JPWO2020111203A1 - Blood flow disorder judgment device, blood flow disorder judgment method, blood flow disorder judgment program and blood flow disorder judgment system - Google Patents

Abstract

Provided is a blood flow disorder determination device or the like capable of determining a blood flow disorder by reducing the artifacts included in the pulse wave data. The blood flow disorder determination device (10) has an acquisition unit (11) for acquiring a plurality of pulse wave data obtained by measuring the temporal change of the pulse wave of the living body (1) in a plurality of different periods, and a plurality of pulse wave data, respectively. A generation unit (12) that performs Fourier transform to generate a plurality of spectral data, a detection unit (13) that detects one or a plurality of peaks included in the plurality of spectral data, and one or a plurality of units for each predetermined frequency interval. A calculation unit (14) that calculates the frequency at which peaks are detected, a first determination unit (15) that determines whether one or more peaks are artifacts based on the frequency, and one or more peaks. Is provided with a second determination unit (16) for determining whether or not a blood flow disorder has occurred in the living body based on a plurality of spectral data when it is determined that is not an artifact.

Description

The present invention relates to a blood flow disorder determination device, a blood flow disorder determination method, a blood flow disorder determination program, and a blood flow disorder determination system.

Conventionally, in the medical field, medical staff determines whether or not blood flow disorders such as congestion and ischemia occur. For example, the refill method, which is judged by the time from when the patient's living tissue is pressed to discolor and the color returns to the original color, the method which is judged by the color of the living tissue, and the bleeding state when the needle is pierced into the living tissue. The possibility of blood flow disorder is judged by the method.

As a technique for automating the detection of blood flow disorders, Patent Document 1 below describes a sensor sheet in which a plurality of types of sensing means for measuring different blood flow information of living tissues are arranged on a flexible base material. A blood flow disorder detection device having the above is described.

International Publication No. 2017/023633

According to the technique described in Patent Document 1, blood flow disorders can be detected based on the patient's pulse wave, skin color, and skin temperature measured by a wearable sensor.

However, when the measurement is performed for a long period of time, the patient is not always stationary, and the patient's body movement may cause artifacts to be mixed in the pulse wave data. If the pulse wave data contains an artifact, it may be mistakenly judged as a blood flow disorder or the blood flow disorder may be overlooked.

Therefore, the present invention provides a blood flow disorder determination device, a blood flow disorder determination method, a blood flow disorder determination program, and a blood flow disorder determination system that can determine blood flow disorders by reducing artifacts contained in pulse wave data. do.

The blood flow disorder determination device according to one aspect of the present invention includes an acquisition unit that acquires a plurality of pulse wave data obtained by measuring a time change of a pulse wave of a living body in a plurality of different periods, and a Fourier transform of the plurality of pulse wave data. A generator that generates a plurality of spectrum data, a detection unit that detects one or a plurality of peaks included in the plurality of spectrum data, and a frequency in which one or a plurality of peaks are detected for each predetermined frequency section are calculated. The calculation unit to be used, the first determination unit for determining whether one or more peaks are artifacts based on the frequency, and a plurality of spectral data when it is determined that one or more peaks are not artifacts. A second determination unit for determining whether or not a blood flow disorder has occurred in the living body based on the above.

According to this aspect, pulse wave data is determined by determining whether one or more peaks are artifacts based on the frequency of one or more peaks contained in the spectral data rather than the power of the spectral data. Blood flow disorders can be determined by reducing the artifacts contained in.

In the above aspect, the first determination unit may determine whether one or more peaks are artifacts when the sum of the powers of the plurality of spectral data is equal to or greater than the first threshold value.

According to this aspect, when the power of the spectral data is sufficiently high, it is determined whether or not one or more peaks are artifacts, and the artifacts contained in the pulse wave data are reduced to determine the blood flow disorder. be able to.

In the above embodiment, the second determination unit identifies the most frequent frequency interval among the one or a plurality of peaks determined not to be artifacts, and the average value of the power of the frequency intervals of the plurality of spectral data is equal to or less than the second threshold value. If this is the case, it may be determined that the living body has a blood flow disorder.

According to this aspect, the power corresponding to the frequency of the pulse wave can be grasped more accurately, and the occurrence of blood flow disorder can be determined more accurately.

In the above aspect, the second determination unit applies to the living body when the sum of the powers of the plurality of spectral data is less than the first threshold value and the average value of the sum of the powers of the plurality of spectral data is equal to or less than the second threshold value. It may be determined that a blood flow disorder has occurred.

According to this aspect, when the power of the spectral data is relatively low, the occurrence of blood flow abnormality is determined by whether or not the average value of the sum of the powers of a plurality of spectral data is sufficiently high, thereby causing a blood flow disorder. Can be determined more accurately.

In the above aspect, the acquisition unit acquires time-series data including at least one of color data obtained by measuring the time change of the color of the living body and temperature data measuring the time change of the temperature of the living body, and approximates the time-series data. A second determination unit further includes a determination unit that determines the value of one or more parameters included in a predetermined function, and a first estimation unit that estimates the degree of risk based on the values of the one or more parameters. May determine whether or not a blood flow disorder has occurred in the living body based on the degree of risk.

According to this aspect, the occurrence of blood flow disorder can be determined from a viewpoint different from that of the pulse wave, based on at least one time change of the color and temperature of the living body.

In the above embodiment, the first estimation unit calculates an index based on the value of one or more parameters and the coefficient of determination of one or more parameters, and updates the degree of risk based on the index, thereby changing the risk over time. The degree may be estimated.

According to this aspect, an index can be calculated based on the goodness of fitting the approximation by a predetermined function and the magnitude of the time change, and the risk of time change can be estimated.

In the above embodiment, when time is represented by t and one or more parameters are represented by A, A ₀ and τ, the predetermined function may be A × exp (−t / τ) + A ₀ .

According to this aspect, it is possible to approximate the situation where the time series data changes exponentially by a predetermined function and calculate the degree of risk according to the magnitude of the change.

In the above embodiment, when the absolute value of the index is equal to or higher than the third threshold value, the first estimation unit updates the risk level by adding the index value to the previous value of the risk level, and the absolute value of the index is the third threshold value. If it is less than, the risk may be updated by the larger of the previous value of the risk and the index.

According to this aspect, it is possible to calculate the degree of risk according to the magnitude of the change in both the case where the time series data decreases and the case where the time series data increases.

In the above aspect, the time-varying pulse wave risk is determined based on the rate at which it is determined that blood flow disorder occurs when the first determination unit and the second determination unit make a plurality of determinations in a predetermined period. A second estimation unit for estimation may be further provided.

According to this aspect, it is possible to reduce the artifacts contained in the pulse wave data and estimate the time-varying pulse wave risk.

In the above aspect, the second determination unit uses a plurality of pulse wave data to determine whether or not a blood flow disorder has occurred in the living body when it is determined that one or more peaks are not artifacts. , Color data and temperature data are used to comprehensively determine whether or not the living body has a blood flow disorder based on the result of determining whether or not the living body has a blood flow disorder. May be good.

According to this aspect, it is possible to reduce the artifacts based on the pulse wave data of the living body and comprehensively determine whether or not the blood flow disorder occurs based on the pulse wave, the color and the temperature.

In the above aspect, the second determination unit may comprehensively determine that the blood flow disorder occurs in the living body when at least one of the pulse wave risk and the risk is equal to or higher than the fourth threshold.

According to this aspect, oversight of blood flow disorder is reduced by comprehensively determining that blood flow disorder occurs when there is a high risk of blood flow disorder for at least one of the pulse wave, color, and temperature of the living body. be able to.

In the above embodiment, the color data includes infrared data, and the determination unit determines the values of one or more parameters included in a predetermined function that approximates the noise-removed time series data based on the infrared data. You may.

According to this aspect, the risk of blood flow disorder can be calculated more accurately by removing noise from color data based on infrared data.

In the above aspect, the calculation unit determines whether or not the probability distribution of the pulse wave data measured in the reference period among the plurality of different periods is equal to the probability distribution of the pulse wave data measured in the target period among the plurality of different periods. The test statistic for testing the above may be calculated, and the second determination unit may determine whether or not a blood flow disorder has occurred in the living body based on the test statistic.

According to this aspect, by paying attention to the difference between the probability distribution of the pulse wave data in the reference period and the probability distribution of the pulse wave data in the target period, the characteristics of the pulse wave data are relatively evaluated, and the blood flow disorder. Can be determined whether or not is occurring.

