WO2020111203A1 - Blood flow obstruction determination device, blood flow obstruction determination method, blood flow obstruction determination program, and blood flow obstruction determination system - Google Patents

Blood flow obstruction determination device, blood flow obstruction determination method, blood flow obstruction determination program, and blood flow obstruction determination system Download PDF

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Publication number
WO2020111203A1
WO2020111203A1 PCT/JP2019/046671 JP2019046671W WO2020111203A1 WO 2020111203 A1 WO2020111203 A1 WO 2020111203A1 JP 2019046671 W JP2019046671 W JP 2019046671W WO 2020111203 A1 WO2020111203 A1 WO 2020111203A1
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Prior art keywords
blood flow
flow disorder
data
pulse wave
peaks
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PCT/JP2019/046671
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French (fr)
Japanese (ja)
Inventor
正樹 関野
剣 顧
晃一 喜田
容子 富岡
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国立大学法人東京大学
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Priority to JP2020557839A priority Critical patent/JPWO2020111203A1/en
Publication of WO2020111203A1 publication Critical patent/WO2020111203A1/en

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/026—Measuring blood flow

Definitions

  • 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.
  • a refill method that determines by the time it takes for the color of the patient's living tissue to change color after being pressed and discolored, a method of determining by the color of the living tissue, and a bleeding condition when a needle is pierced into the living tissue.
  • the possibility of blood flow disorder is determined by the method.
  • Patent Document 1 discloses a sensor sheet in which a plurality of types of sensing means for measuring blood flow information of different living tissues are arranged on a flexible base material. A blood flow disorder detection device having the above is described.
  • a blood flow disorder can be detected based on the pulse wave of the patient, the color of the skin, and the temperature of the skin measured by the wearable sensor.
  • the patient is not always stationary, and artifacts may be mixed in the pulse wave data due to the body movement of the patient. If the pulse wave data includes an artifact, there is a possibility that the blood flow disorder may be erroneously determined or the blood flow disorder may be missed.
  • 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 reduce blood flow disorders by reducing artifacts included in pulse wave data. To do.
  • the blood flow disorder determination device 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 each of the plurality of pulse wave data.
  • Generating unit for generating a plurality of spectrum data, a detecting unit for detecting one or a plurality of peaks included in the plurality of spectrum data, and a frequency of detecting one or a plurality of peaks for each predetermined frequency section And a first determination unit that determines whether or not one or more peaks are artifacts based on the frequency, and a plurality of spectral data when it is determined that the one or more peaks are not artifacts And a second determination unit that determines whether or not a blood flow disorder has occurred in the living body.
  • the pulse wave data is determined by determining whether or not the one or more peaks are artifacts based on the frequency of the one or more peaks included in the spectrum data instead of the power of the spectrum data.
  • Blood flow disorders can be determined by reducing the artifacts contained in.
  • the first determination unit may determine whether or not one or more peaks are artifacts when the sum of the powers of the plurality of spectrum data is equal to or greater than the first threshold.
  • the blood flow disorder is determined by reducing the artifacts included in the pulse wave data. be able to.
  • the second determination unit identifies the frequency section having the highest frequency among the one or the plurality of peaks determined not to be an artifact, and the average value of the power of the frequency sections of the plurality of spectrum data is equal to or less than the second threshold value. If it is, it may be determined that a blood flow disorder has occurred in the living body.
  • the power corresponding to the frequency of the pulse wave can be more accurately captured, and the occurrence of blood flow disorder can be more accurately determined.
  • the second determination unit determines whether the average value of the sum of the powers of the plurality of spectrum data is less than or equal to the second threshold value. It may be determined that a blood flow disorder has occurred.
  • the occurrence of blood flow abnormality is determined by determining whether or not the average value of the sum of the powers of the plurality of spectrum data is sufficiently high, thereby determining the blood flow abnormality. Can be determined more accurately.
  • 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 obtained by measuring the time change of the temperature of the living body, and approximates the time-series data.
  • the second determination unit further includes a determination unit that determines the value of one or more parameters included in the predetermined function, and a first estimation unit that estimates the 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.
  • the first estimation unit 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 risk based on the index, thereby changing the risk over time.
  • the degree may be estimated.
  • the predetermined function may be A ⁇ exp( ⁇ t/ ⁇ )+A 0 .
  • the first estimation unit updates the risk by adding the index to the previous value of the risk, and the absolute value of the index is the third threshold. If it is less than the risk level, the risk level may be updated with the larger value of the previous risk level and the index.
  • the time-varying pulse wave risk is determined based on the rate at which the blood flow disorder is determined to have occurred when the determinations by the first determination unit and the second determination unit are performed multiple times in the predetermined period.
  • a second estimating unit for estimating may be further provided.
  • the second determination unit when one or a plurality of peaks is determined not to be an artifact, a result of determining whether a blood flow disorder has occurred in the living body by using a plurality of pulse wave data, Based on the result of determining whether the blood flow disorder is occurring in the living body using at least one of the color data and the temperature data, a comprehensive determination is made as to whether the blood flow disorder is occurring in the living body. Good.
  • the second determination unit may comprehensively determine that the blood flow is impaired 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.
  • the blood flow disorder when the blood flow disorder is high in at least one of the pulse wave, the color, and the temperature of the living body, it is comprehensively determined that the blood flow disorder is occurring, so that the overlooking of the blood flow disorder is reduced. be able to.
  • the color data includes infrared data
  • the determining unit determines a value of one or more parameters included in a predetermined function that approximates the noise-removed time series data based on the infrared data. May be.
  • the risk of blood flow disorder can be calculated more accurately by performing noise removal of color data based on infrared data.
  • the calculation unit may determine whether or not a blood flow disorder has occurred in the living body based on the test statistic by calculating a test statistic for testing.
  • the characteristics of the pulse wave data are relatively evaluated to determine the blood flow disorder. Can be determined.
  • a blood flow disorder determination method is to obtain 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 perform a Fourier transform on each of the plurality of pulse wave data.
  • To generate a plurality of spectrum data to detect one or a plurality of peaks included in the plurality of spectrum data, and to calculate a frequency at which one or a plurality of peaks are detected for each predetermined frequency section. And, based on the frequency, to determine whether or not one or more peaks are artifacts, and when it is determined that the one or more peaks are not artifacts, based on multiple spectral data, Determining whether a blood flow disorder has occurred.
  • the pulse wave data is determined by determining whether or not the one or more peaks are artifacts based on the frequency of the one or more peaks included in the spectrum data instead of the power of the spectrum data.
  • Blood flow disorders can be determined by reducing the artifacts contained in.
  • a blood flow disorder determination program uses a processor provided in a blood flow disorder determination device 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.
  • An acquisition unit a generation unit that performs Fourier transform on each of a plurality of pulse wave data to generate a plurality of spectrum data, a detection unit that detects one or a plurality of peaks included in the plurality of spectrum data, and one or a predetermined frequency section.
  • a calculation unit that calculates the frequency at which a plurality of peaks are detected, a first determination unit that determines whether or not one or more peaks are artifacts based on the frequency, and a determination unit that determines that one or more peaks are not artifacts
  • the second determination unit that determines whether or not a blood flow disorder has occurred in the living body is caused to function based on the plurality of spectrum data.
  • the pulse wave data is determined by determining whether or not the one or more peaks are artifacts based on the frequency of the one or more peaks included in the spectrum data instead of the power of the spectrum data.
  • Blood flow disorders can be determined by reducing the artifacts contained in.
  • a blood flow disorder determination system 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.
  • a blood flow disorder determination system comprising: a blood flow disorder determination device that determines whether or not a blood flow disorder has occurred in a living body, wherein the blood flow disorder determination device performs Fourier transform on a plurality of pulse wave data.
  • Generating unit for generating a plurality of spectrum data, a detecting unit for detecting one or a plurality of peaks included in the plurality of spectrum data, and a frequency of detecting one or a plurality of peaks for each predetermined frequency section And a first determination unit that determines whether or not one or more peaks are artifacts based on the frequency, and a plurality of spectral data when it is determined that the one or more peaks are not artifacts And a second determination unit that determines whether or not a blood flow disorder has occurred in the living body.
  • the pulse wave data is determined by determining whether or not the one or more peaks are artifacts based on the frequency of the one or more peaks included in the spectrum data instead of the power of the spectrum data.
  • Blood flow disorders can be determined by reducing the artifacts contained in.
  • 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 included in pulse wave data. can do.
  • FIG. 1 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
  • 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 measures the measured pulse wave data through the transmitter 30 to the blood flow.
  • the information is transmitted to the failure determination device 10, and the blood flow failure determination device 10 determines whether or not a blood flow failure has occurred in the living body 1.
  • the blood flow disorder includes congestion and ischemia.
  • the sensor 20 and the transmitter 30 are connected by wired communication, and the transmitter 30 and the blood flow disorder determination device 10 are connected by wireless communication.
  • the communication method is arbitrary.
  • the blood flow disorder determination device 10 is composed of a tablet computer.
  • the blood flow disorder determination device 10 may be configured by a laptop computer or another type of computer.
  • the blood flow disorder determination system 100 measures the time change of the color of the living body 1 with the sensor 20 or the time change of the temperature of the living body 1, and transmits the measured color data and temperature data to the transmitter 30. To the blood flow disorder determination device 10, and the blood flow disorder determination device 10 determines whether or not a blood flow disorder has occurred in the living body 1.
  • FIG. 2 is a diagram showing an outline of the sensor 20 included in the blood flow disorder determination system 100 according to the present embodiment.
  • the sensor 20 includes a pulse wave sensor 21 that measures the time change of the pulse wave of the living body 1 in a plurality of different periods, a color sensor 22 that measures the time change of the color of the living body 1, and a time change of the temperature of the living body 1. And a temperature sensor 23 that operates.
  • 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 blood flow data of one channel. The sensor 20 according to this embodiment outputs a total of four channels of blood flow data.
  • 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 configured by, 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 include, for example, a photodiode that detects infrared light, 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, for example, a thermistor.
  • FIG. 3 is a diagram showing functional blocks 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, from the pulse wave sensor 21 via the transmitter 30, 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. In addition, 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 performs Fourier transform on each of the plurality of pulse wave data to generate a plurality of spectrum data.
  • the generation unit 12 may generate a plurality of spectrum data by performing a fast Fourier transform on a plurality of pulse wave data measured at a predetermined sampling rate.
  • the predetermined sampling rate may be 16 Hz, for example.
  • the detection unit 13 detects one or a plurality of peaks included in a plurality of spectrum data.
  • the detection unit 13 may detect the maximum points of the plurality of spectrum 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 calculator 14 may calculate the frequency at which one or a plurality of 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 spectrum data is equal to or more than the first threshold. When the sum of the powers of the plurality of spectrum data is not equal to or more than the first threshold, the first determination unit 15 does not have to determine whether one or more peaks are artifacts. As described above, when one or more peaks are artifacts when the power of the spectrum data is sufficiently high, it is possible to reduce the artifacts included in the pulse wave data and determine the blood flow disorder. it can.
  • the second determination unit 16 determines whether or not the blood flow disorder has occurred in the living body 1 based on the plurality of spectrum data. Details of the determination by the second determination unit 16 will be described later.
  • the blood flow disorder determination device 10 determines whether or not one or a plurality of peaks are artifacts based on the frequency of the one or a plurality of peaks included in the spectrum data, not the power of the spectrum data. By determining, the blood flow disorder can be determined by reducing the artifacts included in the pulse wave data.
  • the determining unit 17 determines the values of one or a plurality of parameters included in a predetermined function that approximates time series data including at least one of color data and temperature data. Specifically, when time is represented by t and one or more parameters are represented by A, A 0, and ⁇ , the predetermined function may be A ⁇ exp( ⁇ t/ ⁇ )+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 change can be calculated.
  • the first estimation unit 18 estimates the degree of risk based on the values of one or more 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 a blood flow disorder has occurred in the living body 1, based on the estimated risk. In this way, the occurrence of the blood flow disorder can be determined from the viewpoint different from the pulse wave, based on the temporal change of at least one of the color and the temperature of the living body 1.
  • the second estimation unit 19 changes with time based on the rate at which it is determined that the blood flow disorder has occurred when the determinations by the first determination unit 15 and the second determination unit 16 are performed multiple times 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 estimating unit 19 can reduce the artifacts included 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 determination 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, a ROM (Read Only Memory) 10c corresponding to a storage unit, and It has a section 10d, an input section 10e, and a display section 10f.
  • a bus so that data can be transmitted and received.
  • 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.
  • the configuration shown in FIG. 4 is an example, and the blood flow disorder determination device 10 may have a configuration other than these, or may not have some of these configurations.
  • the CPU 10a is a control unit that controls the execution of programs stored in the RAM 10b or the ROM 10c, calculates data, and processes the 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 and the 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 executed by the CPU 10a, pulse wave data, color data, temperature data, and the like. Note that these are merely examples, and data other than these may be stored in the RAM 10b, or some 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 and data that is not rewritten.
  • the communication unit 10d is an interface that connects 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 or 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 the pulse wave data, the color data, and the risk of blood flow disorder.
  • the blood flow disorder determination program may be provided by being stored in a computer-readable storage medium such as the RAM 10b or the ROM 10c, or may be provided via a communication network connected by the communication unit 10d.
  • the CPU 10a executes the blood flow disorder determination program, so that the various operations described with reference to FIG. 3 are realized.
  • the blood flow disorder determination device 10 may include an LSI (Large-Scale Integration) in which the CPU 10a and the RAM 10b and the ROM 10c are integrated.
  • FIG. 5 is a flowchart of the first process executed by the blood flow disorder determination system 100 according to this embodiment.
  • the first process is a process of calculating the pulse wave risk level based on the pulse wave data.
  • the blood flow disorder determination system 100 measures 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 the series of pulse wave data into predetermined lengths (S11). For example, the blood flow disorder determination device 10 divides the pulse wave data continuously measured for about 3 minutes into 9 pieces of data having a length of about 21 seconds, and removes the first half of 5 seconds of each of the 9 pieces of data. Then, nine pulse wave data of about 16 seconds may be created. The nine pulse wave data of about 16 seconds may include sampling data of 256 points.
  • the blood flow disorder determination device 10 Fourier transforms a plurality of pulse wave data to generate a plurality of spectrum data (S12). Specifically, the blood flow disorder determination device 10 performs fast Fourier transform on nine pulse wave data having a length of about 16 seconds to generate nine spectrum data.
  • the blood flow disorder determination device 10 calculates the total power of a plurality of spectrum data (S13).
  • the total power may be a value obtained by integrating the power of the spectrum data in a predetermined frequency range.
  • the predetermined frequency range may be, for example, 0.5-2 Hz. Note that 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 spectrum data.
  • the blood flow disorder determination device 10 determines whether the total power of the spectrum data is equal to or higher 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 intensity of the pulse wave data is sufficiently strong, the blood flow disorder determination device 10 excludes the artifact and performs a process of calculating an evaluation value. (S15). The same process will be described in detail with reference to the next figure. When the pulse wave data is excluded 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.
  • the blood flow disorder determination device 10 sets the average value of the total power of the plurality of spectrum data as the evaluation value. Calculate (S17).
  • the blood flow disorder determination device 10 may calculate the evaluation value by the average value of the sum of the powers of the plurality of spectrum data. For example, when the total power of the spectrum data is represented by 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 . ..
  • the blood flow disorder determination device 10 determines that a blood flow disorder has occurred (S19). On the other hand, when the calculated evaluation value is not less than or equal to the second threshold value (S18: NO), the blood flow disorder determination device 10 determines that the blood flow disorder has not occurred (S20).
  • the blood flow obstruction determination device 10 is based on the ratio of the blood flow obstruction determined to have occurred when the first determination unit 15 and the second determination unit 16 make a plurality of determinations in a predetermined period.
  • Pulse wave risk is calculated (S21).
  • the blood flow disorder determination device 10 uses a value obtained by dividing the number of times that the blood flow disorder has been determined by the second determination unit 16 within 30 minutes by the total number of determinations by the second determination unit 16. The pulse wave risk may be calculated.
  • 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 excluding the artifacts and calculating the evaluation value when the total power of the spectrum data is equal to or more than the first threshold value.
  • the figure shows the details of the process (S15) of "excluding artifacts and calculating evaluation value" shown in FIG.
  • the blood flow disorder determination device 10 detects one or a plurality of peaks included in a plurality of spectrum data (S151). For example, the blood flow disorder determination device 10 may detect, as one or a plurality of peaks, a maximum point having a size of 1 ⁇ 3 or more of the maximum value among the maximum points of the plurality of spectrum data.
  • the blood flow disorder determination device 10 calculates the frequency at which one or more 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 0.075 Hz section.
  • the blood flow disorder determination device 10 determines whether or not the highest frequency among the frequencies of one or a plurality of peaks is a reference value or more (S153). For example, when detecting one or a plurality of peaks from each of the nine spectrum data, the number of times the peak is detected in each frequency section is a value of 0-9. 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.
