403 nth Order Differentiation Processing Unit 404 Feature Point Identification Unit 405 Difference Calculation Unit 406 Blood Vessel State Estimation Unit 501 Aperture Control Rubber 502 Visible Light Cut Filter 503 Mounted Substrate 504 Cover Case 505 Light emitting element 506 Light receiving element

Claims (6)

A light emitting element that irradiates light to the human body, and a light receiving element that detects a change amount of light transmitted from the light emitting element and then transmitted through the human body, or a change amount of light reflected from the human body after being emitted from the light emitting element. A pulse for detecting a pulse wave of the human body based on a change amount of light detected in synchronization with another optical sensor and converting the pulse wave into an electric signal for each of at least two optical sensors having an element; A wave detector;
For each of the optical sensors, n-order differentiation (n is a natural number) is performed on the electrical signal converted by the pulse wave detection unit, and the waveform is obtained as a result of the n-order differentiation. A feature point identifying unit for identifying the feature point to be
A difference calculation unit that calculates a difference in appearance time of feature points identified by the feature point identification unit for each of the optical sensors;
A blood vessel state estimation device comprising: a blood vessel state estimation unit that estimates a blood vessel state of the human body based on a difference calculated for each of the optical sensors by the difference calculation unit and outputs an estimation result. The difference calculation unit calculates a plurality of differences for each of the optical sensors,
The blood vessel state estimation unit calculates an inter-sensor difference, which is a difference between differences calculated for each optical sensor, for each of a plurality of differences calculated by the difference calculation unit, and each of the inter-sensor differences is widely dispersed. The blood vessel age is estimated to be higher than the case where the blood vessel age is higher than that in the case of narrow dispersion, and the blood vessel age is estimated to be lower than that in the case of wide dispersion when each of the differences between the sensors is narrowly distributed. The blood vessel state estimation device according to 1.   2. The blood vessel state estimation apparatus according to claim 1, wherein at least two of the optical sensors irradiate light to a part of a human body having blood vessels of different thicknesses. The feature point identification unit performs second order differentiation on the electrical signal converted by the pulse wave detection unit for each of the optical sensors, and at least four feature points for each pulse wave included in the second order differential waveform Identify and
For the optical sensor that irradiates light to a blood vessel that is thicker than the other optical sensor, the difference calculating unit is the third feature point that has the third appearance time among the at least four feature points for each pulse wave. And at least four feature points for each pulse wave with respect to an optical sensor that irradiates light to a thin blood vessel compared to the other optical sensor. A second difference between the first feature point of which appearance time is the first and the second feature point of the second from the previous time,
The blood vessel state estimation unit according to claim 3, wherein the blood vessel state estimation unit calculates each difference between sensors by calculating a difference between the first difference and the second difference for each pulse wave. Estimating device. A method executed by an information processing apparatus,
A light emitting element that irradiates light to the human body, and a light receiving element that detects a change amount of light transmitted from the light emitting element and then transmitted through the human body, or a change amount of light reflected from the human body after being emitted from the light emitting element. A pulse for detecting a pulse wave of the human body based on a change amount of light detected in synchronization with another optical sensor and converting the pulse wave into an electric signal for each of at least two optical sensors having an element; A wave detection step;
For each of the optical sensors, n-order differentiation (n is a natural number) is performed on the electrical signal converted by the pulse wave detection step, and the waveform is obtained as a result of the n-order differentiation. A feature point identifying step for identifying the feature points to be
A difference calculating step for calculating a difference between appearance times of feature points identified by the feature point identifying step for each of the optical sensors;
A blood vessel state estimation method comprising: estimating a blood vessel state of the human body based on the difference calculated for each of the optical sensors in the difference calculation step, and outputting an estimation result. In the information processing device,
A light emitting element that irradiates light to the human body, and a light receiving element that detects a change amount of light transmitted from the light emitting element and then transmitted through the human body, or a change amount of light reflected from the human body after being emitted from the light emitting element. A pulse for detecting a pulse wave of the human body based on a change amount of light detected in synchronization with another optical sensor and converting the pulse wave into an electric signal for each of at least two optical sensors having an element; Wave detection procedure;
For each of the optical sensors, n-order differentiation (n is a natural number) is performed on the electrical signal converted by the pulse wave detection procedure, and the waveform is obtained as a result of the n-order differentiation. A feature point identification procedure for identifying a feature point to be
A difference calculation procedure for calculating a difference between appearance times of feature points identified by the feature point identification procedure for each of the optical sensors;
A blood vessel state estimation program for executing a blood vessel state estimation procedure for estimating a blood vessel state of the human body based on a difference calculated for each of the optical sensors by the difference calculation procedure and outputting an estimation result.

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