The method for determining blood flow disorder according to another aspect of the present invention is to acquire a plurality of pulse wave data obtained by measuring a time change of a pulse wave of a living body in a plurality of different periods, and to Fourier transform the plurality of pulse wave data. To generate a plurality of spectral data, detect one or a plurality of peaks contained in the plurality of spectral data, and calculate the frequency at which one or a plurality of peaks are detected for each predetermined frequency section. And, based on the frequency, it is determined whether or not one or more peaks are artifacts, and when it is determined that one or more peaks are not artifacts, the living body is determined based on a plurality of spectral data. Includes determining whether or not a blood flow disorder has occurred.

According to this aspect, pulse wave data is determined by determining whether one or more peaks are artifacts based on the frequency of one or more peaks contained in the spectral data rather than the power of the spectral data. Blood flow disorders can be determined by reducing the artifacts contained in.

In the blood flow disorder determination program according to another aspect of the present invention, the processor provided in the blood flow disorder determination device acquires a plurality of pulse wave data obtained by measuring the temporal change of the pulse wave of the living body in a plurality of different periods. An acquisition unit, a generation unit that generates a plurality of spectrum data by Fourier transforming a plurality of pulse wave data, a detection unit that detects one or a plurality of peaks included in a plurality of spectrum data, and one or one for each predetermined frequency section. A calculation unit that calculates the frequency at which multiple peaks are detected, a first determination unit that determines whether one or more peaks are artifacts based on the frequency, and a determination that one or more peaks are not artifacts. If so, it functions as a second determination unit for determining whether or not a blood flow disorder has occurred in the living body based on a plurality of spectral data.

According to this aspect, pulse wave data is determined by determining whether one or more peaks are artifacts based on the frequency of one or more peaks contained in the spectral data rather than the power of the spectral data. Blood flow disorders can be determined by reducing the artifacts contained in.

The blood flow disorder determination system according to another aspect of the present invention measures a time change of a pulse wave of a living body in a plurality of different periods and outputs a plurality of pulse wave data, and a plurality of pulse wave data. It is a blood flow disorder determination system equipped with a blood flow disorder determination device that determines whether or not a blood flow disorder has occurred in a living body by using the blood flow disorder determination device. A generator that generates a plurality of spectrum data, a detection unit that detects one or a plurality of peaks included in the plurality of spectrum data, and a frequency of detecting one or a plurality of peaks in a predetermined frequency section are calculated. A calculation unit to be used, a first determination unit for determining whether or not one or more peaks are artifacts based on the frequency, and a plurality of spectral data when it is determined that one or more peaks are not artifacts. Based on the above, it has a second determination unit for determining whether or not a blood flow disorder has occurred in the living body.

According to this aspect, pulse wave data is determined by determining whether one or more peaks are artifacts based on the frequency of one or more peaks contained in the spectral data rather than the power of the spectral data. Blood flow disorders can be determined by reducing the artifacts contained in.

According to the present invention, a blood flow disorder determination device, a blood flow disorder determination method, a blood flow disorder determination program, and a blood flow disorder determination system capable of determining a blood flow disorder by reducing artifacts contained in pulse wave data are provided. can do.

It is a figure which shows the outline of the blood flow disorder determination system which concerns on embodiment of this invention. It is a figure which shows the outline of the sensor provided in the blood flow disorder determination system which concerns on this embodiment. It is a figure which shows the functional block of the blood flow disorder determination apparatus which concerns on this embodiment. It is a figure which shows the physical structure of the blood flow disorder determination apparatus which concerns on this embodiment. It is a flowchart of the 1st process executed by the blood flow disorder determination system which concerns on this embodiment. It is a flowchart of the 2nd process executed by the blood flow disorder determination apparatus which concerns on this embodiment. It is a figure which shows one or a plurality of peaks included in a plurality of spectrum data and a plurality of spectrum data generated by the blood flow disorder determination apparatus which concerns on this embodiment. It is a figure which shows the 1st example of the frequency of one or a plurality of peaks calculated by the blood flow disorder determination apparatus which concerns on this embodiment. It is a figure which shows the 2nd example of the frequency of one or a plurality of peaks calculated by the blood flow disorder determination apparatus which concerns on this embodiment. It is a flowchart of the 3rd process executed by the blood flow disorder determination system which concerns on this embodiment. It is a figure which shows the degree of risk estimated based on the color data by the blood flow disorder determination apparatus which concerns on this embodiment. It is a flowchart of the 4th process executed by the blood flow disorder determination system which concerns on this embodiment. It is a figure which shows the degree of risk estimated based on the temperature data by the blood flow disorder determination apparatus which concerns on this embodiment. It is a flowchart of the 5th process executed by the blood flow disorder determination system which concerns on this embodiment. It is a figure which shows the 1st example of the risk degree and the detection rate of the artifact comprehensively determined by the blood flow disorder determination apparatus which concerns on this embodiment. It is a figure which shows the 2nd example of the risk degree and the detection rate of the artifact which were comprehensively judged by the blood flow disorder determination apparatus which concerns on this embodiment. It is a flowchart of the 6th process executed by the blood flow disorder determination system which concerns on this embodiment. It is a figure which shows the D value calculated by the blood flow disorder determination apparatus which concerns on this embodiment, and the blood flow disorder detection timing. It is a flowchart of the 7th process executed by the blood flow disorder determination system which concerns on this embodiment. It is a figure which shows the color data which was measured by the blood flow disorder determination system which concerns on this embodiment, and the color data which noise-removed and the color data which was not noise-removed. It is a figure which shows the degree of risk estimated based on the color data by the blood flow disorder determination apparatus which concerns on this embodiment.

Embodiments of the present invention will be described with reference to the accompanying drawings. In each figure, those having the same reference numerals have the same or similar configurations.

FIG. 1 is a diagram showing an outline of a blood flow disorder determination system 100 according to an embodiment of the present invention. The blood flow disorder determination system 100 includes a blood flow disorder determination device 10, a sensor 20, and a transmitter 30.

The blood flow disorder determination system 100 measures the time change of the pulse wave of the living body 1 in a plurality of different periods by the flexible sensor 20 attached to the living body 1, and the measured pulse wave data is transmitted to the blood flow via the transmitter 30. It is transmitted to the disorder determination device 10 and determines whether or not the blood flow disorder is caused in the living body 1 by the blood flow disorder determination device 10. Here, impaired blood flow includes congestion and ischemia. In the present embodiment, the sensor 20 and the transmitter 30 are connected by wire communication, and the transmitter 30 and the blood flow disorder determination device 10 are connected by wireless communication. However, the communication method is arbitrary. Further, in the present embodiment, the blood flow disorder determination device 10 is composed of a tablet computer. However, the blood flow disorder determination device 10 may be composed of a laptop computer or another type of computer.

Further, the blood flow disorder determination system 100 measures the time change of the color of the living body 1 by the sensor 20 and measures the time change of the temperature of the living body 1, and transmits the measured color data and the temperature data to the transmitter 30. It is transmitted to the blood flow disorder determination device 10 via the blood flow disorder determination device 10, and it is determined whether or not the blood flow disorder occurs in the living body 1 by the blood flow disorder determination device 10.

FIG. 2 is a diagram showing an outline of a sensor 20 included in the blood flow disorder determination system 100 according to the present embodiment. The sensor 20 measures the time change of the pulse wave of the living body 1, the pulse wave sensor 21 that measures the time change of the pulse wave of the living body 1 in a plurality of different periods, the color sensor 22 that measures the time change of the color of the living body 1, and the time change of the temperature of the living body 1. It has a temperature sensor 23 and a temperature sensor 23. The numerical unit of the measure shown in FIG. 2 is cm.

The sensor 20 according to the present embodiment is configured by mounting four pulse wave sensors 21, four color sensors 22, and four temperature sensors 23 on a flexible substrate 25. Further, the sensor 20 is configured such that one pulse wave sensor 21, one color sensor 22, and one temperature sensor 23 output one channel of blood flow data. The sensor 20 according to this embodiment outputs blood flow data of a total of 4 channels.

The flexible substrate 25 is attached to the living body 1 so as to follow the deformation of the body surface. The pulse wave sensor 21 may be composed of, for example, an optical pulse wave sensor that irradiates the living body 1 with light and measures the pulse wave based on the amount of light absorbed. The color sensor 22 may be composed of, for example, a photodiode that detects infrared rays, a photodiode that detects red light, a photodiode that detects green light, and a photodiode that detects blue light. The temperature sensor 23 may be composed of, for example, a thermistor.