  • the blood flow disorder determination device 10 When the highest frequency is equal to or higher than the reference value among the frequencies of one or a plurality of peaks (S153: YES), the blood flow disorder determination device 10 identifies the frequency section with the highest frequency (S154). Then, the blood flow disorder determination device 10 calculates the average value of the power of the plurality of spectrum data regarding the specified frequency section as the evaluation value (S155). The blood flow disorder determination device 10 identifies the frequency section having the highest frequency among the one or the plurality of peaks determined not to be artifacts, and calculates the average value of the powers of the plurality of spectrum data regarding the frequency section as the evaluation value. You may.
  • the blood flow disorder determination device 10 determines the peak as an artifact and excludes it (S156). In this way, the blood flow disorder determination device 10 determines whether or not one or a plurality of peaks are artifacts based on the frequency of the one or a plurality of peaks included in the spectrum data, not the power of the spectrum data. By doing so, the artifacts included in the pulse wave data can be reduced. With the above, the second processing ends.
  • the blood flow disorder determination device 10 identifies a frequency section having the highest frequency among one or a plurality of peaks determined not to be artifacts, and an average value of powers of a plurality of spectrum data regarding the frequency section is equal to or less than a second threshold value. In some cases, it is determined that the blood flow disorder has occurred in the living body 1. Thereby, the power corresponding to the frequency of the pulse wave can be more accurately captured, and the occurrence of the blood flow disorder can be more accurately determined.
  • the blood flow disorder determination device 10 uses the living body 1 when the sum of the powers of the plurality of spectrum data is less than the first threshold and when the average value of the sum of the powers of the plurality of spectrum data is less than or equal to the second threshold. It is determined that there is blood flow disorder. In this way, when the power of spectrum data is relatively low, the occurrence of blood flow disorder is determined by determining the occurrence of blood flow abnormality depending on whether or not the average value of the sum of the powers of multiple spectrum data is sufficiently high. Can be determined more accurately.
  • FIG. 7 is a diagram showing a plurality of spectrum data S1 to S9 generated by the blood flow disorder determination device 10 according to the present embodiment and one or a plurality of peaks P1 to P9 included in the plurality of spectrum data S1 to S9. ..
  • the horizontal axis represents frequency in units of Hz
  • the vertical axis represents power in arbitrary units.
  • Each of the one or a plurality of peaks P1 to P9 represents frequency in arbitrary units
  • the vertical axis represents power in arbitrary units.
  • the plurality of spectrum data S1 to S9 are data obtained by fast Fourier transforming 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 spectrum data S1 to S9.
  • a single peak corresponding to the pulse wave frequency is often detected from the spectrum data. Then, from a plurality of spectrum data, a peak is often detected in a frequency section corresponding to the pulse wave frequency.
  • 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 determination device 10 according to the present embodiment.
  • the frequencies of a plurality of peaks included in the nine spectrum data are shown as a first histogram H1. There is.
  • the section between 1.51 Hz and 1.59 Hz is the highest frequency section PW.
  • the maximum frequency is 6.
  • the reference value is 6, in the example shown in the figure, since the highest peak frequency is equal to or higher than the reference value, it is determined that the peak frequency is not an artifact. In this case, it is determined based on the nine spectrum data whether or not a blood flow disorder has occurred.
  • 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 determination device 10 according to the present embodiment.
  • the frequency of a plurality of peaks included in the nine spectrum data is calculated as a second histogram H2. Is shown as.
  • the second histogram H2 peak frequencies are scattered in the frequency range of 0.5 Hz to 2 Hz, and the frequency range of 0.97 Hz to 1.05 Hz is the highest frequency range.
  • the highest frequency is 3.
  • the reference value is 6, in the example shown in the same figure, since the maximum frequency of peaks is less than the reference value, it is determined to be an artifact and excluded. In this case, the 9 pieces of spectral data are not used for determining the blood flow disorder and are discarded.
  • FIG. 10 is a flowchart of the third process executed by the blood flow disorder determination system 100 according to this embodiment.
  • the third process is a process of calculating the risk degree based on the color data.
  • the blood flow disorder determination system 100 uses the color sensor 22 to measure color data at a predetermined sampling rate (S30). After that, the blood flow disorder determination device 10 smoothes the color data (S31). For example, the blood flow obstruction determination device 10 replaces y2 with y1 when
  • the blood flow disorder determination device 10 converts the color data into the lightness data (S32).
  • the blood flow disorder determination device 10 may convert the RGB-IR color system color data into the XYZ color system color data, and extract the Y value to convert the lightness data.
  • the blood flow disorder determination device 10 determines the parameters of a predetermined function that approximates the brightness data (S33).
  • the blood flow disorder determination device 10 uses A ⁇ exp( ⁇ t/ ⁇ )+A 0 as a predetermined function when the time is represented by t and one or more parameters are represented by A, A 0, and ⁇ .
  • A, A 0 and ⁇ may be determined to approximate the data.
  • the fitting of the predetermined function may be performed by solving the least squares method by, for example, 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 parameters (S34).
  • the blood flow disorder determination device 10 may calculate the coefficient of determination by Goodness of Fitting (GoF) that takes a value from 0 to 100.
  • the first estimation unit 18 of the blood flow disorder determination device 10 calculates the index based on the values of the one or more parameters and the coefficient of determination of the one or more parameters, and updates the risk level based on the index. By doing so, the time-varying risk may be estimated. Accordingly, it is possible to calculate the index based on the goodness of fit of the approximation by the predetermined function and the magnitude of the temporal change, and to estimate the risk of temporal change.
  • the first estimation unit 18 updates the risk by adding the index to the previous value of the risk, and the absolute value of the index is less than the third threshold. If, then the risk may be updated with the larger value 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 change both when the time series data (brightness data) decreases and when the time series data increases. With the above, the third processing ends.
  • FIG. 11 is a diagram showing a risk degree estimated based on color data by the blood flow disorder determination device 10 according to the present embodiment.
  • the horizontal axis indicates the number of days elapsed
  • the vertical axis indicates 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 danger based on the four color data measured by the four-channel color sensor 22. From FIG. 11, it can be seen that the first risk level C1 indicated by the solid line and the second risk level C2 indicated by the alternate long and short dash line sharply increase on the night of the third day (Day 3). The first risk C1 rises to near the maximum value of 1.0 and then maintains about 1.0. Further, the second risk C2 rises to about 0.3 and then maintains about 0.3.
  • the risk is constant near the maximum value for at least one channel of color data, and it can be determined that there is a high probability that blood flow disorder has occurred 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 this embodiment.
  • the fourth process is a process of calculating the risk degree based on the temperature data.
  • 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 obstruction determination device 10 replaces y2 with y1 when
  • the blood flow disorder determination device 10 determines a parameter of a predetermined function that approximates the temperature data (S42).
  • the blood flow disorder determination apparatus 10 uses A ⁇ exp( ⁇ t/ ⁇ )+A 0 as a predetermined function when the time is represented by t and one or more parameters are represented by A, A 0, and ⁇ .
  • A, A 0 and ⁇ may be determined to approximate the data.
  • the fitting of the predetermined function may be performed by solving the least squares method by, for example, 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 parameters (S43).
  • ⁇ 1/4
  • ⁇ may be selected so that the mode exp( ⁇ 2 ) of the lognormal distribution is 2.
  • FIG. 13 is a diagram showing a risk degree estimated based on temperature data by the blood flow disorder determination device 10 according to the present embodiment.
  • the horizontal axis indicates the number of days elapsed
  • the vertical axis indicates the degree of risk.
  • the figure shows the result of calculating the degree of danger based on the temperature data measured by the four-channel temperature sensor 23.
  • the blood flow disorder determination device 10 estimates the degree of danger based on the four temperature data measured by the four-channel temperature sensor 23. From FIG. 13, it can be seen that the first risk level T1 shown by the solid line rises to near 1.0 at noon on the sixth day (Day 6) and then returns to zero. In addition, it can be seen that the second risk level T2 indicated by the alternate long and short dash line in the morning of the fourth day (Day 4) has risen to about 0.4 and then returned to zero. Further, it can be seen that the third risk level T3 indicated by the chain double-dashed line increased to about 0.4 at midnight on the seventh day (Day 7) and then returned to 0. It can also be seen that the fourth risk level T4 indicated by the broken line rises to about 0.1 at midnight on the first day (Day 1), and then returns to zero.
  • FIG. 14 is a flowchart of the fifth process executed by the blood flow disorder determination system 100 according to this embodiment.
  • the fifth process is a process for comprehensively determining whether or not a blood flow disorder has occurred in the living body 1.
  • 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). Further, the blood flow disorder determination system 100 executes the third processing shown in FIG. 10 to calculate the color risk (S51). Further, the blood flow disorder determination system 100 executes the fourth process shown in FIG. 12 to calculate the temperature risk (S51). The order of executing these processes is arbitrary.
  • the blood flow disorder determination system 100 When the pulse wave data is excluded as an artifact (S53: YES), the blood flow disorder determination system 100 outputs that the artifact is detected (S54). The output may be performed by displaying a message on the display unit 10f of the blood flow disorder determination device 10, for example. The output indicating that the artifact is detected may be omitted.
  • the blood flow disorder determination system 100 determines that any one of the pulse wave risk, the color risk, and the temperature risk is equal to or higher than the fourth threshold value. Is determined (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, if any of the risks is equal to or higher than the fourth threshold value (S55: YES), the fact that the blood flow disorder has occurred is output (S57). With the above, the fifth process ends.
  • the second determination unit 16 of the blood flow disorder determination device 10 uses the plurality of pulse wave data to cause the blood flow disorder in the living body 1. 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, there is a blood flow disorder in the living body 1. A comprehensive determination may be made as to 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 to comprehensively determine whether the blood flow disorder has occurred based on the pulse wave, the color, and the temperature.
  • the second determination unit 16 of the blood flow disorder determination device 10 causes the 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 the fourth threshold value or more. May be comprehensively determined as occurring. In this way, by comprehensively determining that a blood flow disorder has occurred when at least one of the pulse wave, color, and temperature of the living body 1 has a high risk of blood flow disorder, it is possible to reduce the oversight of the blood flow disorder. You can
  • 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 degree calculated using the color data and the risk degree calculated using the temperature data.
  • the type may be determined.
  • congestion occurs as a blood flow disorder
  • the risk calculated using the color data is expected to increase, but since the temperature of the living body 1 does not decrease with congestion, it was calculated using the temperature data. The risk is usually not increased.
  • 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 the risk calculated using the temperature data also increases. It is expected. In this way, it is possible to discriminate whether the blood flow disorder such as congestion or ischemia is occurring, based on the combination of the risk of color and the risk of temperature.
  • FIG. 15 is a diagram showing a first example of the degree of risk and the detection rate of artifacts comprehensively determined by the blood flow disorder determination device 10 according to the present embodiment.
  • the comprehensively determined risk R1 and the artifact detection rate A1 are shown.
  • the horizontal axis of the comprehensively determined risk R1 and the artifact detection rate A1 is time, and the vertical axis thereof is a value of 0 to 1.
  • the solid line, the alternate long and short dash line, the alternate long and two short dashes line and the broken line indicate the artifact detection rate A1 regarding the pulse wave data of four channels.
  • the comprehensively judged risk R1 is 0 over all the time except the measurement start time. Further, the artifact detection rate A1 frequently increases for the pulse wave data of four channels. As described above, according to the blood flow disorder determination device 10 according to the present embodiment, the blood flow disorder can be determined by reducing the artifacts included in the pulse wave data.
  • 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.
  • the comprehensively determined risk R2 and the artifact detection rate A2 are shown.
  • the abscissa of the comprehensively determined risk R2 and the artifact detection rate A2 is time, and the ordinate is a value of 0 to 1.
  • the solid line, the alternate long and short dash line, the alternate long and two short dashes line, and the broken line indicate the risk R2 comprehensively determined for four channels and the artifact detection rate A2 for pulse wave data for four channels.
  • the comprehensively judged risk level R2 is close to 1 over all time. Therefore, in this example, it is considered highly probable that the blood flow disorder has occurred in the living body 1. Further, 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 determination device 10 according to the present embodiment, it is possible to reduce the artifacts included in the pulse wave data and comprehensively determine whether the blood flow disorder is caused by the pulse wave, the color, and the temperature. Can be determined.
  • FIG. 17 is a flowchart of the sixth process executed by the blood flow disorder determination system according to this 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 determines that the probability distribution of the pulse wave data measured in the reference period of the plurality of different periods and the probability distribution of the pulse wave data measured in the target period of the plurality of different periods. Compute a test statistic that tests for equality.
  • the reference period may be from a time point when the measurement of the pulse wave data is started until a predetermined time period elapses
  • the target time period may be from a current time point up to a predetermined time period. From the data obtained in 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 based on the average and the 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. The calculating unit 14 also calculates a 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 a blood flow disorder has occurred in the living body 1, based on the test statistic. The second determination unit 16 determines that the blood flow disorder is occurring in the living body 1 when the D value is equal to or greater than the fifth threshold value, and determines the blood flow disorder in the living body 1 when the D value is less than the fifth threshold value. May be determined not to occur.
  • 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 defines the 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). The blood flow disorder determination device 10 also 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).
  • the blood flow disorder determination 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 determination device 10 determines that the blood flow disorder has not occurred in the living body 1 (S66).
  • FIG. 18 is a diagram showing the D value calculated by the blood flow disorder determination device 10 according to the present embodiment and the blood flow disorder detection timing.
  • the horizontal axis shows time
  • the upper vertical axis shows the magnitude of pulse wave data (Pulse Power) dimensionlessly
  • the lower vertical axis shows the magnitude of D value dimensionlessly. ..
  • the 4-channel pulse wave data 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 The D value for testing whether or not the probability distributions of are equal is calculated.
  • the graph D of the D value significantly exceeds the fifth threshold Th at a certain time point, and the blood flow disorder determination device 10 determines that the blood flow disorder has occurred in the living body 1 at the first time point d1.
  • the doctor regularly makes a round of the patient to determine whether or not a blood flow disorder has occurred.
  • the doctor determines that the blood flow disorder has occurred in the living body 1 at the second time point d2.
  • the blood flow obstruction determination device 10 enables continuous monitoring, and the occurrence of a blood flow obstruction can be detected promptly.
  • the characteristics of the pulse wave data are relatively determined by focusing on the difference between the probability distribution of the pulse wave data of the reference period and the probability distribution of the pulse wave data of the target period. It is possible to determine whether or not a blood flow disorder has occurred by performing a physical evaluation.
  • the sensor 20 may be attached to a place where the blood flow disorder is concerned, but a place where the blood flow disorder is concerned. It may be attached so as to straddle a normal place.
  • the pulse wave sensor 21 of at least one channel is attached to a place where blood flow disorder is concerned, and at least another channel is used.
  • the pulse wave sensor 21 is attached to a normal place.
  • the blood flow disorder determination device 10 uses the pulse wave data of the channel corresponding to the normal place as a reference, and the probability distribution of the pulse wave data of the channel corresponding to the normal place, and the place where the blood flow disorder is concerned.
  • a test statistic for testing whether or not the probability distribution of the pulse wave data of the channel corresponding to is equal may be calculated.
  • a plurality of sensors 20 may be prepared, a first sensor including a plurality of channels may be attached to a normal place, and another sensor including a plurality of channels may be attached to a place where blood flow disorder is concerned.
  • the blood flow disorder determination device 10 uses the probability distribution of the pulse wave data of the first sensor attached to a normal place and the probability distribution of the pulse wave data of the second sensor attached to a place where blood flow disorder is concerned. A test statistic for testing whether and are equal may be calculated.
  • FIG. 19 is a flowchart of the seventh process executed by the blood flow disorder determination system 100 according to this embodiment.
  • the sixth process is a process of removing noise based on infrared data and calculating a risk level based on color data.
  • the color data measured by the color sensor 22 of the blood flow disorder determination system 100 includes infrared data
  • the determination unit 17 includes the noise-removed time-series data in a predetermined function that approximates the infrared data.
  • the value of one or more parameters to be set is determined.
  • the noise removal based on the infrared data may be performed, for example, by removing the color data at that time as noise when the size of the infrared data is equal to or larger than the sixth threshold value.
  • the blood flow disorder determination system 100 uses the color sensor 22 to measure color data at a predetermined sampling rate (S70).
  • the blood flow disorder determination device 10 removes the color data in the section in which the infrared data is equal to or greater than the sixth threshold value to remove noise related to the color data (S71). Thereafter, the blood flow disorder determination device 10 smoothes the color data (S72). The smoothing may be performed similarly to the third processing.
  • the blood flow disorder determination device 10 converts color data into lightness data (S73).
  • the conversion from color data to lightness data may be performed in the same manner as the third process.
  • the blood flow disorder determination device 10 determines a parameter 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 parameters (S75). The index may be calculated similarly to the third process.