FIG. 3 is a diagram showing a functional block of the blood flow disorder determination device 10 according to the present embodiment. The blood flow disorder determination device 10 includes an acquisition unit 11, a generation unit 12, a detection unit 13, a calculation unit 14, a first determination unit 15, a second determination unit 16, a determination unit 17, a first estimation unit 18, and a second estimation unit. 19 is provided.

The acquisition unit 11 acquires a plurality of pulse wave data obtained by measuring the time change of the pulse wave of the living body 1 in a plurality of different periods from the pulse wave sensor 21 via the transmitter 30. Further, the acquisition unit 11 acquires the color data obtained by measuring the time change of the color of the living body 1 from the color sensor 22 via the transmitter 30. Further, the acquisition unit 11 acquires temperature data obtained by measuring the time change of the temperature of the living body 1 from the temperature sensor 23 via the transmitter 30.

The generation unit 12 Fourier transforms each of the plurality of pulse wave data to generate a plurality of spectral data. The generation unit 12 may generate a plurality of spectral data by performing a fast Fourier transform on the plurality of pulse wave data measured at a predetermined sampling rate. The predetermined sampling rate may be, for example, 16 Hz.

The detection unit 13 detects one or a plurality of peaks included in the plurality of spectral data. The detection unit 13 may detect the maximum point of a plurality of spectral data as one or a plurality of peaks.

The calculation unit 14 calculates the frequency at which one or more peaks are detected for each predetermined frequency section. The calculation unit 14 may calculate the frequency at which one or more peaks are detected, for example, every 0.075 Hz.

The first determination unit 15 determines whether or not one or more peaks are artifacts based on the frequency with which one or more peaks are detected. Details of the determination by the first determination unit 15 will be described later.

The first determination unit 15 may determine whether or not one or more peaks are artifacts when the sum of the powers of the plurality of spectral data is equal to or greater than the first threshold value. The first determination unit 15 does not have to determine whether or not one or a plurality of peaks are artifacts when the sum of the powers of the plurality of spectral data is not equal to or more than the first threshold value. In this way, when the power of the spectral data is sufficiently high, it is possible to determine whether or not one or more peaks are artifacts, and to reduce the artifacts contained in the pulse wave data to determine the blood flow disorder. can.

When it is determined that one or a plurality of peaks are not artifacts, the second determination unit 16 determines whether or not the blood flow disorder occurs in the living body 1 based on the plurality of spectral data. Details of the determination by the second determination unit 16 will be described later.

According to the blood flow disorder determination device 10 according to the present embodiment, whether or not one or more peaks are artifacts based on the frequency of one or more peaks included in the spectrum data, not on the power of the spectrum data. By determining, it is possible to reduce the artifacts contained in the pulse wave data and determine the blood flow disorder.

The determination unit 17 determines the values of one or more parameters included in a predetermined function that approximates the time series data including at least one of the color data and the temperature data. Specifically, when time is represented by t and one or more parameters are represented by A, A ₀ and τ, the predetermined function may be A × exp (−t / τ) + A ₀ . In this way, the situation in which the time series data changes exponentially can be approximated by a predetermined function, and the degree of risk according to the magnitude of the change can be calculated.

The first estimation unit 18 estimates the degree of risk based on the values of one or a plurality of parameters. Details of the estimation by the first estimation unit 18 will be described later. The second determination unit 16 may determine whether or not the blood flow disorder has occurred in the living body 1 based on the estimated risk level. In this way, the occurrence of blood flow disorder can be determined from a viewpoint different from that of the pulse wave, based on at least one time change of the color and temperature of the living body 1.

The second estimation unit 19 changes with time based on the rate at which it is determined that a blood flow disorder has occurred when the first determination unit 15 and the second determination unit 16 make a plurality of determinations in a predetermined period. Estimate the pulse wave risk. The pulse wave risk may be estimated independently of the risk estimated by the first estimation unit 18 based on the color data and the temperature data. The second estimation unit 19 can reduce the artifacts contained in the pulse wave data and estimate the time-varying pulse wave risk.

FIG. 4 is a diagram showing a physical configuration of the blood flow disorder determining device 10 according to the present embodiment. The blood flow disorder determination device 10 communicates with a CPU (Central Processing Unit) 10a corresponding to a processor, a RAM (Random Access Memory) 10b corresponding to a storage unit, and a ROM (Read only Memory) 10c corresponding to a storage unit. It has a unit 10d, an input unit 10e, and a display unit 10f. Each of these configurations is connected to each other via a bus so that data can be transmitted and received. In this example, the case where the blood flow disorder determination device 10 is composed of one computer will be described, but the blood flow disorder determination device 10 may be realized by combining a plurality of computers. Further, the configuration shown in FIG. 4 is an example, and the blood flow disorder determining device 10 may have a configuration other than these, or may not have a part of these configurations.

The CPU 10a is a control unit that controls execution of a program stored in the RAM 10b or ROM 10c, calculates data, and processes data. The CPU 10a is a calculation unit that executes a program (blood flow disorder determination program) for determining a blood flow disorder of the living body 1 based on pulse wave data, color data, and temperature data. The CPU 10a receives various data from the input unit 10e and the communication unit 10d, displays the calculation result of the data on the display unit 10f, and stores it in the RAM 10b or ROM 10c.

The RAM 10b is a storage unit in which data can be rewritten, and may be composed of, for example, a semiconductor storage element. The RAM 10b may store a blood flow disorder determination program, pulse wave data, color data, temperature data, and the like executed by the CPU 10a. It should be noted that these are examples, and data other than these may be stored in the RAM 10b, or a part of these may not be stored.

The ROM 10c is a storage unit capable of reading data, and may be composed of, for example, a semiconductor storage element. The ROM 10c may store, for example, a blood flow disorder determination program or data that is not rewritten.

The communication unit 10d is an interface for connecting the blood flow disorder determination device 10 to another device. The communication unit 10d may be connected to a communication network N such as the Internet.

The input unit 10e receives data input from the user, and may include, for example, a keyboard and a touch panel.

The display unit 10f visually displays the calculation result by the CPU 10a, and may be configured by, for example, an LCD (Liquid Crystal Display). The display unit 10f may display pulse wave data, color data, and the risk of blood flow disorder.

The blood flow disorder determination program may be stored in a storage medium readable by a computer such as RAM 10b or ROM 10c and provided, or may be provided via a communication network connected by the communication unit 10d. In the blood flow disorder determination device 10, the CPU 10a executes the blood flow disorder determination program to realize various operations described with reference to FIG. It should be noted that these physical configurations are examples and do not necessarily have to be independent configurations. For example, the blood flow disorder determination device 10 may include an LSI (Large-Scale Integration) in which the CPU 10a and the RAM 10b or ROM 10c are integrated.

FIG. 5 is a flowchart of the first process executed by the blood flow disorder determination system 100 according to the present embodiment. The first process is a process of calculating the pulse wave risk based on the pulse wave data.

First, the blood flow disorder determination system 100 measures the pulse wave data at a predetermined sampling rate by the pulse wave sensor 21 (S10). After that, the blood flow disorder determination device 10 divides a series of pulse wave data into a predetermined length (S11). For example, the blood flow disorder determination device 10 divides the pulse wave data measured continuously for about 3 minutes into 9 data having a length of about 21 seconds, and removes each of the first half 5 seconds of the 9 data. Then, nine pulse wave data of about 16 seconds may be created. Nine pulse wave data of about 16 seconds may include sampling data of 256 points.

The blood flow disorder determining device 10 Fourier transforms a plurality of pulse wave data to generate a plurality of spectral data (S12). Specifically, the blood flow disorder determination device 10 performs a high-speed Fourier transform on nine pulse wave data having a length of about 16 seconds to generate nine spectral data.

The blood flow disorder determination device 10 calculates the total power of the plurality of spectral data (S13). Here, the total power may be a value obtained by integrating the power of the spectral data for a predetermined frequency range. The predetermined frequency range may be, for example, 0.5 to 2 Hz. In addition, 0.5 to 2 Hz corresponds to 30 to 120 bpm. The blood flow disorder determination device 10 may calculate the total power for each of the nine spectral data.

The blood flow disorder determination device 10 determines whether or not the total power of the spectrum data is equal to or greater than the first threshold value (S14). When the total power is equal to or higher than the first threshold value (S14: YES), that is, when the signal strength of the pulse wave data is sufficiently strong, the blood flow disorder determining device 10 excludes the artifacts and performs a process of calculating the evaluation value. (S15). This process will be described in detail with reference to the following figure. When the blood flow disorder determination device 10 excludes the pulse wave data as an artifact (S16: YES), the blood flow disorder determination device 10 ends the first process without performing the subsequent process. On the other hand, when the evaluation value is calculated without excluding the pulse wave data as an artifact (S16: NO), the subsequent processing is performed.

On the other hand, when the total power is not equal to or higher than the first threshold value (S14: NO), that is, when the signal intensity of the pulse wave data is weak, the blood flow disorder determination device 10 uses the average value of the total powers of the plurality of spectral data as the evaluation value. Calculate (S17). When the sum of the powers of the plurality of spectral data is less than the first threshold value, the blood flow disorder determining device 10 may calculate the evaluation value by the average value of the sum of the powers of the plurality of spectral data. For example, when the total power of the spectrum data _{is expressed as P tot} , the blood flow disorder determination device 10 may calculate the evaluation value by (1 / (2 Hz-0.5 Hz)) × (16 Hz / 256) × P _tot. ..

When the calculated evaluation value is equal to or less than the second threshold value (S18: YES), the blood flow disorder determining device 10 determines that the blood flow disorder has occurred (S19). On the other hand, when the calculated evaluation value is not equal to or less than the second threshold value (S18: NO), the blood flow disorder determining device 10 determines that no blood flow disorder has occurred (S20).

Finally, the blood flow disorder determination device 10 is based on the rate at which it is determined that a blood flow disorder has occurred when the first determination unit 15 and the second determination unit 16 make a plurality of determinations in a predetermined period. , Calculate the pulse wave risk (S21). For example, the blood flow disorder determination device 10 divides the number of times the second determination unit 16 determines that a blood flow disorder has occurred in 30 minutes by the total number of determinations by the second determination unit 16. , The pulse wave risk may be calculated. With the above, the first process is completed.

FIG. 6 is a flowchart of the second process executed by the blood flow disorder determination device 10 according to the present embodiment. The second process is a process of calculating an evaluation value after excluding artifacts when the total power of the spectrum data is equal to or greater than the first threshold value. FIG. 5 shows the details of the process (S15) of “excluding artifacts and calculating the evaluation value” shown in FIG.

First, the blood flow disorder determining device 10 detects one or a plurality of peaks included in a plurality of spectral data (S151). For example, the blood flow disorder determination device 10 may detect a maximum point having a size of 1/3 or more of the maximum value as one or a plurality of peaks among the maximum points of a plurality of spectral data.

The blood flow disorder determination device 10 calculates the frequency at which one or a plurality of peaks are detected for each predetermined frequency section (S152). For example, the blood flow disorder determination device 10 may calculate the frequency at which one or a plurality of peaks are detected for each section of 0.075 Hz.

The blood flow disorder determining device 10 determines whether or not the highest frequency among the frequencies of one or a plurality of peaks is equal to or higher than the reference value (S153). For example, when one or a plurality of peaks are detected from each of the nine spectral data, the number of times the peaks are detected in each frequency interval is a value of 0 to 9. In this case, the reference value may be set to 6, and it may be determined whether or not the maximum frequency of one or a plurality of peaks is 6 or more.

When the highest frequency of the frequencies of one or a plurality of peaks is equal to or higher than the reference value (S153: YES), the blood flow disorder determining device 10 specifies the frequency section of the highest frequency (S154). Then, the blood flow disorder determination device 10 calculates the average value of the powers of the plurality of spectral data relating to the specified frequency interval as the evaluation value (S155). The blood flow disorder determination device 10 identifies the most frequent frequency section among one or a plurality of peaks determined not to be an artifact, and calculates the average value of the powers of a plurality of spectral data related to the frequency section as an evaluation value. It's okay.

On the other hand, when the highest frequency of the frequency of one or a plurality of peaks is not equal to or higher than the reference value (S153: NO), the blood flow disorder determining device 10 determines the peak as an artifact and excludes it (S156). In this way, the blood flow disorder determining device 10 determines whether or not one or more peaks are artifacts based on the frequency of one or more peaks contained in the spectral data rather than the power of the spectral data. By doing so, the artifacts contained in the pulse wave data can be reduced. With the above, the second process is completed.

The blood flow disorder determination device 10 identifies the most frequent frequency section among the one or a plurality of peaks determined not to be an artifact, and the average value of the powers of the plurality of spectral data relating to the frequency section is equal to or less than the second threshold value. In a certain case, it is determined that the living body 1 has a blood flow disorder. As a result, the power corresponding to the frequency of the pulse wave can be grasped more accurately, and the occurrence of blood flow disorder can be determined more accurately.

Further, the blood flow disorder determining device 10 is a living body 1 when the sum of the powers of the plurality of spectral data is less than the first threshold value and the average value of the sum of the powers of the plurality of spectral data is equal to or less than the second threshold value. It is determined that blood flow disorder has occurred in. In this way, when the power of the spectral data is relatively low, the occurrence of blood flow disorder is determined by determining whether or not the average value of the sum of the powers of a plurality of spectral data is sufficiently high. Can be determined more accurately.

FIG. 7 is a diagram showing one or a plurality of peaks P1 to P9 included in the plurality of spectral data S1 to S9 and the plurality of spectral data S1 to S9 generated by the blood flow disorder determining device 10 according to the present embodiment. .. Each of the plurality of spectral data S1 to S9 shows the frequency on the horizontal axis in Hz and the power on the vertical axis in arbitrary units. Further, one or a plurality of peaks P1 to P9 each indicate a frequency on the horizontal axis in an arbitrary unit and a power on the vertical axis in an arbitrary unit.

The plurality of spectral data S1 to S9 are data obtained by performing a high-speed Fourier transform on each of the nine pulse wave data. Further, one or a plurality of peaks P1 to P9 are data obtained by detecting a maximum point having a size of 1/3 or more of the maximum value among the maximum points of the plurality of spectral data S1 to S9.

When the blood flow of the living body 1 is normal, a single peak corresponding to the pulse wave frequency is often detected from the spectral data. Then, from the plurality of spectral data, peaks are often detected in the frequency section corresponding to the pulse wave frequency.

On the other hand, when the blood flow of the living body 1 is abnormal, a plurality of peaks are often detected from the spectral data. Then, peaks are often detected for a plurality of frequency sections from a plurality of spectral data.

FIG. 8 is a diagram showing a first example of the frequency of one or a plurality of peaks calculated by the blood flow disorder determining device 10 according to the present embodiment. In the figure, when nine spectral data are generated from nine pulse wave data measured when blood flow is normal, the frequencies of a plurality of peaks included in the nine spectral data are shown as the first histogram H1. There is.

In the first histogram H1, the section from 1.51 Hz to 1.59 Hz is the highest frequency section PW. Here, the maximum frequency is 6. For example, when the reference value is 6, the example shown in the figure is determined not to be an artifact because the maximum frequency of peaks is equal to or higher than the reference value. In this case, it is determined whether or not a blood flow disorder has occurred based on the nine spectral data.

FIG. 9 is a diagram showing a second example of the frequency of one or a plurality of peaks calculated by the blood flow disorder determining device 10 according to the present embodiment. In the figure, when nine spectral data are generated from nine pulse wave data measured when a blood flow disorder occurs, the frequency of a plurality of peaks included in the nine spectral data is shown in the second histogram H2. It is shown as.

In the second histogram H2, the frequency of peaks is scattered in the frequency section from 0.5 Hz to 2 Hz, and the section from 0.97 Hz to 1.05 Hz is the highest frequency section. Here, the maximum frequency is 3. For example, when the reference value is 6, the example shown in the figure is excluded because it is determined to be an artifact because the maximum frequency of peaks is less than the reference value. In this case, the nine spectral data are not used for determining blood flow disorders and are rejected.

FIG. 10 is a flowchart of the third process executed by the blood flow disorder determination system 100 according to the present embodiment. The third process is a process of calculating the degree of risk based on the color data.

First, the blood flow disorder determination system 100 measures color data at a predetermined sampling rate by the color sensor 22 (S30). After that, the blood flow disorder determination device 10 smoothes the color data (S31). For example, the blood flow disorder determining device 10 replaces y2 with y1 when | y3-y2 |> | y2-y1 | / 2 for the three points of data y1, y2, y3 measured continuously. Then, smoothing may be performed. Further, the blood flow disorder determination device 10 smoothes, for example, by replacing y3 with the average value of the data of 5 points for the data y1, y2, y3, y4, y5 of 5 points measured continuously. You may go.

The blood flow disorder determination device 10 converts the color data into the brightness data (S32). For example, the blood flow disorder determination device 10 may convert the color data of the RGB-IR color system into the color data of the XYZ color system and extract the Y value to convert the color data into the brightness data.