  • the blood flow disorder determination device 10 determines whether or not the absolute value of the index is greater than or equal to the third threshold value (S76). When the index is equal to or greater than the third threshold value (S76: YES), the blood flow disorder determination 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 greater than or equal to the third threshold value (S76: NO), the risk is updated with the larger value of the previous risk and the index (S78).
  • FIG. 20 is a diagram showing color data with noise removed and color data without noise measured by the blood flow disorder determination system 100 according to the present embodiment.
  • the horizontal axis represents time
  • the upper vertical axis represents the lightness of noise-removed color data in a non-dimensional manner
  • the lower vertical axis represents the brightness of non-noise-removed color data in a non-dimensional manner. Shows.
  • the 4-channel color data is indicated by a solid line, a one-dot chain line, a two-dot chain line, and a broken line.
  • the graph Y1 of color data from which noise has been removed is data in which discontinuous portions are included and the portions have been removed as noise.
  • the graph Y2 of the color data without noise removal is continuous.
  • FIG. 21 is a diagram showing a risk degree estimated based on color data by the blood flow disorder determination device 10 according to the present embodiment.
  • the horizontal axis indicates the number of days elapsed
  • the vertical axis indicates the degree of risk.
  • the result of calculating the degree of danger based on the color data measured by the 4-channel color sensor 22 and noise-removed based on the infrared data is shown.
  • the blood flow disorder determination device 10 estimates the degree of danger based on the four color data from which noise has been removed. It can be seen from FIG. 21 that the first risk level C1 indicated by the solid line and the second risk level C2 indicated by the alternate long and short dash line are rapidly increasing on the night of July 30, 2018. The first risk C1 has risen to a maximum value of nearly 1.0, and has been maintained at about 0.6 thereafter. Further, the second risk C2 rises to about 0.3 and then maintains about 0.3. In addition, the third risk C3 indicated by the chain double-dashed line and the fourth risk C4 indicated by the broken line rise to about 0.1 on the morning of July 31, 2018, and then maintain about 0.1. ing.
  • the present invention calculates a risk of blood flow disorder based on at least one of color data and temperature data of a living body, and a blood flow disorder determination device capable of determining a blood flow disorder based on the risk.
  • a failure determination method a blood flow failure determination program, and a blood flow failure determination system.
  • 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 a risk level based on the values of the one or more parameters; A second determination unit that determines whether or not a blood flow disorder has occurred in the living body based on the risk level; A device for determining blood flow disorders.
  • the first estimation unit calculates an index based on the value of the one or more parameters and the coefficient of determination of the one or more parameters, and updates the risk based on the index, thereby changing with time. Estimating the risk, The blood flow disorder determination device according to attachment 1.
  • the first estimation unit is When the absolute value of the index is equal to or greater than a third threshold value, the risk level is updated by adding the index to the previous value of the risk level, If the absolute value of the index is less than the third threshold value, the risk level is updated with a larger value of the previous value of the risk level and the index, The blood flow disorder determination device according to attachment 2 or 3.
  • 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 generation unit that generates a plurality of spectrum data by Fourier transforming each of the plurality of pulse wave data, A detector for detecting one or more peaks contained in the plurality of spectrum data; A calculation unit that calculates the frequency at which the one or more peaks are detected for each predetermined frequency section; A first determination unit that determines whether or not the one or more peaks are artifacts based on the frequency, The second determination unit, when it is determined that the one or more peaks are not artifacts, determines whether or not a blood flow disorder has occurred in the living body based on the plurality of spectrum data, 5.
  • the blood flow disorder determination device according to any one of appendices 1 to 4.
  • the first determination unit determines whether or not the one or more peaks are artifacts when the sum of powers of the plurality of spectrum data is equal to or more than a first threshold value.
  • the blood flow disorder determination device according to attachment 5.
  • the second determination unit identifies a frequency section having the highest frequency among the one or a plurality of peaks determined not to be the artifact, and an average value of powers of the frequency sections of the plurality of spectrum data is a second threshold value.
  • Appendix 8 When the sum of the powers of the plurality of spectrum data is less than a first threshold, the second determination unit determines that the living body has the average value of the sum of the powers of the plurality of spectrum data is equal to or less than a second threshold. It is determined that a blood flow disorder has occurred, The blood flow disorder determination device according to appendix 6 or 7.
  • the time-varying pulse wave risk is estimated based on the rate at which it is determined that a blood flow disorder has occurred when the determinations by the first determination unit and the second determination unit are performed multiple times within a predetermined period. Further comprising a second estimation unit, 9.
  • the blood flow disorder determination device according to any one of appendices 5 to 8.
  • the second determination unit determines whether or not a blood flow disorder has occurred in the living body by using the plurality of pulse wave data. , Based on the result of determining whether the blood flow disorder has occurred in the living body using at least one of the color data and the temperature data, whether the blood flow disorder has occurred in the living body. Comprehensive judgment, The blood flow disorder determination device according to attachment 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 a fourth threshold value or more, The blood flow disorder determination device according to attachment 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, Determining values of one or more parameters included in a predetermined function approximating the time series data; Estimating a risk level based on the values of the one or more parameters; Based on the risk, to determine whether or not a blood flow disorder has occurred in the living body, A blood flow disorder determination method including the following.
  • 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 measured with time of the color of a living body and temperature data measured with time 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 a risk level 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 risk level. , Blood flow disorder judgment program to function as.
  • At least one of the color data obtained by measuring the time change of the color of the living body and the temperature data obtained by measuring the time change of the temperature of the living body is measured, and the time series data including at least one of the color data and the temperature data is output.
  • a sensor and a blood flow disorder determination system comprising a blood flow disorder determination device that determines whether or not a blood flow disorder has occurred in the living body using the time series data, The blood flow disorder determination device, 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 a risk level based on the values of the one or more parameters; A second determination unit that determines whether or not a blood flow disorder has occurred in the living body based on the risk level. Blood flow disorder determination system.

Abstract

Provided is a blood flow obstruction determination device, for example, with which it is possible to reduce artifacts included in pulse wave data and to determine blood flow obstruction. The blood flow obstruction determination device (10) is provided with: an acquisition unit (11) which acquires a plurality of pulse wave data items by measuring temporal changes in a pulse wave of a living body (1) in a plurality of different periods; a generation unit (12) which generates a plurality of spectral data items by subjecting each of the plurality of pulse wave data items to Fourier transform; a detection unit (13) which detects one or a plurality of peaks included in the plurality of spectral data items; a calculation unit (14) which calculates the frequency of detection of the one or a plurality of peaks in each of predetermined frequency intervals; a first determination unit (15) which, on the basis of the frequency, determines whether the one or a plurality of peaks represent an artifact; and a second determination unit (16) which, if it has been determined that the one or a plurality of peaks do not represent an artifact, determines whether blood flow obstruction is occurring in the living body on the basis of the plurality of spectral data items.

Description

血流障害判定装置、血流障害判定方法、血流障害判定プログラム及び血流障害判定システムBlood flow disorder determination device, blood flow disorder determination method, blood flow disorder determination program, and blood flow disorder determination system
　本発明は、血流障害判定装置、血流障害判定方法、血流障害判定プログラム及び血流障害判定システムに関する。 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.
　従来、医療現場では、鬱血や虚血といった血流障害が生じているか否かを医療スタッフが判断している。例えば、患者の生体組織を圧迫して変色させてから色が元に戻るまでの時間によって判断するレフィル法、生体組織の色によって判断する方法及び生体組織に針を刺した際の出血状態から判断する方法によって血流障害の可能性が判断されている。 Traditionally, medical staff have determined whether or not blood flow disorders such as congestion and ischemia have occurred in the medical field. For example, a refill method that determines by the time it takes for the color of the patient's living tissue to change color after being pressed and discolored, a method of determining by the color of the living tissue, and a bleeding condition when a needle is pierced into the living tissue. The possibility of blood flow disorder is determined by the method.
　血流障害の検出を自動化する技術として、下記特許文献１には、生体組織の異なる血流情報を計測する複数の種類の感知手段を、柔軟な基材上にそれぞれ複数配置してなるセンサーシートを有する血流障害検出装置が記載されている。 As a technique for automating the detection of blood flow disorder, the following Patent Document 1 discloses a sensor sheet in which a plurality of types of sensing means for measuring blood flow information of different living tissues are arranged on a flexible base material. A blood flow disorder detection device having the above is described.
国際公開第２０１７／０２６３９３号International Publication No. 2017/026393
　特許文献１に記載の技術によれば、ウェアラブルセンサによって測定した患者の脈波、皮膚の色及び皮膚の温度に基づいて血流障害を検出することができる。 According to the technique described in Patent Document 1, a blood flow disorder can be detected based on the pulse wave of the patient, the color of the skin, and the temperature of the skin measured by the wearable sensor.
　しかしながら、測定を長時間にわたって行う場合、患者が常に静止しているとは限らず、患者の体動によって脈波データにアーティファクトが混入することがある。脈波データにアーティファクトが含まれると、誤って血流障害と判定したり、血流障害を見逃したりするおそれがある。 However, if the measurement is performed for a long time, the patient is not always stationary, and artifacts may be mixed in the pulse wave data due to the body movement of the patient. If the pulse wave data includes an artifact, there is a possibility that the blood flow disorder may be erroneously determined or the blood flow disorder may be missed.
　そこで、本発明は、脈波データに含まれるアーティファクトを減らして血流障害を判定することができる血流障害判定装置、血流障害判定方法、血流障害判定プログラム及び血流障害判定システムを提供する。 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 reduce blood flow disorders by reducing artifacts included in pulse wave data. To do.
　本発明の一態様に係る血流障害判定装置は、生体の脈波の時間変化を複数の異なる期間に測定した複数の脈波データを取得する取得部と、複数の脈波データをそれぞれフーリエ変換して複数のスペクトルデータを生成する生成部と、複数のスペクトルデータに含まれる１又は複数のピークを検出する検出部と、所定の周波数区間毎に１又は複数のピークが検出された頻度を算出する算出部と、頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定する第１判定部と、１又は複数のピークがアーティファクトでないと判定された場合に、複数のスペクトルデータに基づいて、生体に血流障害が発生しているか否かを判定する第２判定部と、を備える。 The blood flow disorder determination device according to an 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 each of the plurality of pulse wave data. Generating unit for generating a plurality of spectrum data, a detecting unit for detecting one or a plurality of peaks included in the plurality of spectrum data, and a frequency of detecting one or a plurality of peaks for each predetermined frequency section And a first determination unit that determines whether or not one or more peaks are artifacts based on the frequency, and a plurality of spectral data when it is determined that the one or more peaks are not artifacts And a second determination unit that determines whether or not a blood flow disorder has occurred in the living body.
　この態様によれば、スペクトルデータのパワーではなく、スペクトルデータに含まれる１又は複数のピークの頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定することで、脈波データに含まれるアーティファクトを減らして血流障害を判定することができる。 According to this aspect, the pulse wave data is determined by determining whether or not the one or more peaks are artifacts based on the frequency of the one or more peaks included in the spectrum data instead of the power of the spectrum data. Blood flow disorders can be determined by reducing the artifacts contained in.
　上記態様において、第１判定部は、複数のスペクトルデータのパワーの和が第１閾値以上である場合に、１又は複数のピークがアーティファクトであるか否かを判定してもよい。 In the above aspect, the first determination unit may determine whether or not one or more peaks are artifacts when the sum of the powers of the plurality of spectrum data is equal to or greater than the first threshold.
　この態様によれば、スペクトルデータのパワーが十分に高い場合に１又は複数のピークがアーティファクトであるか否かを判定することとして、脈波データに含まれるアーティファクトを減らして血流障害を判定することができる。 According to this aspect, when the power of the spectrum data is sufficiently high, it is determined whether or not one or more peaks are artifacts, and the blood flow disorder is determined by reducing the artifacts included in the pulse wave data. be able to.
　上記態様において、第２判定部は、アーティファクトでないと判定された１又は複数のピークのうち最も頻度が高い周波数区間を特定し、複数のスペクトルデータの周波数区間のパワーの平均値が第２閾値以下である場合に、生体に血流障害が発生していると判定してもよい。 In the above aspect, the second determination unit identifies the frequency section having the highest frequency among the one or the plurality of peaks determined not to be an artifact, and the average value of the power of the frequency sections of the plurality of spectrum data is equal to or less than the second threshold value. If it is, it may be determined that a blood flow disorder has occurred in the living body.
　この態様によれば、脈波の周波数に対応するパワーをより正確に捉えることができ、血流障害の発生をより正確に判定することができる。 According to this aspect, the power corresponding to the frequency of the pulse wave can be more accurately captured, and the occurrence of blood flow disorder can be more accurately determined.
　上記態様において、第２判定部は、複数のスペクトルデータのパワーの和が第１閾値未満である場合、複数のスペクトルデータのパワーの和の平均値が第２閾値以下である場合に、生体に血流障害が発生していると判定してもよい。 In the above aspect, when the sum of the powers of the plurality of spectrum data is less than the first threshold value, the second determination unit determines whether the average value of the sum of the powers of the plurality of spectrum data is less than or equal to the second threshold value. It may be determined that a blood flow disorder has occurred.
　この態様によれば、スペクトルデータのパワーが比較的低い場合に、複数のスペクトルデータのパワーの和の平均値が十分に高いか否かによって血流異常の発生を判定することで、血流障害の発生をより正確に判定することができる。 According to this aspect, when the power of the spectrum data is relatively low, the occurrence of blood flow abnormality is determined by determining whether or not the average value of the sum of the powers of the plurality of spectrum data is sufficiently high, thereby determining the blood flow abnormality. Can be determined more accurately.
　上記態様において、取得部は、生体の色の時間変化を測定した色データ及び生体の温度の時間変化を測定した温度データの少なくともいずれかを含む時系列データを取得し、時系列データを近似する所定の関数に含まれる１又は複数のパラメータの値を決定する決定部と、１又は複数のパラメータの値に基づいて、危険度を推定する第１推定部と、をさらに備え、第２判定部は、危険度に基づいて、生体に血流障害が発生しているか否かを判定してもよい。 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 obtained by measuring the time change of the temperature of the living body, and approximates the time-series data. The second determination unit further includes a determination unit that determines the value of one or more parameters included in the predetermined function, and a first estimation unit that estimates the 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.
　この態様によれば、生体の色及び温度の少なくともいずれかの時間変化に基づいて、脈波とは異なる観点で血流障害の発生を判定することができる。 According to this aspect, it is possible to determine the occurrence of blood flow disorder from the viewpoint different from the pulse wave, based on the temporal change of at least one of the color and temperature of the living body.
　上記態様において、第１推定部は、１又は複数のパラメータの値及び１又は複数のパラメータの決定係数に基づいて指標を算出し、指標に基づいて危険度を更新することで、時間変化する危険度を推定してもよい。 In the above aspect, the first estimation unit 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 risk based on the index, thereby changing the risk over time. The degree may be estimated.
　この態様によれば、所定の関数による近似のあてはまりの良さと、時間変化の大きさとに基づいて指標を算出し、時間変化する危険度を推定することができる。 According to this aspect, it is possible to calculate the index based on the goodness of fit of the approximation by the predetermined function and the magnitude of the time change, and to estimate the risk of time change.
　上記態様において、時間をｔと表し、１又は複数のパラメータをＡ、Ａ０及びτと表すとき、所定の関数は、Ａ×ｅｘｐ（－ｔ／τ）＋Ａ０であってもよい。 In the above aspect, when the 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 .
　この態様によれば、時系列データが指数的に変化する状況を所定の関数によって近似して、変化の大きさに応じた危険度を算出することができる。 According to this aspect, it is possible to approximate the situation in which the time-series data changes exponentially by a predetermined function, and calculate the risk level according to the magnitude of the change.
　上記態様において、第１推定部は、指標の絶対値が第３閾値以上である場合、危険度の前回の値に指標を加算することで危険度を更新し、指標の絶対値が第３閾値未満である場合、危険度の前回の値と指標のいずれか大きい値により危険度を更新してもよい。 In the above aspect, when the absolute value of the index is equal to or greater than the third threshold, the first estimation unit updates the risk by adding the index to the previous value of the risk, and the absolute value of the index is the third threshold. If it is less than the risk level, the risk level may be updated with the larger value of the previous risk level and the index.
　この態様によれば、時系列データが減少する場合と増大する場合の両方について変化の大きさに応じた危険度を算出することができる。 According to this aspect, it is possible to calculate the degree of risk according to the magnitude of change both when the time series data decreases and when the time series data increases.
　上記態様において、所定期間に第１判定部及び第２判定部による判定を複数回行った場合における血流障害が発生していると判定された割合に基づいて、時間変化する脈波危険度を推定する第２推定部をさらに備えてもよい。 In the above aspect, the time-varying pulse wave risk is determined based on the rate at which the blood flow disorder is determined to have occurred when the determinations by the first determination unit and the second determination unit are performed multiple times in the predetermined period. A second estimating unit for estimating may be further provided.
　この態様によれば、脈波データに含まれるアーティファクトを減らして、時間変化する脈波危険度を推定することができる。 According to this aspect, it is possible to estimate the time-varying pulse wave risk by reducing the artifacts included in the pulse wave data.