The blood flow disorder determination device 10 determines the parameters of a predetermined function that approximates the brightness data (S33). When the blood flow disorder determination device 10 expresses time as t and one or more parameters as A, A ₀ and τ, the blood flow disorder determination device 10 uses A × exp (−t / τ) + A ₀ as a predetermined function to determine the brightness. _{A, A 0} and τ may be determined to approximate the data. The fitting of a predetermined function may be performed by solving the least squares method, for example, by the Levenberg-Marquardt method.

The blood flow disorder determination device 10 calculates an index by the product of the coefficient of determination and the lognormal distribution of the parameters (S34). The blood flow disorder determining device 10 may calculate the coefficient of determination by Goodness of Fitting (GoF), which takes a value from 0 to 100. Further, the blood flow disorder determination device 10 calculates the lognormal distribution of the parameter A by lognormal (A) = 1 / (√ (2π) σA) exp (− (ln (A) −μ) ² / 2σ ² ). You can do it. Here, with σ = 1/4, μ may be selected so that ^{the mode exp (μ−σ 2) of the lognormal distribution is 1000.}

The blood flow disorder determining device 10 determines whether or not the absolute value of the index ind = GoF × lognormal (A) is equal to or greater than the third threshold value (S35). When the index is equal to or higher than the third threshold value (S35: YES), the blood flow disorder determining device 10 updates the risk level by adding the index to the previous value of the risk level (S36). On the other hand, when the index is not equal to or higher than the third threshold value (S35: NO), the risk level is updated by the larger value of the previous value of the risk level and the index (S37).

In this way, the first estimation unit 18 of the blood flow disorder determination device 10 calculates an index based on the value of one or a plurality of parameters and the coefficient of determination of the one or a plurality of parameters, and updates the degree of risk based on the index. By doing so, the risk of time-varying may be estimated. As a result, the index can be calculated based on the goodness of the fit of the approximation by the predetermined function and the magnitude of the time change, and the risk of time change can be estimated.

Further, when the absolute value of the index is equal to or higher than the third threshold value, the first estimation unit 18 updates the risk level by adding the index to the previous value of the risk level, and the absolute value of the index is less than the third threshold value. If, the risk may be updated by the larger of the previous value of the risk and the index. As a result, it is possible to calculate the degree of risk according to the magnitude of the change in both the case where the time series data (brightness data) decreases and the case where the time series data increases. With the above, the third process is completed.

FIG. 11 is a diagram showing a degree of risk estimated based on color data by the blood flow disorder determining device 10 according to the present embodiment. In the figure, the horizontal axis shows the number of days elapsed and the vertical axis shows the degree of risk. The figure shows the result of calculating the degree of risk based on the color data measured by the 4-channel color sensor 22.

The blood flow disorder determination device 10 estimates the degree of risk based on the four color data measured by the four-channel color sensor 22. From FIG. 11, it can be read that the first risk level C1 shown by the solid line and the second risk level C2 shown by the alternate long and short dash line are rapidly increasing on the night of the third day (Day 3). The first risk level C1 has risen to near the maximum value of 1.0, and has been maintained at about 1.0 thereafter. The second risk level C2 has risen to about 0.3 and has been maintained at about 0.3 thereafter.

According to the data shown in FIG. 11, with respect to the color data of at least one channel, the degree of risk is constant near the maximum value, and it can be determined that there is a high possibility that the blood flow disorder occurs in the living body 1.

FIG. 12 is a flowchart of the fourth process executed by the blood flow disorder determination system 100 according to the present embodiment. The fourth process is a process of calculating the degree of risk based on the temperature data.

First, the blood flow disorder determination system 100 measures color data at a predetermined sampling rate by the temperature sensor 23 (S40). After that, the blood flow disorder determination device 10 smoothes the temperature data (S41). For example, the blood flow disorder determining device 10 replaces y2 with y1 when | y3-y2 |> | y2-y1 | / 2 for the three points of data y1, y2, y3 measured continuously. Then, smoothing may be performed. Further, the blood flow disorder determination device 10 smoothes, for example, by replacing y3 with the average value of the data of 5 points for the data y1, y2, y3, y4, y5 of 5 points measured continuously. You may go.

The blood flow disorder determination device 10 determines a parameter of a predetermined function that approximates the temperature data (S42). When the blood flow disorder determination device 10 expresses time as t and one or more parameters as A, A ₀ and τ, the blood flow disorder determination device 10 uses A × exp (−t / τ) + A ₀ as a predetermined function and uses temperature. _{A, A 0} and τ may be determined to approximate the data. The fitting of a predetermined function may be performed by solving the least squares method, for example, by the Levenberg-Marquardt method.

The blood flow disorder determination device 10 calculates an index by the product of the coefficient of determination and the lognormal distribution of the parameters (S43). The blood flow disorder determining device 10 may calculate the coefficient of determination by Goodness of Fitting (GoF), which takes a value from 0 to 100. Further, the blood flow disorder determination device 10 calculates the lognormal distribution of the parameter A by lognormal (A) = 1 / (√ (2π) σA) exp (− (ln (A) −μ) ² / 2σ ² ). You can do it. Here, with σ = 1/4, μ may be selected so that ^{the mode exp (μ−σ 2) of the lognormal distribution is 2.}

The blood flow disorder determination device 10 updates the risk level by adding the index ind = GoF × lognormal (A) to the previous value of the risk level (S44). With the above, the fourth process is completed.

FIG. 13 is a diagram showing a degree of risk estimated based on temperature data by the blood flow disorder determining device 10 according to the present embodiment. In the figure, the horizontal axis shows the number of days elapsed and the vertical axis shows the degree of risk. The figure shows the result of calculating the degree of risk based on the temperature data measured by the 4-channel temperature sensor 23.

The blood flow disorder determination device 10 estimates the degree of risk based on the four temperature data measured by the four-channel temperature sensor 23. From FIG. 13, it can be read that the first risk level T1 shown by the solid line increased to nearly 1.0 around noon on the 6th day (Day6) and then returned to 0. In addition, it can be read that the second danger level T2 indicated by the alternate long and short dash line increased to about 0.4 in the morning of the 4th day (Day 4) and then returned to 0. It can also be seen that at midnight on the 7th day (Day 7), the third risk T3 indicated by the alternate long and short dash line increased to about 0.4 and then returned to 0. Further, it can be read that the fourth risk T4 shown by the broken line increased to about 0.1 at midnight on the first day (Day 1) and then returned to 0.

According to the data shown in FIG. 13, for the color data of 4 channels, the risk level temporarily increased to near the maximum value, but then the risk level decreased to 0, and the living body 1 suffered from blood flow disorder. It can be judged that the probability of occurrence is low.

FIG. 14 is a flowchart of the fifth process executed by the blood flow disorder determination system 100 according to the present embodiment. The fifth process is a process for comprehensively determining whether or not the living body 1 has a blood flow disorder.

First, the blood flow disorder determination system 100 executes the first process shown in FIG. 5 and calculates the risk level of the pulse wave (S50). In addition, the blood flow disorder determination system 100 executes the third process shown in FIG. 10 to calculate the degree of color risk (S51). Further, the blood flow disorder determination system 100 executes the fourth process shown in FIG. 12 and calculates the degree of risk of temperature (S51). The execution order of these processes is arbitrary.

The blood flow disorder determination system 100 outputs that the artifact is detected when the pulse wave data is excluded as an artifact (S53: YES) (S54). The output may be performed, for example, by displaying a message on the display unit 10f of the blood flow disorder determination device 10. Note that the output that an artifact has been detected may be omitted.

On the other hand, when the pulse wave data is not excluded as an artifact (S53: NO), the blood flow disorder determination system 100 determines that any of the pulse wave risk, the color risk, and the temperature risk is equal to or higher than the fourth threshold value. (S55). When none of the risks is equal to or higher than the fourth threshold value (S55: NO), the blood flow disorder determination system 100 outputs that the risk of blood flow disorder is low (S56). On the other hand, when any of the risk levels is equal to or higher than the fourth threshold value (S55: YES), it is output that a blood flow disorder has occurred (S57). With the above, the fifth process is completed.

The second determination unit 16 of the blood flow disorder determination device 10 uses a plurality of pulse wave data to cause a blood flow disorder in the living body 1 when it is determined that one or a plurality of peaks in the spectrum data are not artifacts. Based on the result of determining whether or not there is a blood flow disorder in the living body 1 using at least one of the color data and the temperature data, the living body 1 has a blood flow disorder. It may be comprehensively determined whether or not it has occurred. Thereby, it is possible to reduce the artifacts based on the pulse wave data of the living body 1 and comprehensively determine whether or not the blood flow disorder occurs based on the pulse wave, the color and the temperature.

In addition, the second determination unit 16 of the blood flow disorder determination device 10 causes a blood flow disorder in the living body 1 when at least one of the pulse wave risk, the color risk, and the temperature risk is equal to or higher than the fourth threshold value. May be comprehensively determined to have occurred. In this way, it is possible to reduce the oversight of blood flow disorders by comprehensively determining that blood flow disorders occur when there is a high risk of blood flow disorders with respect to at least one of the pulse wave, color, and temperature of the living body 1. Can be done.

The second determination unit 16 of the blood flow disorder determination device 10 determines the blood flow disorder of the living body 1 based on the risk calculated using the color data and the risk calculated using the temperature data. The type may be determined. When congestion occurs as a blood flow disorder, the risk calculated using color data is expected to increase, but since the temperature of living body 1 does not decrease in congestion, it was calculated using temperature data. The risk usually does not increase. On the other hand, when ischemia occurs as a blood flow disorder, the risk calculated using the color data increases, and the temperature of the living body 1 decreases, so that the risk calculated using the temperature data also increases. It is expected. In this way, it is possible to distinguish whether blood flow disorder such as congestion or ischemia is occurring by the combination of the color risk and the temperature risk.

FIG. 15 is a diagram showing a first example of a risk level and an artifact detection rate comprehensively determined by the blood flow disorder determination device 10 according to the present embodiment. In this example, the comprehensively determined risk level R1 and the artifact detection rate A1 are shown. The horizontal axis of the comprehensively determined risk level R1 and the artifact detection rate A1 is time, and the vertical axis is a value of 0 to 1. In the figure, the artifact detection rate A1 for the 4-channel pulse wave data is shown by the solid line, the one-dot chain line, the two-dot chain line, and the broken line.

In this example, the comprehensively determined risk level R1 is 0 for all times except the start of measurement. In addition, the artifact detection rate A1 frequently increases for 4-channel pulse wave data. As described above, according to the blood flow disorder determination device 10 according to the present embodiment, it is possible to reduce the artifacts included in the pulse wave data and determine the blood flow disorder.

FIG. 16 is a diagram showing a second example of the risk level and the detection rate of the artifacts comprehensively determined by the blood flow disorder determination device 10 according to the present embodiment. In this example, the comprehensively determined risk level R2 and the artifact detection rate A2 are shown. The horizontal axis of the comprehensively determined risk level R2 and the artifact detection rate A2 is time, and the vertical axis is a value of 0 to 1. In the figure, the solid line, the one-dot chain line, the two-dot chain line, and the broken line show the four-channel comprehensively determined risk level R2 and the artifact detection rate A2 for the four-channel pulse wave data.

In this example, the comprehensively determined risk level R2 is a value close to 1 over all the time. Therefore, in this example, it is highly probable that the living body 1 has a blood flow disorder. In addition, the artifact detection rate A2 is a high value of about 0.5 to 0.7 over all the time. As described above, according to the blood flow disorder determining device 10 according to the present embodiment, the artifacts included in the pulse wave data are reduced, and whether or not the blood flow disorder is caused by the pulse wave, the color, and the temperature is comprehensively determined. Can be determined.

FIG. 17 is a flowchart of the sixth process executed by the blood flow disorder determination system according to the present embodiment. The sixth process is a process of determining whether or not a blood flow disorder has occurred in the living body 1 based on the pulse wave data.

The calculation unit 14 of the blood flow disorder determination device 10 has a probability distribution of pulse wave data measured in a reference period among a plurality of different periods and a probability distribution of pulse wave data measured in a target period among a plurality of different periods. Calculate a test statistic to test for equality. Here, the reference period may be from the time when the measurement of the pulse wave data is started until the predetermined period elapses, and the target period may be from the present time to the time when the predetermined period is traced back. From the data obtained in the previous studies, it is known that the probability distribution of pulse wave data can be approximated by the gamma distribution. The calculation unit 14 estimates the gamma distribution of the pulse wave data measured in the reference period based on the average and variance of the pulse wave data measured in the reference period, and is based on the average and variance of the pulse wave data measured in the target period. Then, the gamma distribution of the pulse wave data measured during the target period may be estimated. Further, the calculation unit 14 calculates the D value as a test statistic for testing whether or not the gamma distribution of the pulse wave data measured in the reference period is equal to the gamma distribution of the pulse wave data measured in the target period. good.

The second determination unit 16 of the blood flow disorder determination device 10 determines whether or not the blood flow disorder has occurred in the living body 1 based on the test statistic. The second determination unit 16 determines that the living body 1 has a blood flow disorder when the D value is equal to or higher than the fifth threshold value, and determines that the living body 1 has a blood flow disorder when the D value is less than the fifth threshold value. May be determined not to occur.

First, the blood flow disorder determination system 100 measures the pulse wave data at a predetermined sampling rate by the pulse wave sensor 21 (S60). After that, the blood flow disorder determination device 10 determines a reference period, calculates the average and variance of the reference section, and estimates the probability distribution of the pulse wave data measured during the reference period (S61). In addition, the blood flow disorder determination device 10 calculates the average and variance of the target section, and estimates the probability distribution of the pulse wave data measured during the target period (S62). Then, the blood flow disorder determination device 10 calculates a D value as a test statistic for testing whether or not both probability distributions are equal (S63).

When the D value is equal to or greater than the fifth threshold value (S64: YES), the blood flow disorder determining device 10 determines that the blood flow disorder has occurred in the living body 1 (S65). On the other hand, when the D value is less than the fifth threshold value (S64: NO), the blood flow disorder determining device 10 determines that the blood flow disorder has not occurred in the living body 1 (S66).

FIG. 18 is a diagram showing a D value calculated by the blood flow disorder determination device 10 according to the present embodiment and a blood flow disorder detection timing. In the figure, the horizontal axis shows time, the upper vertical axis shows the magnitude of pulse wave data (Pulse Power) dimensionlessly, and the lower vertical axis shows the magnitude of D value dimensionlessly. ..

In the graph PP of pulse wave data, the pulse wave data of 4 channels is shown by a solid line, a one-dot chain line, a two-dot chain line and a broken line. The blood flow disorder determination device 10 estimates the probability distribution of the pulse wave data of the target period including the latest pulse wave data and the probability distribution of the pulse wave data of the reference period including the pulse wave data at the start of measurement, and they are estimated. Calculate the D value to test whether the probability distributions of are equal. The graph D of the D value significantly exceeds the fifth threshold value Th at a certain point in time, and the blood flow disorder determining device 10 determines that the blood flow disorder has occurred in the living body 1 at the first time point d1.

On the other hand, the doctor regularly visits the patient to determine whether or not blood flow disorder has occurred. In the case of this example, the doctor determined that the blood flow disorder occurred in the living body 1 at the second time point d2.

As described above, although the judgment by the doctor is accurate, it cannot always be made, and a certain amount of time may elapse from the occurrence of the blood flow disorder to the discovery. In this regard, according to the blood flow disorder determining device 10 according to the present embodiment, continuous monitoring is possible, and the occurrence of blood flow disorder can be detected at an early stage. According to the blood flow disorder determination device 10 according to the present embodiment, by paying attention to the difference between the probability distribution of the pulse wave data in the reference period and the probability distribution of the pulse wave data in the target period, the characteristics of the pulse wave data are relative to each other. It is possible to determine whether or not a blood flow disorder has occurred.

When determining the occurrence of blood flow disorder based on the change in the probability distribution of the pulse wave data, the sensor 20 may be attached to a place where blood flow disorder is a concern, but a place where blood flow disorder is a concern. It may be attached so as to straddle the normal part. When the sensor 20 is attached so as to straddle a place where blood flow disorder is a concern and a normal place, a pulse wave sensor 21 of at least one channel is attached to a place where blood flow disorder is a concern, and at least one channel of the other is attached. The pulse wave sensor 21 is attached to a normal place. In this case, the blood flow disorder determination device 10 uses the pulse wave data of the channel corresponding to the normal location as a reference, the probability distribution of the pulse wave data of the channel corresponding to the normal location, and the location where the blood flow disorder is a concern. A test statistic may be calculated to test whether or not the probability distribution of the pulse wave data of the channel corresponding to is equal. Further, a plurality of sensors 20 may be prepared, the first sensor including the plurality of channels may be attached to a normal place, and another sensor including the plurality of channels may be attached to a place where blood flow disorder is a concern. In that case, the blood flow disorder determination device 10 has a probability distribution of the pulse wave data of the first sensor attached to a normal place and a probability distribution of the pulse wave data of the second sensor attached to a place where there is a concern about blood flow disorder. You may calculate a test statistic that tests whether and are equal.