　上記態様において、第２判定部は、１又は複数のピークがアーティファクトでないと判定された場合に、複数の脈波データを用いて生体に血流障害が発生しているか否かを判定した結果と、色データ及び温度データの少なくともいずれかを用いて生体に血流障害が発生しているか否かを判定した結果とに基づいて、生体に血流障害が生じているか否かを総合判定してもよい。 In the above aspect, the second determination unit, when one or a plurality of peaks is determined not to be an artifact, a result of determining whether a blood flow disorder has occurred in the living body by using a plurality of pulse wave data, Based on the result of determining whether the blood flow disorder is occurring in the living body using at least one of the color data and the temperature data, a comprehensive determination is made as to whether the blood flow disorder is occurring in the living body. Good.
　この態様によれば、生体の脈波データに基づいてアーティファクトを減らして、脈波、色及び温度に基づいて、総合的に血流障害が生じているか否かを判定することができる。 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 has occurred based on the pulse wave, the color, and the temperature.
　上記態様において、第２判定部は、脈波危険度及び危険度の少なくともいずれかが第４閾値以上である場合に、生体に血流障害が生じていると総合判定してもよい。 In the above aspect, the second determination unit may comprehensively determine that the blood flow is impaired 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.
　この態様によれば、生体の脈波、色及び温度の少なくともいずれかについて血流障害の危険性が高い場合に血流障害が生じていると総合判定することで、血流障害の見逃しを減らすことができる。 According to this aspect, when the blood flow disorder is high in at least one of the pulse wave, the color, and the temperature of the living body, it is comprehensively determined that the blood flow disorder is occurring, so that the overlooking of the blood flow disorder is reduced. be able to.
　上記態様において、色データは、赤外データを含み、決定部は、赤外データに基づいてノイズ除去された時系列データを近似する所定の関数に含まれる１又は複数のパラメータの値を決定してもよい。 In the above aspect, the color data includes infrared data, and the determining unit determines a value of one or more parameters included in a predetermined function that approximates the noise-removed time series data based on the infrared data. May be.
　この態様によれば、赤外データに基づいて色データのノイズ除去を行うことで、血流障害の危険度をより正確に算出することができる。 According to this aspect, the risk of blood flow disorder can be calculated more accurately by performing noise removal of color data based on infrared data.
　上記態様において、算出部は、複数の異なる期間のうち基準期間に測定した脈波データの確率分布と、複数の異なる期間のうち対象期間に測定した脈波データの確率分布とが等しいか否かを検定する検定統計量を算出し、第２判定部は、検定統計量に基づいて、生体に血流障害が発生しているか否かを判定してよい。 In the above aspect, the calculation unit, whether the probability distribution of the pulse wave data measured in the reference period of the plurality of different periods and the probability distribution of the pulse wave data measured in the target period of the plurality of different periods are equal or not The second determination unit may determine whether or not a blood flow disorder has occurred in the living body based on the test statistic by calculating a test statistic for testing.
　この態様によれば、基準期間の脈波データの確率分布と対象期間の脈波データの確率分布との差異に着目することで、脈波データの特徴を相対的に評価して、血流障害が発生している否かを判定することができる。 According to this aspect, by focusing on 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 to determine the blood flow disorder. Can be determined.
　本発明の他の態様に係る血流障害判定方法は、生体の脈波の時間変化を複数の異なる期間に測定した複数の脈波データを取得することと、複数の脈波データをそれぞれフーリエ変換して複数のスペクトルデータを生成することと、複数のスペクトルデータに含まれる１又は複数のピークを検出することと、所定の周波数区間毎に１又は複数のピークが検出された頻度を算出することと、頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定することと、１又は複数のピークがアーティファクトでないと判定された場合に、複数のスペクトルデータに基づいて、生体に血流障害が発生しているか否かを判定することと、を含む。 A blood flow disorder determination method according to another aspect of the present invention is to obtain 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 perform a Fourier transform on each of the plurality of pulse wave data. To generate a plurality of spectrum data, to detect one or a plurality of peaks included in the plurality of spectrum data, and to calculate a frequency at which one or a plurality of peaks are detected for each predetermined frequency section. And, based on the frequency, to determine whether or not one or more peaks are artifacts, and when it is determined that the one or more peaks are not artifacts, based on multiple spectral data, Determining whether a blood flow disorder has occurred.
　この態様によれば、スペクトルデータのパワーではなく、スペクトルデータに含まれる１又は複数のピークの頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定することで、脈波データに含まれるアーティファクトを減らして血流障害を判定することができる。 According to this aspect, the pulse wave data is determined by determining whether or not the one or more peaks are artifacts based on the frequency of the one or more peaks included in the spectrum data instead of the power of the spectrum data. Blood flow disorders can be determined by reducing the artifacts contained in.
　本発明の他の態様に係る血流障害判定プログラムは、血流障害判定装置に備えられたプロセッサを、生体の脈波の時間変化を複数の異なる期間に測定した複数の脈波データを取得する取得部、複数の脈波データをそれぞれフーリエ変換して複数のスペクトルデータを生成する生成部、複数のスペクトルデータに含まれる１又は複数のピークを検出する検出部、所定の周波数区間毎に１又は複数のピークが検出された頻度を算出する算出部、頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定する第１判定部、及び１又は複数のピークがアーティファクトでないと判定された場合に、複数のスペクトルデータに基づいて、生体に血流障害が発生しているか否かを判定する第２判定部、として機能させる。 A blood flow disorder determination program according to another aspect of the present invention uses a processor provided in a blood flow disorder determination device 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. An acquisition unit, a generation unit that performs Fourier transform on each of a plurality of pulse wave data to generate a plurality of spectrum data, a detection unit that detects one or a plurality of peaks included in the plurality of spectrum data, and one or a predetermined frequency section. A calculation unit that calculates the frequency at which a plurality of peaks are detected, a first determination unit that determines whether or not one or more peaks are artifacts based on the frequency, and a determination unit that determines that one or more peaks are not artifacts In this case, the second determination unit that determines whether or not a blood flow disorder has occurred in the living body is caused to function based on the plurality of spectrum data.
　この態様によれば、スペクトルデータのパワーではなく、スペクトルデータに含まれる１又は複数のピークの頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定することで、脈波データに含まれるアーティファクトを減らして血流障害を判定することができる。 According to this aspect, the pulse wave data is determined by determining whether or not the one or more peaks are artifacts based on the frequency of the one or more peaks included in the spectrum data instead of the power of the spectrum data. Blood flow disorders can be determined by reducing the artifacts contained in.
　本発明の他の態様に係る血流障害判定システムは、生体の脈波の時間変化を複数の異なる期間に測定し、複数の脈波データを出力する脈波センサと、複数の脈波データを用いて生体に血流障害が発生しているか否かを判定する血流障害判定装置とを備える血流障害判定システムであって、血流障害判定装置は、複数の脈波データをそれぞれフーリエ変換して複数のスペクトルデータを生成する生成部と、複数のスペクトルデータに含まれる１又は複数のピークを検出する検出部と、所定の周波数区間毎に１又は複数のピークが検出された頻度を算出する算出部と、頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定する第１判定部と、１又は複数のピークがアーティファクトでないと判定された場合に、複数のスペクトルデータに基づいて、生体に血流障害が発生しているか否かを判定する第２判定部と、を有する。 A 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. A blood flow disorder determination system comprising: a blood flow disorder determination device that determines whether or not a blood flow disorder has occurred in a living body, wherein the blood flow disorder determination device performs Fourier transform on a plurality of pulse wave data. Generating unit for generating a plurality of spectrum data, a detecting unit for detecting one or a plurality of peaks included in the plurality of spectrum data, and a frequency of detecting one or a plurality of peaks for each predetermined frequency section And a first determination unit that determines whether or not one or more peaks are artifacts based on the frequency, and a plurality of spectral data when it is determined that the one or more peaks are not artifacts And a second determination unit that determines whether or not a blood flow disorder has occurred in the living body.
　この態様によれば、スペクトルデータのパワーではなく、スペクトルデータに含まれる１又は複数のピークの頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定することで、脈波データに含まれるアーティファクトを減らして血流障害を判定することができる。 According to this aspect, the pulse wave data is determined by determining whether or not the one or more peaks are artifacts based on the frequency of the one or more peaks included in the spectrum data instead of the power of the spectrum data. Blood flow disorders can be determined by reducing the artifacts contained in.
　本発明によれば、脈波データに含まれるアーティファクトを減らして血流障害を判定することができる血流障害判定装置、血流障害判定方法、血流障害判定プログラム及び血流障害判定システムを提供することができる。 According to the present invention, there is provided 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 included in pulse wave data. can do.
本発明の実施形態に係る血流障害判定システムの概要を示す図である。It is a figure which shows the outline of the blood-flow disorder determination system which concerns on embodiment of this invention. 本実施形態に係る血流障害判定システムが備えるセンサの概要を示す図である。It is a figure which shows the outline|summary of the sensor with which the blood-flow disorder determination system which concerns on this embodiment is equipped. 本実施形態に係る血流障害判定装置の機能ブロックを示す図である。It is a figure which shows the functional block of the blood flow disorder determination apparatus which concerns on this embodiment. 本実施形態に係る血流障害判定装置の物理的構成を示す図である。It is a figure showing the physical composition of the blood flow disorder judgment device concerning this embodiment. 本実施形態に係る血流障害判定システムにより実行される第１処理のフローチャートである。It is a flow chart of the 1st processing performed by the blood flow disorder judging system concerning this embodiment. 本実施形態に係る血流障害判定装置により実行される第２処理のフローチャートである。It is a flow chart of the 2nd processing performed by the blood flow disorder judgment device concerning this embodiment. 本実施形態に係る血流障害判定装置により生成された複数のスペクトルデータ及び複数のスペクトルデータに含まれる１又は複数のピークを示す図である。It is a figure showing a plurality of spectrum data generated by a blood flow disorder judging device concerning this embodiment, and one or a plurality of peaks contained in a plurality of spectrum data. 本実施形態に係る血流障害判定装置により算出された１又は複数のピークの頻度の第１例を示す図である。It is a figure which shows the 1st example of the frequency of the 1 or several peak calculated by the blood-flow disorder determination apparatus which concerns on this embodiment. 本実施形態に係る血流障害判定装置により算出された１又は複数のピークの頻度の第２例を示す図である。It is a figure which shows the 2nd example of the frequency of the 1 or several peak calculated by the blood-flow disorder determination apparatus which concerns on this embodiment. 本実施形態に係る血流障害判定システムにより実行される第３処理のフローチャートである。It is a flow chart of the 3rd processing performed by the blood flow disorder judgment system concerning this embodiment. 本実施形態に係る血流障害判定装置により色データに基づき推定された危険度を示す図である。It is a figure which shows the risk degree estimated based on color data by the blood flow disorder determination apparatus which concerns on this embodiment. 本実施形態に係る血流障害判定システムにより実行される第４処理のフローチャートである。It is a flow chart of the 4th processing performed by the blood flow disorder judgment system concerning this embodiment. 本実施形態に係る血流障害判定装置により温度データに基づき推定された危険度を示す図である。It is a figure which shows the risk degree estimated based on the temperature data by the blood flow disorder determination apparatus which concerns on this embodiment. 本実施形態に係る血流障害判定システムにより実行される第５処理のフローチャートである。It is a flow chart of the 5th processing performed by the blood flow disorder judgment system concerning this embodiment. 本実施形態に係る血流障害判定装置により総合判定された危険度及びアーティファクトの検出率の第１例を示す図である。It is a figure which shows the 1st example of the risk and the detection rate of the artifact which were comprehensively judged by the blood-flow-disorder determining apparatus which concerns on this embodiment. 本実施形態に係る血流障害判定装置により総合判定された危険度及びアーティファクトの検出率の第２例を示す図である。It is a figure which shows the 2nd example of the detection rate of the risk degree and the artifact which were comprehensively determined by the blood-flow-disorder determining apparatus which concerns on this embodiment. 本実施形態に係る血流障害判定システムにより実行される第６処理のフローチャートである。It is a flow chart of the 6th processing performed by the blood flow disorder judgment system concerning this embodiment. 本実施形態に係る血流障害判定装置により算出されたＤ値及び血流障害検出タイミングを示す図である。It is a figure which shows the D value calculated by the blood-flow disorder determination apparatus and the blood-flow disorder detection timing which concern on this embodiment. 本実施形態に係る血流障害判定システムにより実行される第７処理のフローチャートである。It is a flow chart of the 7th processing performed by the blood flow disorder judging system concerning this embodiment. 本実施形態に係る血流障害判定システムにより測定され、ノイズ除去された色データ及びノイズ除去されていない色データを示す図である。It is a figure which shows the color data which was measured by the blood-flow obstruction determination system which concerns on this embodiment, and the noise-free color data and the noise-free color data. 本実施形態に係る血流障害判定装置により色データに基づき推定された危険度を示す図である。It is a figure which shows the risk degree estimated based on color data by the blood flow disorder determination apparatus which concerns on this embodiment.
　添付図面を参照して、本発明の実施形態について説明する。なお、各図において、同一の符号を付したものは、同一又は同様の構成を有する。 Embodiments of the present invention will be described with reference to the accompanying drawings. In addition, in each of the drawings, components denoted by the same reference numerals have the same or similar configurations.
　図１は、本発明の実施形態に係る血流障害判定システム１００の概要を示す図である。血流障害判定システム１００は、血流障害判定装置１０と、センサ２０と、トランスミッタ３０とを備える。 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.
　血流障害判定システム１００は、生体１に貼付されるフレキシブルなセンサ２０によって生体１の脈波の時間変化を複数の異なる期間に測定し、測定した脈波データを、トランスミッタ３０を介して血流障害判定装置１０に送信し、血流障害判定装置１０によって生体１に血流障害が生じているか否かを判定する。ここで、血流障害は、鬱血及び虚血を含む。本実施形態では、センサ２０とトランスミッタ３０は有線通信で接続され、トランスミッタ３０と血流障害判定装置１０は無線通信で接続されている。もっとも、通信方式は任意である。また、本実施形態では、血流障害判定装置１０は、タブレットコンピュータで構成されている。もっとも、血流障害判定装置１０は、ラップトップコンピュータで構成されてもよいし、他の形式のコンピュータで構成されてもよい。 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 measures the measured pulse wave data through the transmitter 30 to the blood flow. The information is transmitted to the failure determination device 10, and the blood flow failure determination device 10 determines whether or not a blood flow failure has occurred in the living body 1. Here, the blood flow disorder includes congestion and ischemia. In this embodiment, the sensor 20 and the transmitter 30 are connected by wired 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 configured by a laptop computer or another type of computer.
　また、血流障害判定システム１００は、センサ２０によって生体１の色の時間変化を測定したり、生体１の温度の時間変化を測定したりして、測定した色データ及び温度データを、トランスミッタ３０を介して血流障害判定装置１０に送信し、血流障害判定装置１０によって生体１に血流障害が生じているか否かを判定する。 In addition, the blood flow disorder determination system 100 measures the time change of the color of the living body 1 with the sensor 20 or the time change of the temperature of the living body 1, and transmits the measured color data and temperature data to the transmitter 30. To the blood flow disorder determination device 10, and the blood flow disorder determination device 10 determines whether or not a blood flow disorder has occurred in the living body 1.
　図２は、本実施形態に係る血流障害判定システム１００が備えるセンサ２０の概要を示す図である。センサ２０は、生体１の脈波の時間変化を複数の異なる期間に測定する脈波センサ２１と、生体１の色の時間変化を測定する色センサ２２と、生体１の温度の時間変化を測定する温度センサ２３と、を有する。なお、図２に示したメジャーの数値単位はｃｍである。 FIG. 2 is a diagram showing an outline of the sensor 20 included in the blood flow disorder determination system 100 according to the present embodiment. The sensor 20 includes a pulse wave sensor 21 that measures the time change of the pulse wave of the living body 1 in a plurality of different periods, a color sensor 22 that measures the time change of the color of the living body 1, and a time change of the temperature of the living body 1. And a temperature sensor 23 that operates. The numerical unit of the measure shown in FIG. 2 is cm.
　本実施形態に係るセンサ２０は、フレキシブル基板２５に４つの脈波センサ２１と、４つの色センサ２２と、４つの温度センサ２３とが実装されて構成されている。また、センサ２０は、１つの脈波センサ２１と、１つの色センサ２２と、１つの温度センサ２３とで１チャンネルの血流データを出力するように構成されている。本実施形態に係るセンサ２０は、合計４チャンネルの血流データを出力する。 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 blood flow data of one channel. The sensor 20 according to this embodiment outputs a total of four channels of blood flow data.
　フレキシブル基板２５は、体表面の変形に追随するように生体１に貼付される。脈波センサ２１は、例えば生体１に光を照射して、光の吸収量に基づき脈波を測定する光学式脈波センサで構成されてよい。色センサ２２は、例えば、赤外線を検出するフォトダイオードと、赤色の光を検出するフォトダイオードと、緑色の光を検出するフォトダイオードと、青色の光を検出するフォトダイオードとによって構成されてよい。温度センサ２３は、例えばサーミスタで構成されてよい。 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 configured by, 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 include, for example, a photodiode that detects infrared light, 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, for example, a thermistor.
　図３は、本実施形態に係る血流障害判定装置１０の機能ブロックを示す図である。血流障害判定装置１０は、取得部１１、生成部１２、検出部１３、算出部１４、第１判定部１５、第２判定部１６、決定部１７、第１推定部１８及び第２推定部１９を備える。 FIG. 3 is a diagram showing functional blocks 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.
　取得部１１は、生体１の脈波の時間変化を複数の異なる期間に測定した複数の脈波データを、トランスミッタ３０を介して脈波センサ２１から取得する。また、取得部１１は、生体１の色の時間変化を測定した色データを、トランスミッタ３０を介して色センサ２２から取得する。また、取得部１１は、生体１の温度の時間変化を測定した温度データを、トランスミッタ３０を介して温度センサ２３から取得する。 The acquisition unit 11 acquires, from the pulse wave sensor 21 via the transmitter 30, 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. In addition, 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.
　生成部１２は、複数の脈波データをそれぞれフーリエ変換して複数のスペクトルデータを生成する。生成部１２は、所定のサンプリングレートで測定された複数の脈波データに対して高速フーリエ変換を行うことで、複数のスペクトルデータを生成してよい。所定のサンプリングレートは、例えば１６Ｈｚであってよい。 The generation unit 12 performs Fourier transform on each of the plurality of pulse wave data to generate a plurality of spectrum data. The generation unit 12 may generate a plurality of spectrum data by performing a fast Fourier transform on a plurality of pulse wave data measured at a predetermined sampling rate. The predetermined sampling rate may be 16 Hz, for example.
　検出部１３は、複数のスペクトルデータに含まれる１又は複数のピークを検出する。検出部１３は、複数のスペクトルデータの極大点を１又は複数のピークとして検出してよい。 The detection unit 13 detects one or a plurality of peaks included in a plurality of spectrum data. The detection unit 13 may detect the maximum points of the plurality of spectrum data as one or a plurality of peaks.
　算出部１４は、所定の周波数区間毎に１又は複数のピークが検出された頻度を算出する。算出部１４は、例えば０．０７５Ｈｚ毎に１又は複数のピークが検出された頻度を算出してよい。 The calculation unit 14 calculates the frequency at which one or more peaks are detected for each predetermined frequency section. The calculator 14 may calculate the frequency at which one or a plurality of peaks are detected, for example, every 0.075 Hz.
　第１判定部１５は、１又は複数のピークが検出された頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定する。第１判定部１５による判定の詳細は、後に説明する。 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.
　第１判定部１５は、複数のスペクトルデータのパワーの和が第１閾値以上である場合に、１又は複数のピークがアーティファクトであるか否かを判定してよい。第１判定部１５は、複数のスペクトルデータのパワーの和が第１閾値以上でない場合には、１又は複数のピークがアーティファクトであるか否かを判定しなくてもよい。このように、スペクトルデータのパワーが十分に高い場合に１又は複数のピークがアーティファクトであるか否かを判定することとして、脈波データに含まれるアーティファクトを減らして血流障害を判定することができる。 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 spectrum data is equal to or more than the first threshold. When the sum of the powers of the plurality of spectrum data is not equal to or more than the first threshold, the first determination unit 15 does not have to determine whether one or more peaks are artifacts. As described above, when one or more peaks are artifacts when the power of the spectrum data is sufficiently high, it is possible to reduce the artifacts included in the pulse wave data and determine the blood flow disorder. it can.
　第２判定部１６は、１又は複数のピークがアーティファクトでないと判定された場合に、複数のスペクトルデータに基づいて、生体１に血流障害が発生しているか否かを判定する。第２判定部１６による判定の詳細は、後に説明する。 When the one or more peaks are determined not to be artifacts, the second determination unit 16 determines whether or not the blood flow disorder has occurred in the living body 1 based on the plurality of spectrum data. Details of the determination by the second determination unit 16 will be described later.
　本実施形態に係る血流障害判定装置１０によれば、スペクトルデータのパワーではなく、スペクトルデータに含まれる１又は複数のピークの頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定することで、脈波データに含まれるアーティファクトを減らして血流障害を判定することができる。 According to the blood flow disorder determination device 10 according to the present embodiment, whether or not one or a plurality of peaks are artifacts is determined based on the frequency of the one or a plurality of peaks included in the spectrum data, not the power of the spectrum data. By determining, the blood flow disorder can be determined by reducing the artifacts included in the pulse wave data.
　決定部１７は、色データ及び温度データの少なくともいずれかを含む時系列データを近似する所定の関数に含まれる１又は複数のパラメータの値を決定する。具体的には、時間をｔと表し、１又は複数のパラメータをＡ、Ａ０及びτと表すとき、所定の関数は、Ａ×ｅｘｐ（－ｔ／τ）＋Ａ０であってよい。このようにして、時系列データが指数的に変化する状況を所定の関数によって近似して、変化の大きさに応じた危険度を算出することができる。 The determining unit 17 determines the values of one or a plurality of parameters included in a predetermined function that approximates time series data including at least one of color data and 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 change can be calculated.
　第１推定部１８は、１又は複数のパラメータの値に基づいて、危険度を推定する。第１推定部１８による推定の詳細は、後に説明する。第２判定部１６は、推定された危険度に基づいて、生体１に血流障害が発生しているか否かを判定してよい。このようにして、生体１の色及び温度の少なくともいずれかの時間変化に基づいて、脈波とは異なる観点で血流障害の発生を判定することができる。 The first estimation unit 18 estimates the degree of risk based on the values of one or more 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 a blood flow disorder has occurred in the living body 1, based on the estimated risk. In this way, the occurrence of the blood flow disorder can be determined from the viewpoint different from the pulse wave, based on the temporal change of at least one of the color and the temperature of the living body 1.
　第２推定部１９は、所定期間に第１判定部１５及び第２判定部１６による判定を複数回行った場合における血流障害が発生していると判定された割合に基づいて、時間変化する脈波危険度を推定する。脈波危険度は、第１推定部１８により色データ及び温度データに基づき推定される危険度とは独立に推定されてよい。第２推定部１９によって、脈波データに含まれるアーティファクトを減らして、時間変化する脈波危険度を推定することができる。 The second estimation unit 19 changes with time based on the rate at which it is determined that the blood flow disorder has occurred when the determinations by the first determination unit 15 and the second determination unit 16 are performed multiple times 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 estimating unit 19 can reduce the artifacts included in the pulse wave data and estimate the time-varying pulse wave risk.
　図４は、本実施形態に係る血流障害判定装置１０の物理的構成を示す図である。血流障害判定装置１０は、プロセッサに相当するＣＰＵ（Central Processing Unit）１０ａと、記憶部に相当するＲＡＭ（Random Access Memory）１０ｂと、記憶部に相当するＲＯＭ（Read only Memory）１０ｃと、通信部１０ｄと、入力部１０ｅと、表示部１０ｆと、を有する。これらの各構成は、バスを介して相互にデータ送受信可能に接続される。なお、本例では血流障害判定装置１０が一台のコンピュータで構成される場合について説明するが、血流障害判定装置１０は、複数のコンピュータが組み合わされて実現されてもよい。また、図４で示す構成は一例であり、血流障害判定装置１０はこれら以外の構成を有してもよいし、これらの構成のうち一部を有さなくてもよい。 FIG. 4 is a diagram showing a physical configuration of the blood flow disorder determination 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, a ROM (Read Only Memory) 10c corresponding to a storage unit, and It has a section 10d, an input section 10e, and a display section 10f. These respective configurations are 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 determination device 10 may have a configuration other than these, or may not have some of these configurations.
　ＣＰＵ１０ａは、ＲＡＭ１０ｂ又はＲＯＭ１０ｃに記憶されたプログラムの実行に関する制御やデータの演算、加工を行う制御部である。ＣＰＵ１０ａは、脈波データ、色データ及び温度データに基づいて生体１の血流障害を判定するプログラム（血流障害判定プログラム）を実行する演算部である。ＣＰＵ１０ａは、入力部１０ｅや通信部１０ｄから種々のデータを受け取り、データの演算結果を表示部１０ｆに表示したり、ＲＡＭ１０ｂやＲＯＭ１０ｃに格納したりする。 The CPU 10a is a control unit that controls the execution of programs stored in the RAM 10b or the ROM 10c, calculates data, and processes the 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 and the ROM 10c.
　ＲＡＭ１０ｂは、記憶部のうちデータの書き換えが可能なものであり、例えば半導体記憶素子で構成されてよい。ＲＡＭ１０ｂは、ＣＰＵ１０ａが実行する血流障害判定プログラム、脈波データ、色データ及び温度データ等を記憶してよい。なお、これらは例示であって、ＲＡＭ１０ｂには、これら以外のデータが記憶されていてもよいし、これらの一部が記憶されていなくてもよい。 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 executed by the CPU 10a, pulse wave data, color data, temperature data, and the like. Note that these are merely examples, and data other than these may be stored in the RAM 10b, or some of these may not be stored.
　ＲＯＭ１０ｃは、記憶部のうちデータの読み出しが可能なものであり、例えば半導体記憶素子で構成されてよい。ＲＯＭ１０ｃは、例えば血流障害判定プログラムや、書き換えが行われないデータを記憶してよい。 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 and data that is not rewritten.
　通信部１０ｄは、血流障害判定装置１０を他の機器に接続するインターフェースである。通信部１０ｄは、インターネット等の通信ネットワークＮに接続されてよい。 The communication unit 10d is an interface that connects 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.
　入力部１０ｅは、ユーザからデータの入力を受け付けるものであり、例えば、キーボードやタッチパネルを含んでよい。 The input unit 10e receives data input from the user, and may include, for example, a keyboard or a touch panel.
　表示部１０ｆは、ＣＰＵ１０ａによる演算結果を視覚的に表示するものであり、例えば、ＬＣＤ（Liquid Crystal Display）により構成されてよい。表示部１０ｆは、脈波データ、色データ及びを表示したり、血流障害の危険度を表示したりしてよい。 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 the pulse wave data, the color data, and the risk of blood flow disorder.
　血流障害判定プログラムは、ＲＡＭ１０ｂやＲＯＭ１０ｃ等のコンピュータによって読み取り可能な記憶媒体に記憶されて提供されてもよいし、通信部１０ｄにより接続される通信ネットワークを介して提供されてもよい。血流障害判定装置１０では、ＣＰＵ１０ａが血流障害判定プログラムを実行することにより、図３を用いて説明した様々な動作が実現される。なお、これらの物理的な構成は例示であって、必ずしも独立した構成でなくてもよい。例えば、血流障害判定装置１０は、ＣＰＵ１０ａとＲＡＭ１０ｂやＲＯＭ１０ｃが一体化したＬＳＩ（Large-Scale Integration）を備えていてもよい。 The blood flow disorder determination program may be provided by being stored in a computer-readable storage medium such as the RAM 10b or the ROM 10c, 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, so that the various operations described with reference to FIG. 3 are realized. Note that these physical configurations are mere 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 and the ROM 10c are integrated.
　図５は、本実施形態に係る血流障害判定システム１００により実行される第１処理のフローチャートである。第１処理は、脈波データに基づいて脈波危険度を算出する処理である。 FIG. 5 is a flowchart of the first process executed by the blood flow disorder determination system 100 according to this embodiment. The first process is a process of calculating the pulse wave risk level based on the pulse wave data.
　はじめに、血流障害判定システム１００は、脈波センサ２１によって、所定のサンプリングレートで脈波データを測定する（Ｓ１０）。その後、血流障害判定装置１０は、一連の脈波データを所定の長さに分割する（Ｓ１１）。例えば、血流障害判定装置１０は、３分程度連続して測定された脈波データを、２１秒程度の長さの９つのデータに分割し、９つのデータの前半５秒程度をそれぞれ除去して、１６秒程度の９つの脈波データを作成してよい。１６秒程度の９つの脈波データは、２５６点のサンプリングデータを含んでよい。 First, the blood flow disorder determination system 100 measures 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 the series of pulse wave data into predetermined lengths (S11). For example, the blood flow disorder determination device 10 divides the pulse wave data continuously measured for about 3 minutes into 9 pieces of data having a length of about 21 seconds, and removes the first half of 5 seconds of each of the 9 pieces of data. Then, nine pulse wave data of about 16 seconds may be created. The nine pulse wave data of about 16 seconds may include sampling data of 256 points.
　血流障害判定装置１０は、複数の脈波データをフーリエ変換して複数のスペクトルデータを生成する（Ｓ１２）。具体的には、血流障害判定装置１０は、１６秒程度の長さの９つの脈波データを高速フーリエ変換して、９つのスペクトルデータを生成する。 The blood flow disorder determination device 10 Fourier transforms a plurality of pulse wave data to generate a plurality of spectrum data (S12). Specifically, the blood flow disorder determination device 10 performs fast Fourier transform on nine pulse wave data having a length of about 16 seconds to generate nine spectrum data.
　血流障害判定装置１０は、複数のスペクトルデータの総パワーを算出する（Ｓ１３）。ここで、総パワーは、スペクトルデータのパワーを所定の周波数範囲について積分した値であってよい。所定の周波数範囲は、例えば、０．５～２Ｈｚであってよい。なお、０．５～２Ｈｚは、３０～１２０ｂｐｍに相当する。血流障害判定装置１０は、９つのスペクトルデータそれぞれについて総パワーを算出してよい。 The blood flow disorder determination device 10 calculates the total power of a plurality of spectrum data (S13). Here, the total power may be a value obtained by integrating the power of the spectrum data in a predetermined frequency range. The predetermined frequency range may be, for example, 0.5-2 Hz. Note that 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 spectrum data.
　血流障害判定装置１０は、スペクトルデータの総パワーが第１閾値以上であるか否かを判定する（Ｓ１４）。総パワーが第１閾値以上である場合（Ｓ１４：ＹＥＳ）、すなわち脈波データの信号強度が十分に強い場合、血流障害判定装置１０は、アーティファクトを除外し、評価値を算出する処理を行う（Ｓ１５）。同処理については、次図を用いて詳細に説明する。血流障害判定装置１０は、脈波データをアーティファクトとして除外した場合（Ｓ１６：ＹＥＳ）、その後の処理を行わずに第１処理を終了する。一方、脈波データをアーティファクトとして除外せず、評価値を算出した場合（Ｓ１６：ＮＯ）、その後の処理を行う。 The blood flow disorder determination device 10 determines whether the total power of the spectrum data is equal to or higher 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 intensity of the pulse wave data is sufficiently strong, the blood flow disorder determination device 10 excludes the artifact and performs a process of calculating an evaluation value. (S15). The same process will be described in detail with reference to the next figure. When the pulse wave data is excluded 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.
　一方、総パワーが第１閾値以上でない場合（Ｓ１４：ＮＯ）、すなわち脈波データの信号強度が弱い場合、血流障害判定装置１０は、複数のスペクトルデータの総パワーの平均値を評価値として算出する（Ｓ１７）。血流障害判定装置１０は、複数のスペクトルデータのパワーの和が第１閾値未満である場合、複数のスペクトルデータのパワーの和の平均値によって評価値を算出してよい。例えば、スペクトルデータの総パワーをＰｔｏｔと表す場合、血流障害判定装置１０は、（１／（２Ｈｚ－０．５Ｈｚ））×（１６Ｈｚ／２５６）×Ｐｔｏｔによって評価値を算出してよい。 On the other hand, when the total power is not greater than or equal to 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 sets the average value of the total power of the plurality of spectrum data as the evaluation value. Calculate (S17). When the sum of the powers of the plurality of spectrum data is less than the first threshold, the blood flow disorder determination device 10 may calculate the evaluation value by the average value of the sum of the powers of the plurality of spectrum data. For example, when the total power of the spectrum data is represented by 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 . ..
　血流障害判定装置１０は、算出した評価値が第２閾値以下である場合（Ｓ１８：ＹＥＳ）、血流障害が発生していると判定する（Ｓ１９）。一方、算出した評価値が第２閾値以下でない場合（Ｓ１８：ＮＯ）、血流障害判定装置１０は、血流障害が発生していないと判定する（Ｓ２０）。 When the calculated evaluation value is equal to or less than the second threshold value (S18: YES), the blood flow disorder determination device 10 determines that a blood flow disorder has occurred (S19). On the other hand, when the calculated evaluation value is not less than or equal to the second threshold value (S18: NO), the blood flow disorder determination device 10 determines that the blood flow disorder has not occurred (S20).