FIG. 19 is a flowchart of the seventh process executed by the blood flow disorder determination system 100 according to the present embodiment. The sixth process is a process of removing noise based on infrared data and calculating the degree of risk based on color data. The color data measured by the color sensor 22 of the blood flow disorder determination system 100 includes infrared data, and the determination unit 17 is included in a predetermined function that approximates the noise-removed time series data based on the infrared data. Determine the value of one or more parameters. Here, the noise removal based on the infrared data may be performed by, for example, when the magnitude of the infrared data is equal to or larger than the sixth threshold value, the color data at that time is removed as noise.

First, the blood flow disorder determination system 100 measures color data at a predetermined sampling rate by the color sensor 22 (S70). The blood flow disorder determining device 10 removes noise related to the color data by removing the color data in the section where the infrared data is equal to or higher than the sixth threshold value (S71). After that, the blood flow disorder determination device 10 smoothes the color data (S72). The smoothing may be performed in the same manner as in the third process.

The blood flow disorder determination device 10 converts the color data into the brightness data (S73). The conversion from the color data to the brightness data may be performed in the same manner as in the third process.

The blood flow disorder determination device 10 determines the parameters of a predetermined function that approximates the brightness data (S74). The parameters of the predetermined function that approximates the brightness data may be determined in the same manner as in the third process.

The blood flow disorder determination device 10 calculates an index by the product of the coefficient of determination and the lognormal distribution of the parameters (S75). The index may be calculated in the same manner as in the third process.

The blood flow disorder determination device 10 determines whether or not the absolute value of the index is equal to or greater than the third threshold value (S76). When the index is equal to or higher than the third threshold value (S76: YES), the blood flow disorder determining device 10 updates the risk level by adding the index to the previous value of the risk level (S77). On the other hand, when the index is not equal to or higher than the third threshold value (S76: NO), the risk level is updated by the larger value of the previous value of the risk level and the index (S78).

By removing noise from color data based on infrared data, the risk of blood flow disorder can be calculated more accurately.

FIG. 20 is a diagram showing color data with noise removed and color data without noise removal measured by the blood flow disorder determination system 100 according to the present embodiment. In the figure, the horizontal axis shows time, the upper vertical axis shows the brightness of color data with noise removal in dimensionless, and the lower vertical axis shows the brightness of color data without noise removal in dimensionless. Shown. In both the graph Y1 of the color data with noise removal and the graph Y2 of the color data without noise removal, the color data of 4 channels is shown by a solid line, a one-dot chain line, a two-dot chain line and a broken line.

The graph Y1 of the color data from which noise has been removed is data in which discontinuous portions are included and the portions are removed as noise. On the other hand, the graph Y2 of the color data in which noise is not removed is continuous.

FIG. 21 is a diagram showing a degree of risk estimated based on color data by the blood flow disorder determining device 10 according to the present embodiment. In the figure, the horizontal axis shows the number of days elapsed and the vertical axis shows the degree of risk. The figure shows the result of calculating the degree of risk based on the color data obtained by removing noise based on the infrared data measured by the 4-channel color sensor 22.

The blood flow disorder determination device 10 estimates the degree of risk based on the four color data from which noise has been removed. From FIG. 21, it can be read that the first risk level C1 shown by the solid line and the second risk level C2 shown by the alternate long and short dash line are rapidly increasing on the night of July 30, 2018. The first risk level C1 has risen to near the maximum value of 1.0, and has been maintained at about 0.6 thereafter. The second risk level C2 has risen to about 0.3 and has been maintained at about 0.3 thereafter. In addition, the 3rd risk C3 indicated by the alternate long and short dash line and the 4th risk C4 indicated by the broken line increased to about 0.1 on the morning of July 31, 2018, and then maintained at about 0.1. ing.

According to the data shown in FIG. 21, with respect to the color data of at least one channel, the degree of risk has risen to near the maximum value, and it can be determined that there is a high possibility that the blood flow disorder has occurred in the living body 1.

The embodiments described above are for facilitating the understanding of the present invention, and are not for limiting and interpreting the present invention. Each element included in the embodiment and its arrangement, material, condition, shape, size, and the like are not limited to those exemplified, and can be changed as appropriate. In addition, the configurations shown in different embodiments can be partially replaced or combined.

The present invention is a blood flow disorder determining device and blood flow that can calculate the risk of blood flow disorder based on at least one of the color data and the temperature data of a living body and determine the blood flow disorder based on the risk. Provided are a disorder determination method, a blood flow disorder determination program, and a blood flow disorder determination system.

[Appendix 1]
An acquisition unit that acquires time-series data including at least one of color data that measures the time change of the color of the living body and temperature data that measures the time change of the temperature of the living body.
A determination unit that determines the values of one or more parameters included in a predetermined function that approximates the time series data.
A first estimation unit that estimates the degree of risk based on the values of the one or more parameters, and
A second determination unit that determines whether or not a blood flow disorder has occurred in the living body based on the degree of risk.
A blood flow disorder determination device comprising.

[Appendix 2]
The first estimation unit calculates an index based on the value of the one or a plurality of parameters and the coefficient of determination of the one or a plurality of parameters, and updates the degree of risk based on the index to change with time. Estimate the degree of risk,
The blood flow disorder determination device according to Appendix 1.

[Appendix 3]
When time is expressed as t and the one or more parameters are expressed as A, A ₀ and τ,
The predetermined function is A × exp (−t / τ) + A ₀ .
The blood flow disorder determination device according to Appendix 2.

[Appendix 4]
The first estimation unit
When the absolute value of the index is equal to or higher than the third threshold value, the risk level is updated by adding the index value to the previous value of the risk level.
When the absolute value of the index is less than the third threshold value, the risk level is updated by the larger value of the previous value of the risk level and the index.
The blood flow disorder determination device according to Appendix 2 or 3.

[Appendix 5]
The acquisition unit acquires a plurality of pulse wave data obtained by measuring the time change of the pulse wave of the living body in a plurality of different periods.
A generator that generates a plurality of spectral data by Fourier transforming each of the plurality of pulse wave data,
A detection unit that detects one or more peaks included in the plurality of spectral data, and a detection unit.
A calculation unit that calculates the frequency at which the one or more peaks are detected for each predetermined frequency section, and
A first determination unit for determining whether or not the one or more peaks are artifacts based on the frequency is further provided.
When it is determined that the one or more peaks are not artifacts, the second determination unit determines whether or not the living body has a blood flow disorder based on the plurality of spectral data.
The blood flow disorder determining device according to any one of Appendix 1 to 4.

[Appendix 6]
The first determination unit determines whether or not the one or more peaks are artifacts when the sum of the powers of the plurality of spectral data is equal to or greater than the first threshold value.
The blood flow disorder determination device according to Appendix 5.

[Appendix 7]
The second determination unit identifies the most frequent frequency section of the one or a plurality of peaks determined not to be the artifact, and the average value of the power of the frequency section of the plurality of spectral data is the second threshold value. When the following, it is determined that the living body has a blood flow disorder.
The blood flow disorder determination device according to Appendix 6.

[Appendix 8]
The second determination unit applies to the living body when the sum of the powers of the plurality of spectral data is less than the first threshold value and the average value of the sum of the powers of the plurality of spectral data is equal to or less than the second threshold value. Judge that blood flow disorder has occurred,
The blood flow disorder determination device according to Appendix 6 or 7.

[Appendix 9]
The time-varying pulse wave risk is estimated based on the rate at which it is determined that blood flow disorder has occurred when the first determination unit and the second determination unit make a plurality of determinations in a predetermined period. Further equipped with a second estimation unit,
The blood flow disorder determining device according to any one of Appendix 5 to 8.

[Appendix 10]
The second determination unit uses the plurality of pulse wave data to determine whether or not a blood flow disorder has occurred in the living body when it is determined that the one or more peaks are not artifacts. Based on the result of determining whether or not the living body has a blood flow disorder using at least one of the color data and the temperature data, whether or not the living body has a blood flow disorder is determined. Comprehensive judgment,
The blood flow disorder determination device according to Appendix 9.

[Appendix 11]
The second determination unit comprehensively determines that a blood flow disorder has occurred in the living body when at least one of the pulse wave risk and the risk is equal to or higher than the fourth threshold value.
The blood flow disorder determination device according to Appendix 10.