　最後に、血流障害判定装置１０は、所定期間に第１判定部１５及び第２判定部１６による判定を複数回行った場合における血流障害が発生していると判定された割合に基づいて、脈波危険度を算出する（Ｓ２１）。例えば、血流障害判定装置１０は、３０分間の間に第２判定部１６によって血流障害が発生していると判定された回数を、第２判定部１６による総判定回数で割った値によって、脈波危険度を算出してよい。以上により、第１処理が終了する。 Finally, the blood flow obstruction determination device 10 is based on the ratio of the blood flow obstruction determined to have occurred when the first determination unit 15 and the second determination unit 16 make a plurality of determinations in a predetermined period. , Pulse wave risk is calculated (S21). For example, the blood flow disorder determination device 10 uses a value obtained by dividing the number of times that the blood flow disorder has been determined by the second determination unit 16 within 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 ends.
　図６は、本実施形態に係る血流障害判定装置１０により実行される第２処理のフローチャートである。第２処理は、スペクトルデータの総パワーが第１閾値以上の場合に、アーティファクトを除外した上で評価値を算出する処理である。同図では、図５に示す「アーティファクトを除外し、評価値を算出」する処理（Ｓ１５）の詳細を示している。 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 excluding the artifacts and calculating the evaluation value when the total power of the spectrum data is equal to or more than the first threshold value. The figure shows the details of the process (S15) of "excluding artifacts and calculating evaluation value" shown in FIG.
　はじめに、血流障害判定装置１０は、複数のスペクトルデータに含まれる１又は複数のピークを検出する（Ｓ１５１）。例えば、血流障害判定装置１０は、複数のスペクトルデータの極大点のうち、最大値の１／３以上の大きさをもつ極大点を１又は複数のピークとして検出してよい。 First, the blood flow disorder determination device 10 detects one or a plurality of peaks included in a plurality of spectrum data (S151). For example, the blood flow disorder determination device 10 may detect, as one or a plurality of peaks, a maximum point having a size of ⅓ or more of the maximum value among the maximum points of the plurality of spectrum data.
　血流障害判定装置１０は、所定の周波数区間毎に１又は複数のピークが検出された頻度を算出する（Ｓ１５２）。例えば、血流障害判定装置１０は、０．０７５Ｈｚの区間毎に１又は複数のピークが検出された頻度を算出してよい。 The blood flow disorder determination device 10 calculates the frequency at which one or more 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 0.075 Hz section.
　血流障害判定装置１０は、１又は複数のピークの頻度のうち、最高頻度が基準値以上であるか否かを判定する（Ｓ１５３）。例えば、９つのスペクトルデータそれぞれから１又は複数のピークを検出する場合、各周波数区間においてピークが検出される回数は０～９の値となる。この場合、基準値を６として、１又は複数のピークの最高頻度が６以上であるか否かを判定することとしてよい。 The blood flow disorder determination device 10 determines whether or not the highest frequency among the frequencies of one or a plurality of peaks is a reference value or more (S153). For example, when detecting one or a plurality of peaks from each of the nine spectrum data, the number of times the peak is detected in each frequency section is a value of 0-9. 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.
　１又は複数のピークの頻度のうち、最高頻度が基準値以上である場合（Ｓ１５３：ＹＥＳ）、血流障害判定装置１０は、最高頻度の周波数区間を特定する（Ｓ１５４）。そして、血流障害判定装置１０は、特定された周波数区間に関する複数のスペクトルデータのパワーの平均値を評価値として算出する（Ｓ１５５）。血流障害判定装置１０は、アーティファクトでないと判定された１又は複数のピークのうち最も頻度が高い周波数区間を特定し、当該周波数区間に関する複数のスペクトルデータのパワーの平均値を評価値として算出してよい。 When the highest frequency is equal to or higher than the reference value among the frequencies of one or a plurality of peaks (S153: YES), the blood flow disorder determination device 10 identifies the frequency section with the highest frequency (S154). Then, the blood flow disorder determination device 10 calculates the average value of the power of the plurality of spectrum data regarding the specified frequency section as the evaluation value (S155). The blood flow disorder determination device 10 identifies the frequency section having the highest frequency among the one or the plurality of peaks determined not to be artifacts, and calculates the average value of the powers of the plurality of spectrum data regarding the frequency section as the evaluation value. You may.
　一方、１又は複数のピークの頻度のうち、最高頻度が基準値以上でない場合（Ｓ１５３：ＮＯ）、血流障害判定装置１０は、ピークをアーティファクトと判定して除外する（Ｓ１５６）。このようにして、血流障害判定装置１０は、スペクトルデータのパワーではなく、スペクトルデータに含まれる１又は複数のピークの頻度に基づいて、１又は複数のピークがアーティファクトであるか否かを判定することで、脈波データに含まれるアーティファクトを減らすことができる。以上により、第２処理が終了する。 On the other hand, when the highest frequency is not higher than the reference value among the frequencies of one or a plurality of peaks (S153: NO), the blood flow disorder determination device 10 determines the peak as an artifact and excludes it (S156). In this way, the blood flow disorder determination device 10 determines whether or not one or a plurality of peaks are artifacts based on the frequency of the one or a plurality of peaks included in the spectrum data, not the power of the spectrum data. By doing so, the artifacts included in the pulse wave data can be reduced. With the above, the second processing ends.
　血流障害判定装置１０は、アーティファクトでないと判定された１又は複数のピークのうち最も頻度が高い周波数区間を特定し、当該周波数区間に関する複数のスペクトルデータのパワーの平均値が第２閾値以下である場合に、生体１に血流障害が発生していると判定する。これにより、脈波の周波数に対応するパワーをより正確に捉えることができ、血流障害の発生をより正確に判定することができる。 The blood flow disorder determination device 10 identifies a frequency section having the highest frequency among one or a plurality of peaks determined not to be artifacts, and an average value of powers of a plurality of spectrum data regarding the frequency section is equal to or less than a second threshold value. In some cases, it is determined that the blood flow disorder has occurred in the living body 1. Thereby, the power corresponding to the frequency of the pulse wave can be more accurately captured, and the occurrence of the blood flow disorder can be more accurately determined.
　また、血流障害判定装置１０は、複数のスペクトルデータのパワーの和が第１閾値未満である場合、複数のスペクトルデータのパワーの和の平均値が第２閾値以下である場合に、生体１に血流障害が発生していると判定する。このように、スペクトルデータのパワーが比較的低い場合に、複数のスペクトルデータのパワーの和の平均値が十分に高いか否かによって血流異常の発生を判定することで、血流障害の発生をより正確に判定することができる。 In addition, the blood flow disorder determination device 10 uses the living body 1 when the sum of the powers of the plurality of spectrum data is less than the first threshold and when the average value of the sum of the powers of the plurality of spectrum data is less than or equal to the second threshold. It is determined that there is blood flow disorder. In this way, when the power of spectrum data is relatively low, the occurrence of blood flow disorder is determined by determining the occurrence of blood flow abnormality depending on whether or not the average value of the sum of the powers of multiple spectrum data is sufficiently high. Can be determined more accurately.
　図７は、本実施形態に係る血流障害判定装置１０により生成された複数のスペクトルデータＳ１～Ｓ９及び複数のスペクトルデータＳ１～Ｓ９に含まれる１又は複数のピークＰ１～Ｐ９を示す図である。複数のスペクトルデータＳ１～Ｓ９は、それぞれＨｚの単位で横軸に周波数を示し、任意単位で縦軸にパワーを示している。また、１又は複数のピークＰ１～Ｐ９は、それぞれ任意単位で横軸に周波数を示し、任意単位で縦軸にパワーを示している。 FIG. 7 is a diagram showing a plurality of spectrum data S1 to S9 generated by the blood flow disorder determination device 10 according to the present embodiment and one or a plurality of peaks P1 to P9 included in the plurality of spectrum data S1 to S9. .. In each of the plurality of spectrum data S1 to S9, the horizontal axis represents frequency in units of Hz, and the vertical axis represents power in arbitrary units. Each of the one or a plurality of peaks P1 to P9 represents frequency in arbitrary units, and the vertical axis represents power in arbitrary units.
　複数のスペクトルデータＳ１～Ｓ９は、９つの脈波データをそれぞれ高速フーリエ変換して得られたデータである。また、１又は複数のピークＰ１～Ｐ９は、複数のスペクトルデータＳ１～Ｓ９の極大点のうち、最大値の１／３以上の大きさをもつ極大点を検出したデータである。 The plurality of spectrum data S1 to S9 are data obtained by fast Fourier transforming 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 ⅓ or more of the maximum value among the maximum points of the plurality of spectrum data S1 to S9.
　生体１の血流が正常である場合、スペクトルデータからは脈波周波数に対応する単一のピークが検出されることが多い。そして、複数のスペクトルデータからは、脈波周波数に対応する周波数区間についてピークが検出されることが多い。 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 spectrum data. Then, from a plurality of spectrum data, a peak is often detected in a frequency section corresponding to the pulse wave frequency.
　一方、生体１の血流が異常である場合、スペクトルデータからは複数のピークが検出されることが多い。そして、複数のスペクトルデータからは、複数の周波数区間についてピークが検出されることが多い。 On the other hand, when the blood flow of the living body 1 is abnormal, multiple peaks are often detected from the spectrum data. Then, peaks are often detected in a plurality of frequency sections from a plurality of spectrum data.
　図８は、本実施形態に係る血流障害判定装置１０により算出された１又は複数のピークの頻度の第１例を示す図である。同図では、血流が正常な場合に測定された９つの脈波データから９つのスペクトルデータを生成した場合に、９つのスペクトルデータに含まれる複数のピークの頻度を第１ヒストグラムＨ１として示している。 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 determination device 10 according to the present embodiment. In the figure, when nine spectrum data are generated from nine pulse wave data measured when the blood flow is normal, the frequencies of a plurality of peaks included in the nine spectrum data are shown as a first histogram H1. There is.
　第１ヒストグラムＨ１では、１．５１Ｈｚ～１．５９Ｈｚの区間が最高頻度の周波数区間ＰＷとなっている。ここで、最高頻度は６である。例えば基準値を６とする場合、同図に示す例は、ピークの最高頻度が基準値以上であるから、アーティファクトではないと判定される。この場合、９つのスペクトルデータに基づいて血流障害が発生しているか否かが判定される。 In the first histogram H1, the section between 1.51 Hz and 1.59 Hz is the highest frequency section PW. Here, the maximum frequency is 6. For example, when the reference value is 6, in the example shown in the figure, since the highest peak frequency is equal to or higher than the reference value, it is determined that the peak frequency is not an artifact. In this case, it is determined based on the nine spectrum data whether or not a blood flow disorder has occurred.
　図９は、本実施形態に係る血流障害判定装置１０により算出された１又は複数のピークの頻度の第２例を示す図である。同図では、血流障害が発生している場合に測定された９つの脈波データから９つのスペクトルデータを生成した場合に、９つのスペクトルデータに含まれる複数のピークの頻度を第２ヒストグラムＨ２として示している。 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 determination device 10 according to the present embodiment. In the figure, when nine spectrum data are generated from nine pulse wave data measured when a blood flow disorder is occurring, the frequency of a plurality of peaks included in the nine spectrum data is calculated as a second histogram H2. Is shown as.
　第２ヒストグラムＨ２では、０．５Ｈｚから２Ｈｚの周波数区間にピークの頻度が散在しており、０．９７Ｈｚ～１．０５Ｈｚの区間が最高頻度の周波数区間となっている。ここで、最高頻度は３である。例えば基準値を６とする場合、同図に示す例は、ピークの最高頻度が基準値未満であるから、アーティファクトであると判定されて除外される。この場合、９つのスペクトルデータは血流障害の判定には用いられず、棄却される。 In the second histogram H2, peak frequencies are scattered in the frequency range of 0.5 Hz to 2 Hz, and the frequency range of 0.97 Hz to 1.05 Hz is the highest frequency range. Here, the highest frequency is 3. For example, when the reference value is 6, in the example shown in the same figure, since the maximum frequency of peaks is less than the reference value, it is determined to be an artifact and excluded. In this case, the 9 pieces of spectral data are not used for determining the blood flow disorder and are discarded.
　図１０は、本実施形態に係る血流障害判定システム１００により実行される第３処理のフローチャートである。第３処理は、色データに基づき危険度を算出する処理である。 FIG. 10 is a flowchart of the third process executed by the blood flow disorder determination system 100 according to this embodiment. The third process is a process of calculating the risk degree based on the color data.
　はじめに、血流障害判定システム１００は、色センサ２２によって、所定のサンプリングレートで色データを測定する（Ｓ３０）。その後、血流障害判定装置１０は、色データを平滑化する（Ｓ３１）。例えば、血流障害判定装置１０は、連続して測定された３点のデータｙ１，ｙ２，ｙ３について、｜ｙ３－ｙ２｜＞｜ｙ２－ｙ１｜／２である場合、ｙ２をｙ１に置き換えることで、平滑化を行ってよい。また、血流障害判定装置１０は、例えば、連続して測定された５点のデータｙ１，ｙ２，ｙ３，ｙ４，ｙ５について、ｙ３を５点のデータの平均値で置き換えることで、平滑化を行ってよい。 First, the blood flow disorder determination system 100 uses the color sensor 22 to measure color data at a predetermined sampling rate (S30). After that, the blood flow disorder determination device 10 smoothes the color data (S31). For example, the blood flow obstruction determination device 10 replaces y2 with y1 when |y3-y2|>|y2-y1|/2 for three consecutively measured data y1, y2, y3. Then, smoothing may be performed. Further, the blood flow disorder determination device 10 performs smoothing 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, for example. You can go.
　血流障害判定装置１０は、色データから明度データに変換する（Ｓ３２）。例えば、血流障害判定装置１０は、ＲＧＢ－ＩＲ表色系の色データをＸＹＺ表色系の色データに変換して、Ｙ値を抽出することで明度データへの変換を行ってよい。 The blood flow disorder determination device 10 converts the color data into the lightness data (S32). For example, the blood flow disorder determination device 10 may convert the RGB-IR color system color data into the XYZ color system color data, and extract the Y value to convert the lightness data.
　血流障害判定装置１０は、明度データを近似する所定の関数のパラメータを決定する（Ｓ３３）。血流障害判定装置１０は、時間をｔと表し、１又は複数のパラメータをＡ、Ａ０及びτと表すとき、所定の関数としてＡ×ｅｘｐ（－ｔ／τ）＋Ａ０を用いて、明度データを近似するようにＡ、Ａ０及びτを決定してよい。所定の関数のフィッティングは、最小二乗法を、例えばLevenberg-Marquardt法により解くことで行ってよい。 The blood flow disorder determination device 10 determines the parameters of a predetermined function that approximates the brightness data (S33). The blood flow disorder determination device 10 uses A×exp(−t/τ)+A 0 as a predetermined function when the time is represented by t and one or more parameters are represented by A, A 0, and τ. A, A 0 and τ may be determined to approximate the data. The fitting of the predetermined function may be performed by solving the least squares method by, for example, the Levenberg-Marquardt method.
　血流障害判定装置１０は、決定係数と、パラメータの対数正規分布との積により指標を算出する（Ｓ３４）。血流障害判定装置１０は、０から１００までの値をとるGoodness of Fitting（ＧｏＦ）により決定係数を算出してよい。また、血流障害判定装置１０は、パラメータＡの対数正規分布を、ｌｏｇｎｏｒｍａｌ（Ａ）＝１／（√（２π）σＡ）ｅｘｐ（－（ｌｎ（Ａ）－μ）２／２σ２）により算出してよい。ここで、σ＝１／４として、μは、対数正規分布の最頻値ｅｘｐ（μ－σ２）が１０００となるように選択されてよい。 The blood flow disorder determination device 10 calculates an index by the product of the coefficient of determination and the lognormal distribution of parameters (S34). The blood flow disorder determination device 10 may calculate the coefficient of determination by Goodness of Fitting (GoF) that takes a value from 0 to 100. Further, the blood flow disorder determination apparatus 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 such that the mode exp(μ−σ 2 ) of the lognormal distribution is 1000.
　血流障害判定装置１０は、指標ｉｎｄ＝ＧｏＦ×ｌｏｇｎｏｒｍａｌ（Ａ）の絶対値が第３閾値以上であるか否かを判定する（Ｓ３５）。指標が第３閾値以上である場合（Ｓ３５：ＹＥＳ）、血流障害判定装置１０は、危険度の前回の値に指標を加算することで危険度を更新する（Ｓ３６）。一方、指標が第３閾値以上でない場合（Ｓ３５：ＮＯ）、危険度の前回の値と指標のいずれか大きい値により危険度を更新する（Ｓ３７）。 The blood flow disorder determination device 10 determines whether or not the absolute value of the index ind=GoF×lognormal(A) is greater than or equal to the third threshold value (S35). When the index is equal to or greater than the third threshold value (S35: YES), the blood flow disorder determination device 10 updates the risk level by adding the index to the previous value of the risk level (S36). On the other hand, if the index is not greater than or equal to the third threshold (S35: NO), the risk is updated with the larger value of the previous value of the risk and the index (S37).
　このように、血流障害判定装置１０の第１推定部１８は、１又は複数のパラメータの値及び１又は複数のパラメータの決定係数に基づいて指標を算出し、指標に基づいて危険度を更新することで、時間変化する危険度を推定してよい。これにより、所定の関数による近似のあてはまりの良さと、時間変化の大きさとに基づいて指標を算出し、時間変化する危険度を推定することができる。 As described above, the first estimation unit 18 of the blood flow disorder determination device 10 calculates the index based on the values of the one or more parameters and the coefficient of determination of the one or more parameters, and updates the risk level based on the index. By doing so, the time-varying risk may be estimated. Accordingly, it is possible to calculate the index based on the goodness of fit of the approximation by the predetermined function and the magnitude of the temporal change, and to estimate the risk of temporal change.
　また、第１推定部１８は、指標の絶対値が第３閾値以上である場合、危険度の前回の値に指標を加算することで危険度を更新し、指標の絶対値が第３閾値未満である場合、危険度の前回の値と指標のいずれか大きい値により危険度を更新してよい。これにより、時系列データ（明度データ）が減少する場合と増大する場合の両方について変化の大きさに応じた危険度を算出することができる。以上により、第３処理が終了する。 When the absolute value of the index is equal to or greater than the third threshold, the first estimation unit 18 updates the risk by adding the index to the previous value of the risk, and the absolute value of the index is less than the third threshold. If, then the risk may be updated with the larger value 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 change both when the time series data (brightness data) decreases and when the time series data increases. With the above, the third processing ends.
　図１１は、本実施形態に係る血流障害判定装置１０により色データに基づき推定された危険度を示す図である。同図では、横軸に経過日数を示し、縦軸に危険度を示している。同図では、４チャンネルの色センサ２２により測定された色データに基づき危険度を算出した結果を示している。 FIG. 11 is a diagram showing a risk degree estimated based on color data by the blood flow disorder determination device 10 according to the present embodiment. In the figure, the horizontal axis indicates the number of days elapsed, and the vertical axis indicates 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.
　血流障害判定装置１０は、４チャンネルの色センサ２２により測定された４つの色データに基づき、それぞれ危険度を推定する。図１１からは、３日目（Ｄａｙ３）の夜に実線で示した第１危険度Ｃ１と、一点鎖線で示した第２危険度Ｃ２とが急上昇していることが読み取れる。第１危険度Ｃ１は、最大値の１．０近くまで上昇し、その後１．０程度を維持している。また、第２危険度Ｃ２は、０．３程度まで上昇し、その後０．３程度を維持している。 The blood flow disorder determination device 10 estimates the degree of danger based on the four color data measured by the four-channel color sensor 22. From FIG. 11, it can be seen that the first risk level C1 indicated by the solid line and the second risk level C2 indicated by the alternate long and short dash line sharply increase on the night of the third day (Day 3). The first risk C1 rises to near the maximum value of 1.0 and then maintains about 1.0. Further, the second risk C2 rises to about 0.3 and then maintains about 0.3.
　図１１に示すデータによれば、少なくとも１チャンネルの色データについて、危険度が最大値近くで一定となっており、生体１に血流障害が生じている蓋然性が高いと判断できる。 According to the data shown in FIG. 11, the risk is constant near the maximum value for at least one channel of color data, and it can be determined that there is a high probability that blood flow disorder has occurred in the living body 1.
　図１２は、本実施形態に係る血流障害判定システム１００により実行される第４処理のフローチャートである。第４処理は、温度データに基づき危険度を算出する処理である。 FIG. 12 is a flowchart of the fourth process executed by the blood flow disorder determination system 100 according to this embodiment. The fourth process is a process of calculating the risk degree based on the temperature data.
　はじめに、血流障害判定システム１００は、温度センサ２３によって、所定のサンプリングレートで色データを測定する（Ｓ４０）。その後、血流障害判定装置１０は、温度データを平滑化する（Ｓ４１）。例えば、血流障害判定装置１０は、連続して測定された３点のデータｙ１，ｙ２，ｙ３について、｜ｙ３－ｙ２｜＞｜ｙ２－ｙ１｜／２である場合、ｙ２をｙ１に置き換えることで、平滑化を行ってよい。また、血流障害判定装置１０は、例えば、連続して測定された５点のデータｙ１，ｙ２，ｙ３，ｙ４，ｙ５について、ｙ３を５点のデータの平均値で置き換えることで、平滑化を行ってよい。 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 obstruction determination device 10 replaces y2 with y1 when |y3-y2|>|y2-y1|/2 for three consecutively measured data y1, y2, y3. Then, smoothing may be performed. Further, the blood flow disorder determination device 10 performs smoothing by replacing y3 with the average value of the data of 5 points, for example, for the data y1, y2, y3, y4, y5 of 5 points measured continuously. You can go.
　血流障害判定装置１０は、温度データを近似する所定の関数のパラメータを決定する（Ｓ４２）。血流障害判定装置１０は、時間をｔと表し、１又は複数のパラメータをＡ、Ａ０及びτと表すとき、所定の関数としてＡ×ｅｘｐ（－ｔ／τ）＋Ａ０を用いて、温度データを近似するようにＡ、Ａ０及びτを決定してよい。所定の関数のフィッティングは、最小二乗法を、例えばLevenberg-Marquardt法により解くことで行ってよい。 The blood flow disorder determination device 10 determines a parameter of a predetermined function that approximates the temperature data (S42). The blood flow disorder determination apparatus 10 uses A×exp(−t/τ)+A 0 as a predetermined function when the time is represented by t and one or more parameters are represented by A, A 0, and τ. A, A 0 and τ may be determined to approximate the data. The fitting of the predetermined function may be performed by solving the least squares method by, for example, the Levenberg-Marquardt method.
　血流障害判定装置１０は、決定係数と、パラメータの対数正規分布との積により指標を算出する（Ｓ４３）。血流障害判定装置１０は、０から１００までの値をとるGoodness of Fitting（ＧｏＦ）により決定係数を算出してよい。また、血流障害判定装置１０は、パラメータＡの対数正規分布を、ｌｏｇｎｏｒｍａｌ（Ａ）＝１／（√（２π）σＡ）ｅｘｐ（－（ｌｎ（Ａ）－μ）２／２σ２）により算出してよい。ここで、σ＝１／４として、μは、対数正規分布の最頻値ｅｘｐ（μ－σ２）が２となるように選択されてよい。 The blood flow disorder determination device 10 calculates an index by the product of the coefficient of determination and the lognormal distribution of parameters (S43). The blood flow disorder determination device 10 may calculate the coefficient of determination by Goodness of Fitting (GoF) that takes a value from 0 to 100. Further, the blood flow disorder determination apparatus 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.
　血流障害判定装置１０は、危険度の前回の値に指標ｉｎｄ＝ＧｏＦ×ｌｏｇｎｏｒｍａｌ（Ａ）を加算することで危険度を更新する（Ｓ４４）。以上により、第４処理が終了する。 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 processing ends.
　図１３は、本実施形態に係る血流障害判定装置１０により温度データに基づき推定された危険度を示す図である。同図では、横軸に経過日数を示し、縦軸に危険度を示している。同図では、４チャンネルの温度センサ２３により測定された温度データに基づき危険度を算出した結果を示している。 FIG. 13 is a diagram showing a risk degree estimated based on temperature data by the blood flow disorder determination device 10 according to the present embodiment. In the figure, the horizontal axis indicates the number of days elapsed, and the vertical axis indicates the degree of risk. The figure shows the result of calculating the degree of danger based on the temperature data measured by the four-channel temperature sensor 23.
　血流障害判定装置１０は、４チャンネルの温度センサ２３により測定された４つの温度データに基づき、それぞれ危険度を推定する。図１３からは、６日目（Ｄａｙ６）の昼頃に実線で示した第１危険度Ｔ１が１．０近くまで上昇し、その後０に戻っていることが読み取れる。また、４日目（Ｄａｙ４）の午前に一点鎖線で示した第２危険度Ｔ２が０．４程度まで上昇し、その後０に戻っていることが読み取れる。また、７日目（Ｄａｙ７）の深夜に二点鎖線で示した第３危険度Ｔ３が０．４程度まで上昇し、その後０に戻っていることが読み取れる。また、１日目（Ｄａｙ１）の深夜に破線で示した第４危険度Ｔ４が０．１程度まで上昇し、その後０に戻っていることが読み取れる。 The blood flow disorder determination device 10 estimates the degree of danger based on the four temperature data measured by the four-channel temperature sensor 23. From FIG. 13, it can be seen that the first risk level T1 shown by the solid line rises to near 1.0 at noon on the sixth day (Day 6) and then returns to zero. In addition, it can be seen that the second risk level T2 indicated by the alternate long and short dash line in the morning of the fourth day (Day 4) has risen to about 0.4 and then returned to zero. Further, it can be seen that the third risk level T3 indicated by the chain double-dashed line increased to about 0.4 at midnight on the seventh day (Day 7) and then returned to 0. It can also be seen that the fourth risk level T4 indicated by the broken line rises to about 0.1 at midnight on the first day (Day 1), and then returns to zero.
　図１３に示すデータによれば、４チャンネルの色データについて、一時的に危険度が最大値近くまで上昇しているものの、その後危険度は０に低下しており、生体１に血流障害が生じている蓋然性は低いと判断できる。 According to the data shown in FIG. 13, regarding the 4-channel color data, although the risk temporarily rises to a value close to the maximum value, the risk subsequently decreases to 0, and blood flow disorder in the living body 1 occurs. It can be judged that the probability of occurrence is low.
　図１４は、本実施形態に係る血流障害判定システム１００により実行される第５処理のフローチャートである。第５処理は、生体１に血流障害が生じているか否かを総合判定する処理である。 FIG. 14 is a flowchart of the fifth process executed by the blood flow disorder determination system 100 according to this embodiment. The fifth process is a process for comprehensively determining whether or not a blood flow disorder has occurred in the living body 1.
　はじめに、血流障害判定システム１００は、図５に示す第１処理を実行し、脈波の危険度を算出する（Ｓ５０）。また、血流障害判定システム１００は、図１０に示す第３処理を実行し、色の危険度を算出する（Ｓ５１）。さらに、血流障害判定システム１００は、図１２に示す第４処理を実行し、温度の危険度を算出する（Ｓ５１）。なお、これらの処理の実行順序は任意である。 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). Further, the blood flow disorder determination system 100 executes the third processing shown in FIG. 10 to calculate the color risk (S51). Further, the blood flow disorder determination system 100 executes the fourth process shown in FIG. 12 to calculate the temperature risk (S51). The order of executing these processes is arbitrary.
　血流障害判定システム１００は、脈波データがアーティファクトとして除外された場合（Ｓ５３：ＹＥＳ）、アーティファクトが検出されたことを出力する（Ｓ５４）。出力は、例えば血流障害判定装置１０の表示部１０ｆにメッセージを表示することで行ってよい。なお、アーティファクトが検出されたことの出力は省略してもよい。 When the pulse wave data is excluded as an artifact (S53: YES), the blood flow disorder determination system 100 outputs that the artifact is detected (S54). The output may be performed by displaying a message on the display unit 10f of the blood flow disorder determination device 10, for example. The output indicating that the artifact is detected may be omitted.
　一方、脈波データがアーティファクトとして除外されなかった場合（Ｓ５３：ＮＯ）、血流障害判定システム１００は、脈波の危険度、色の危険度及び温度の危険度のいずれかが第４閾値以上であるか判定する（Ｓ５５）。いずれの危険度も第４閾値以上でない場合（Ｓ５５：ＮＯ）、血流障害判定システム１００は、血流障害のリスクが低いことを出力する（Ｓ５６）。一方、いずれかの危険度が第４閾値以上である場合（Ｓ５５：ＹＥＳ）、血流障害が発生していることを出力する（Ｓ５７）。以上により、第５処理が終了する。 On the other hand, if the pulse wave data is not excluded as an artifact (S53: NO), the blood flow disorder determination system 100 determines that any one of the pulse wave risk, the color risk, and the temperature risk is equal to or higher than the fourth threshold value. Is determined (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, if any of the risks is equal to or higher than the fourth threshold value (S55: YES), the fact that the blood flow disorder has occurred is output (S57). With the above, the fifth process ends.
　血流障害判定装置１０の第２判定部１６は、スペクトルデータの１又は複数のピークがアーティファクトでないと判定された場合に、複数の脈波データを用いて生体１に血流障害が発生しているか否かを判定した結果と、色データ及び温度データの少なくともいずれかを用いて生体１に血流障害が発生しているか否かを判定した結果とに基づいて、生体１に血流障害が生じているか否かを総合判定してよい。これにより、生体１の脈波データに基づいてアーティファクトを減らして、脈波、色及び温度に基づいて、総合的に血流障害が生じているか否かを判定することができる。 When the one or more peaks of the spectrum data are determined not to be artifacts, the second determination unit 16 of the blood flow disorder determination device 10 uses the plurality of pulse wave data to cause the blood flow disorder in the living body 1. 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, there is a blood flow disorder in the living body 1. A comprehensive determination may be made as to 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 to comprehensively determine whether the blood flow disorder has occurred based on the pulse wave, the color, and the temperature.
　また、血流障害判定装置１０の第２判定部１６は、脈波危険度、色の危険度及び温度の危険度の少なくともいずれかが第４閾値以上である場合に、生体１に血流障害が生じていると総合判定してよい。このように、生体１の脈波、色及び温度の少なくともいずれかについて血流障害の危険性が高い場合に血流障害が生じていると総合判定することで、血流障害の見逃しを減らすことができる。 In addition, the second determination unit 16 of the blood flow disorder determination device 10 causes the 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 the fourth threshold value or more. May be comprehensively determined as occurring. In this way, by comprehensively determining that a blood flow disorder has occurred when at least one of the pulse wave, color, and temperature of the living body 1 has a high risk of blood flow disorder, it is possible to reduce the oversight of the blood flow disorder. You can
　なお、血流障害判定装置１０の第２判定部１６は、色データを用いて算出された危険度と、温度データを用いて算出された危険度とに基づいて、生体１の血流障害の種類を判定してもよい。血流障害として鬱血が生じている場合、色データを用いて算出された危険度は上昇することが期待されるが、鬱血では生体１の温度が低下しないため、温度データを用いて算出された危険度は上昇しないことが通常である。一方、血流障害として虚血が生じている場合、色データを用いて算出された危険度が上昇し、生体１の温度が低下することで温度データを用いて算出された危険度も上昇することが期待される。このように、色の危険度と温度の危険度との組み合わせによって、鬱血及び虚血のいずれの血流障害が発生しているかを見分けることができる。 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 degree calculated using the color data and the risk degree calculated using the temperature data. The type may be determined. When congestion occurs as a blood flow disorder, the risk calculated using the color data is expected to increase, but since the temperature of the living body 1 does not decrease with congestion, it was calculated using the temperature data. The risk is usually not increased. 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 the risk calculated using the temperature data also increases. It is expected. In this way, it is possible to discriminate whether the blood flow disorder such as congestion or ischemia is occurring, based on the combination of the risk of color and the risk of temperature.
　図１５は、本実施形態に係る血流障害判定装置１０により総合判定された危険度及びアーティファクトの検出率の第１例を示す図である。本例では、総合判定された危険度Ｒ１と、アーティファクト検出率Ａ１とを示している。総合判定された危険度Ｒ１及びアーティファクト検出率Ａ１の横軸は時間であり、縦軸は０～１の値である。同図では、実線、一点鎖線、二点鎖線及び破線によって、４チャンネルの脈波データに関するアーティファクト検出率Ａ１を示している。 FIG. 15 is a diagram showing a first example of the degree of risk and the detection rate of artifacts comprehensively determined by the blood flow disorder determination device 10 according to the present embodiment. In this example, the comprehensively determined risk R1 and the artifact detection rate A1 are shown. The horizontal axis of the comprehensively determined risk R1 and the artifact detection rate A1 is time, and the vertical axis thereof is a value of 0 to 1. In the same figure, the solid line, the alternate long and short dash line, the alternate long and two short dashes line and the broken line indicate the artifact detection rate A1 regarding the pulse wave data of four channels.
　本例では、総合判定された危険度Ｒ１は、測定開始時点以外のすべての時間にわたって０である。また、アーティファクト検出率Ａ１は、４チャンネルの脈波データについて頻繁に上昇している。このように、本実施形態に係る血流障害判定装置１０によれば、脈波データに含まれるアーティファクトを減らして血流障害を判定することができる。 In this example, the comprehensively judged risk R1 is 0 over all the time except the measurement start time. Further, the artifact detection rate A1 frequently increases for the pulse wave data of four channels. As described above, according to the blood flow disorder determination device 10 according to the present embodiment, the blood flow disorder can be determined by reducing the artifacts included in the pulse wave data.