[Appendix 12]
Acquiring time-series data including at least one of color data measuring the time change of the color of the living body and temperature data measuring the time change of the temperature of the living body, and
Determining the values of one or more parameters contained in a given function that approximates the time series data.
Estimating the degree of risk based on the values of one or more of the above parameters
Determining whether or not a blood flow disorder has occurred in the living body based on the degree of risk,
Blood flow disorder determination method including.

[Appendix 13]
The processor provided in the blood flow disorder determination device,
An acquisition unit that acquires time-series data including at least one of color data that measures the time change of the color of the living body and temperature data that measures the time change of the temperature of the living body.
A determination unit that determines the value of one or more parameters included in a predetermined function that approximates the time series data.
A first estimation unit that estimates the degree of risk based on the values of the one or a plurality of parameters, and a second determination unit that determines whether or not a blood flow disorder has occurred in the living body based on the degree of risk. ,
A blood flow disorder judgment program that functions as a function.

[Appendix 14]
Measure at least one of the color data that measures the time change of the color of the living body and the temperature data that measures the time change of the temperature of the living body, and output the time series data including at least one of the color data and the temperature data. It is a blood flow disorder determination system including a sensor for determining whether or not a blood flow disorder has occurred in the living body using the time series data.
The blood flow disorder determination device is
A determination unit that determines the values of one or more parameters included in a predetermined function that approximates the time series data.
A first estimation unit that estimates the degree of risk based on the values of the one or more parameters, and
It has a second determination unit for determining whether or not a blood flow disorder has occurred in the living body based on the degree of risk.
Blood flow disorder judgment system.

1 ... Living body, 10 ... Blood flow disorder determination device, 10a ... CPU, 10b ... RAM, 10c ... ROM, 10d ... Communication unit, 10e ... Input unit, 10f ... Display unit, 11 ... Acquisition unit, 12 ... Generation unit, 13 ... detection unit, 14 ... calculation unit, 15 ... first judgment unit, 16 ... second judgment unit, 17 ... determination unit, 18 ... first estimation unit, 19 ... second estimation unit, 20 ... sensor, 21 ... pulse wave Sensor, 22 ... color sensor, 23 ... temperature sensor, 25 ... flexible substrate, 30 ... transmitter, 100 ... blood flow disorder determination system

Claims (16)

An acquisition unit that acquires multiple pulse wave data that measures the time change of the pulse wave of the living body in a plurality of different periods, and
A generator that generates a plurality of spectral data by Fourier transforming each of the plurality of pulse wave data,
A detection unit that detects one or more peaks included in the plurality of spectral data, and a detection unit.
A calculation unit that calculates the frequency at which the one or more peaks are detected for each predetermined frequency section, and
A first determination unit that determines whether or not the one or more peaks are artifacts based on the frequency.
When it is determined that the one or a plurality of peaks are not artifacts, a second determination unit for determining whether or not a blood flow disorder has occurred in the living body based on the plurality of spectral data, and a second determination unit.
A blood flow disorder determination device comprising. The first determination unit determines whether or not the one or more peaks are artifacts when the sum of the powers of the plurality of spectral data is equal to or greater than the first threshold value.
The blood flow disorder determining device according to claim 1. The second determination unit identifies the most frequent frequency section of the one or a plurality of peaks determined not to be the artifact, and the average value of the power of the frequency section of the plurality of spectral data is the second threshold value. When the following, it is determined that the living body has a blood flow disorder.
The blood flow disorder determining device according to claim 2. The second determination unit applies to the living body when the sum of the powers of the plurality of spectral data is less than the first threshold value and the average value of the sum of the powers of the plurality of spectral data is equal to or less than the second threshold value. Judge that blood flow disorder has occurred,
The blood flow disorder determining device according to claim 2 or 3. The acquisition unit acquires time-series data including at least one of color data for measuring the time change of the color of the living body and temperature data for measuring the time change of the temperature of the living body.
A determination unit that determines the values of one or more parameters included in a predetermined function that approximates the time series data.
A first estimation unit for estimating the degree of risk based on the values of the one or a plurality of parameters is further provided.
The second determination unit determines whether or not a blood flow disorder has occurred in the living body based on the degree of risk.
The blood flow disorder determining device according to any one of claims 1 to 4. The first estimation unit calculates an index based on the value of the one or a plurality of parameters and the coefficient of determination of the one or a plurality of parameters, and updates the degree of risk based on the index to change with time. Estimate the degree of risk,
The blood flow disorder determining device according to claim 5. When time is expressed as t and the one or more parameters are expressed as A, A ₀ and τ,
The predetermined function is A × exp (−t / τ) + A ₀ .
The blood flow disorder determining device according to claim 6. The first estimation unit
When the absolute value of the index is equal to or higher than the third threshold value, the risk level is updated by adding the index value to the previous value of the risk level.
When the absolute value of the index is less than the third threshold value, the risk level is updated by the larger value of the previous value of the risk level and the index.
The blood flow disorder determination device according to claim 6 or 7. The time-varying pulse wave risk is estimated based on the rate at which it is determined that blood flow disorder has occurred when the first determination unit and the second determination unit make a plurality of determinations in a predetermined period. Further equipped with a second estimation unit,
The blood flow disorder determining device according to any one of claims 5 to 8. The second determination unit uses the plurality of pulse wave data to determine whether or not a blood flow disorder has occurred in the living body when it is determined that the one or more peaks are not artifacts. Based on the result of determining whether or not the living body has a blood flow disorder using at least one of the color data and the temperature data, whether or not the living body has a blood flow disorder is determined. Comprehensive judgment,
The blood flow disorder determining device according to claim 9. The second determination unit comprehensively determines that a blood flow disorder has occurred in the living body when at least one of the pulse wave risk and the risk is equal to or higher than the fourth threshold value.
The blood flow disorder determination device according to claim 10. The color data includes infrared data.
The determination unit determines the values of the one or more parameters included in the predetermined function that approximates the time-series data from which noise has been removed based on the infrared data.
The blood flow disorder determining device according to any one of claims 5 to 11. The calculation unit determines whether or not the probability distribution of the pulse wave data measured in the reference period among the plurality of different periods is equal to the probability distribution of the pulse wave data measured in the target period among the plurality of different periods. Calculate the test statistic to be tested,
The second determination unit determines whether or not a blood flow disorder has occurred in the living body based on the test statistic.
The blood flow disorder determining device according to any one of claims 1 to 12. Acquiring multiple pulse wave data by measuring the time change of the pulse wave of the living body in multiple different periods, and
To generate a plurality of spectral data by Fourier transforming each of the plurality of pulse wave data,
To detect one or more peaks included in the plurality of spectral data,
To calculate the frequency at which the one or more peaks are detected for each predetermined frequency section, and
Determining whether the one or more peaks are artifacts based on the frequency.
When it is determined that the one or more peaks are not artifacts, it is determined whether or not the living body has a blood flow disorder based on the plurality of spectral data.
Blood flow disorder determination method including. The processor provided in the blood flow disorder determination device,
Acquisition unit that acquires multiple pulse wave data that measures the time change of the pulse wave of the living body in a plurality of different periods.
A generator that generates a plurality of spectral data by Fourier transforming each of the plurality of pulse wave data.
A detection unit that detects one or more peaks included in the plurality of spectral data.
A calculation unit that calculates the frequency at which the one or more peaks are detected for each predetermined frequency section.
Based on the frequency, the first determination unit for determining whether or not the one or more peaks are artifacts, and when the one or more peaks are determined not to be artifacts, the plurality of spectral data Based on this, a second determination unit that determines whether or not a blood flow disorder has occurred in the living body,
A blood flow disorder judgment program that functions as a function. Whether or not a blood flow disorder occurs in the living body using a pulse wave sensor that measures the time change of the pulse wave of the living body in a plurality of different periods and outputs a plurality of pulse wave data and the plurality of pulse wave data. It is a blood flow disorder determination system provided with a blood flow disorder determination device for determining whether or not the data is present.
The blood flow disorder determination device is
A generator that generates a plurality of spectral data by Fourier transforming each of the plurality of pulse wave data,
A detection unit that detects one or more peaks included in the plurality of spectral data, and a detection unit.
A calculation unit that calculates the frequency at which the one or more peaks are detected for each predetermined frequency section, and
A first determination unit that determines whether or not the one or more peaks are artifacts based on the frequency.
It has a second determination unit for determining whether or not a blood flow disorder has occurred in the living body based on the plurality of spectral data when it is determined that the one or a plurality of peaks are not artifacts.
Blood flow disorder judgment system.

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