　図１６は、本実施形態に係る血流障害判定装置１０により総合判定された危険度及びアーティファクトの検出率の第２例を示す図である。本例では、総合判定された危険度Ｒ２と、アーティファクト検出率Ａ２とを示している。総合判定された危険度Ｒ２及びアーティファクト検出率Ａ２の横軸は時間であり、縦軸は０～１の値である。同図では、実線、一点鎖線、二点鎖線及び破線によって、４チャンネルの総合判定された危険度Ｒ２及び４チャンネルの脈波データに関するアーティファクト検出率Ａ２を示している。 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 R2 and the artifact detection rate A2 are shown. The abscissa of the comprehensively determined risk R2 and the artifact detection rate A2 is time, and the ordinate is a value of 0 to 1. In the same figure, the solid line, the alternate long and short dash line, the alternate long and two short dashes line, and the broken line indicate the risk R2 comprehensively determined for four channels and the artifact detection rate A2 for pulse wave data for four channels.
　本例では、総合判定された危険度Ｒ２は、すべての時間にわたってほとんど１に近い値となっている。そのため、本例では、生体１に血流障害が生じている蓋然性が高いと考えられる。また、アーティファクト検出率Ａ２は、すべての時間にわたって０．５～０．７程度の高い値となっている。このように、本実施形態に係る血流障害判定装置１０によれば、脈波データに含まれるアーティファクトを減らして、脈波、色及び温度によって血流障害が発生しているか否かを総合的に判定することができる。 In this example, the comprehensively judged risk level R2 is close to 1 over all time. Therefore, in this example, it is considered highly probable that the blood flow disorder has occurred in the living body 1. Further, 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 determination device 10 according to the present embodiment, it is possible to reduce the artifacts included in the pulse wave data and comprehensively determine whether the blood flow disorder is caused by the pulse wave, the color, and the temperature. Can be determined.
　図１７は、本実施形態に係る血流障害判定システムにより実行される第６処理のフローチャートである。第６処理は、脈波データに基づいて生体１に血流障害が発生しているか否かを判定する処理である。 FIG. 17 is a flowchart of the sixth process executed by the blood flow disorder determination system according to this 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.
　血流障害判定装置１０の算出部１４は、複数の異なる期間のうち基準期間に測定した脈波データの確率分布と、複数の異なる期間のうち対象期間に測定した脈波データの確率分布とが等しいか否かを検定する検定統計量を算出する。ここで、基準期間は、脈波データの測定を開始した時点から所定期間経過するまでであってよく、対象期間は、現時点から所定期間遡った時点までであってよい。これまでの研究において得られたデータから、脈波データの確率分布をガンマ分布によって近似できることが分かっている。算出部１４は、基準期間に測定した脈波データの平均及び分散に基づいて、基準期間に測定した脈波データのガンマ分布を推定し、対象期間に測定した脈波データの平均及び分散に基づいて、対象期間に測定した脈波データのガンマ分布を推定してよい。また、算出部１４は、基準期間に測定した脈波データのガンマ分布と、対象期間に測定した脈波データのガンマ分布とが等しいか否かを検定する検定統計量としてＤ値を算出してよい。 The calculation unit 14 of the blood flow disorder determination device 10 determines that the probability distribution of the pulse wave data measured in the reference period of the plurality of different periods and the probability distribution of the pulse wave data measured in the target period of the plurality of different periods. Compute a test statistic that tests for equality. Here, the reference period may be from a time point when the measurement of the pulse wave data is started until a predetermined time period elapses, and the target time period may be from a current time point up to a predetermined time period. From the data obtained in 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 based on the average and the 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. The calculating unit 14 also calculates a 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.
　血流障害判定装置１０の第２判定部１６は、検定統計量に基づいて、生体１に血流障害が発生しているか否かを判定する。第２判定部１６は、Ｄ値が第５閾値以上である場合に生体１に血流障害が発生していると判定し、Ｄ値が第５閾値未満である場合に生体１に血流障害が発生していないと判定してよい。 The second determination unit 16 of the blood flow disorder determination device 10 determines whether or not a blood flow disorder has occurred in the living body 1, based on the test statistic. The second determination unit 16 determines that the blood flow disorder is occurring in the living body 1 when the D value is equal to or greater than the fifth threshold value, and determines the blood flow disorder in the living body 1 when the D value is less than the fifth threshold value. May be determined not to occur.
　はじめに、血流障害判定システム１００は、脈波センサ２１によって、所定のサンプリングレートで脈波データを測定する（Ｓ６０）。その後、血流障害判定装置１０は、基準期間を定め、基準区間の平均及び分散を算出し、基準期間に測定した脈波データの確率分布を推定する（Ｓ６１）。また、血流障害判定装置１０は、対象区間の平均及び分散を算出し、対象期間に測定した脈波データの確率分布を推定する（Ｓ６２）。そして、血流障害判定装置１０は、両確率分布が等しいか否かを検定する検定統計量としてＤ値を算出する（Ｓ６３）。 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 defines the 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). The blood flow disorder determination device 10 also 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).
　Ｄ値が第５閾値以上である場合（Ｓ６４：ＹＥＳ）、血流障害判定装置１０は、生体１に血流障害が発生していると判定する（Ｓ６５）。一方、Ｄ値が第５閾値未満である場合（Ｓ６４：ＮＯ）、血流障害判定装置１０は、生体１に血流障害が発生していないと判定する（Ｓ６６）。 When the D value is greater than or equal to the fifth threshold value (S64: YES), the blood flow disorder determination 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 determination device 10 determines that the blood flow disorder has not occurred in the living body 1 (S66).
　図１８は、本実施形態に係る血流障害判定装置１０により算出されたＤ値及び血流障害検出タイミングを示す図である。同図では、横軸に時間を示し、上側の縦軸に脈波データの大きさ（Pulse Power）を無次元で示し、下側の縦軸にＤ値の大きさを無次元で示している。 FIG. 18 is a diagram showing the D value calculated by the blood flow disorder determination device 10 according to the present embodiment and the 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. ..
　脈波データのグラフＰＰでは、４チャンネルの脈波データを実線、一点鎖線、二点鎖線及び破線で示している。血流障害判定装置１０は、最新の脈波データを含む対象期間の脈波データの確率分布と、測定開始時の脈波データを含む基準期間の脈波データの確率分布とを推定し、それらの確率分布が等しいか否かを検定するＤ値を算出する。Ｄ値のグラフＤは、ある時点で第５閾値Ｔｈを有意に超えており、血流障害判定装置１０は、第１時点ｄ１において、生体１に血流障害が発生していると判定した。 In the pulse wave data graph PP, the 4-channel pulse wave data 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 The D value for testing whether or not the probability distributions of are equal is calculated. The graph D of the D value significantly exceeds the fifth threshold Th at a certain time point, and the blood flow disorder determination device 10 determines that the blood flow disorder has occurred in the living body 1 at the first time point d1.
　一方、医師は、定期的に患者を回診して血流障害が発生しているか否かを判断する。本例の場合、医師は、第２時点ｄ２において、生体１に血流障害が発生していると判断した。 On the other hand, the doctor regularly makes a round of the patient to determine whether or not a blood flow disorder has occurred. In the case of this example, the doctor determines that the blood flow disorder has occurred in the living body 1 at the second time point d2.
　このように、医師による判断は正確ではあるものの、常時行えるものではなく、血流障害が発生してから発見されるまでにある程度時間が経過することがある。この点、本実施形態に係る血流障害判定装置１０によれば、連続的な監視が可能となり、血流障害の発生をいち早く発見することができる。本実施形態に係る血流障害判定装置１０によれば、基準期間の脈波データの確率分布と対象期間の脈波データの確率分布との差異に着目することで、脈波データの特徴を相対的に評価して、血流障害が発生している否かを判定することができる。 Thus, although the doctor's judgment is accurate, it cannot always be done, and some time may elapse after the blood flow disorder is detected until it is detected. In this respect, the blood flow obstruction determination device 10 according to the present embodiment enables continuous monitoring, and the occurrence of a blood flow obstruction can be detected promptly. According to the blood flow disorder determination device 10 according to the present embodiment, the characteristics of the pulse wave data are relatively determined by focusing on the difference between the probability distribution of the pulse wave data of the reference period and the probability distribution of the pulse wave data of the target period. It is possible to determine whether or not a blood flow disorder has occurred by performing a physical evaluation.
　なお、脈波データの確率分布の変化に基づいて血流障害の発生を判定する場合、センサ２０は、血流障害が懸念される箇所に貼付されてよいが、血流障害が懸念される箇所と正常な箇所にまたがるように貼付されてもよい。センサ２０を血流障害が懸念される箇所と正常な箇所にまたがるように貼付する場合、少なくとも１チャネルの脈波センサ２１を血流障害が懸念される箇所に貼付し、他の少なくとも１チャネルの脈波センサ２１を正常な箇所に貼付するようにする。この場合、血流障害判定装置１０は、正常な箇所に対応するチャネルの脈波データを基準として、正常な箇所に対応するチャネルの脈波データの確率分布と、血流障害が懸念される箇所に対応するチャネルの脈波データの確率分布とが等しいか否かを検定する検定統計量を算出してよい。また、センサ２０を複数用意して、複数のチャネルを含む第１センサを正常な箇所に貼付し、複数のチャネルを含む他のセンサを血流障害が懸念される箇所に貼付してもよい。その場合、血流障害判定装置１０は、正常な箇所に貼付した第１センサの脈波データの確率分布と、血流障害が懸念される箇所に貼付した第２センサの脈波データの確率分布とが等しいか否かを検定する検定統計量を算出してよい。 When determining the occurrence of a 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 the blood flow disorder is concerned, but a place where the blood flow disorder is concerned. It may be attached so as to straddle a normal place. When the sensor 20 is attached so as to straddle a place where blood flow disorder is concerned and a normal place, the pulse wave sensor 21 of at least one channel is attached to a place where blood flow disorder is concerned, and at least another channel is used. 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 place as a reference, and the probability distribution of the pulse wave data of the channel corresponding to the normal place, and the place where the blood flow disorder is concerned. A test statistic for testing whether or not the probability distribution of the pulse wave data of the channel corresponding to is equal may be calculated. Alternatively, a plurality of sensors 20 may be prepared, a first sensor including a plurality of channels may be attached to a normal place, and another sensor including a plurality of channels may be attached to a place where blood flow disorder is concerned. In that case, the blood flow disorder determination device 10 uses the probability distribution of the pulse wave data of the first sensor attached to a normal place and the probability distribution of the pulse wave data of the second sensor attached to a place where blood flow disorder is concerned. A test statistic for testing whether and are equal may be calculated.
　図１９は、本実施形態に係る血流障害判定システム１００により実行される第７処理のフローチャートである。第６処理は、赤外データに基づくノイズ除去を行い、色データに基づき危険度を算出する処理である。血流障害判定システム１００の色センサ２２で測定される色データは、赤外データを含み、決定部１７は、赤外データに基づいてノイズ除去された時系列データを近似する所定の関数に含まれる１又は複数のパラメータの値を決定する。ここで、赤外データに基づくノイズ除去は、例えば、赤外データの大きさが第６閾値以上である場合に、その時点の色データをノイズとして除去することにより行われてよい。 FIG. 19 is a flowchart of the seventh process executed by the blood flow disorder determination system 100 according to this embodiment. The sixth process is a process of removing noise based on infrared data and calculating a risk level 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 includes the noise-removed time-series data in a predetermined function that approximates the infrared data. The value of one or more parameters to be set is determined. Here, the noise removal based on the infrared data may be performed, for example, by removing the color data at that time as noise when the size of the infrared data is equal to or larger than the sixth threshold value.
　はじめに、血流障害判定システム１００は、色センサ２２によって、所定のサンプリングレートで色データを測定する（Ｓ７０）。血流障害判定装置１０は、赤外データが第６閾値以上である区間の色データを除去することで、色データに関するノイズ除去を行う（Ｓ７１）。その後、血流障害判定装置１０は、色データを平滑化する（Ｓ７２）。平滑化は、第３処理と同様に行われてよい。 First, the blood flow disorder determination system 100 uses the color sensor 22 to measure color data at a predetermined sampling rate (S70). The blood flow disorder determination device 10 removes the color data in the section in which the infrared data is equal to or greater than the sixth threshold value to remove noise related to the color data (S71). Thereafter, the blood flow disorder determination device 10 smoothes the color data (S72). The smoothing may be performed similarly to the third processing.
　血流障害判定装置１０は、色データから明度データに変換する（Ｓ７３）。色データから明度データへの変換は、第３処理と同様に行われてよい。 The blood flow disorder determination device 10 converts color data into lightness data (S73). The conversion from color data to lightness data may be performed in the same manner as the third process.
　血流障害判定装置１０は、明度データを近似する所定の関数のパラメータを決定する（Ｓ７４）。明度データを近似する所定の関数のパラメータは、第３処理と同様に決定されてよい。 The blood flow disorder determination device 10 determines a parameter 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.
　血流障害判定装置１０は、決定係数と、パラメータの対数正規分布との積により指標を算出する（Ｓ７５）。指標は、第３処理と同様に算出されてよい。 The blood flow disorder determination device 10 calculates an index by the product of the coefficient of determination and the lognormal distribution of parameters (S75). The index may be calculated similarly to the third process.
　血流障害判定装置１０は、指標の絶対値が第３閾値以上であるか否かを判定する（Ｓ７６）。指標が第３閾値以上である場合（Ｓ７６：ＹＥＳ）、血流障害判定装置１０は、危険度の前回の値に指標を加算することで危険度を更新する（Ｓ７７）。一方、指標が第３閾値以上でない場合（Ｓ７６：ＮＯ）、危険度の前回の値と指標のいずれか大きい値により危険度を更新する（Ｓ７８）。 The blood flow disorder determination device 10 determines whether or not the absolute value of the index is greater than or equal to the third threshold value (S76). When the index is equal to or greater than the third threshold value (S76: YES), the blood flow disorder determination 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 greater than or equal to the third threshold value (S76: NO), the risk is updated with the larger value of the previous risk and the index (S78).
　赤外データに基づいて色データのノイズ除去を行うことで、血流障害の危険度をより正確に算出することができるようになる。 By removing noise from color data based on infrared data, the risk of blood flow disorders can be calculated more accurately.
　図２０は、本実施形態に係る血流障害判定システム１００により測定され、ノイズ除去された色データ及びノイズ除去されていない色データを示す図である。同図では、横軸に時間を示し、上側の縦軸にノイズ除去を行った色データの明度を無次元で示し、下側の縦軸にノイズ除去していない色データの明度を無次元で示している。ノイズ除去を行った色データのグラフＹ１及びノイズ除去していない色データのグラフＹ２いずれも、４チャンネルの色データを実線、一点鎖線、二点鎖線及び破線で示している。 FIG. 20 is a diagram showing color data with noise removed and color data without noise measured by the blood flow disorder determination system 100 according to the present embodiment. In the figure, the horizontal axis represents time, the upper vertical axis represents the lightness of noise-removed color data in a non-dimensional manner, and the lower vertical axis represents the brightness of non-noise-removed color data in a non-dimensional manner. Shows. In both the noise-removed color data graph Y1 and the noise-free color data graph Y2, the 4-channel color data is indicated by a solid line, a one-dot chain line, a two-dot chain line, and a broken line.
　ノイズ除去を行った色データのグラフＹ１は、不連続な箇所を含み、当該箇所がノイズとして除去されたデータである。一方、ノイズ除去していない色データのグラフＹ２は連続している。 The graph Y1 of color data from which noise has been removed is data in which discontinuous portions are included and the portions have been removed as noise. On the other hand, the graph Y2 of the color data without noise removal is continuous.
　図２１は、本実施形態に係る血流障害判定装置１０により色データに基づき推定された危険度を示す図である。同図では、横軸に経過日数を示し、縦軸に危険度を示している。同図では、４チャンネルの色センサ２２により測定され、赤外データに基づいてノイズ除去された色データに基づき危険度を算出した結果を示している。 FIG. 21 is a diagram showing a risk degree estimated based on color data by the blood flow disorder determination device 10 according to the present embodiment. In the figure, the horizontal axis indicates the number of days elapsed, and the vertical axis indicates the degree of risk. In the same figure, the result of calculating the degree of danger based on the color data measured by the 4-channel color sensor 22 and noise-removed based on the infrared data is shown.
　血流障害判定装置１０は、ノイズ除去された４つの色データに基づき、それぞれ危険度を推定する。図２１からは、２０１８年７月３０日の夜に実線で示した第１危険度Ｃ１と、一点鎖線で示した第２危険度Ｃ２とが急上昇していることが読み取れる。第１危険度Ｃ１は、最大値の１．０近くまで上昇し、その後０．６程度を維持している。また、第２危険度Ｃ２は、０．３程度まで上昇し、その後０．３程度を維持している。その他、二点鎖線で示した第３危険度Ｃ３及び破線で示した第４危険度Ｃ４は、２０１８年７月３１日の朝に０．１程度に上昇し、その後０．１程度を維持している。 The blood flow disorder determination device 10 estimates the degree of danger based on the four color data from which noise has been removed. It can be seen from FIG. 21 that the first risk level C1 indicated by the solid line and the second risk level C2 indicated by the alternate long and short dash line are rapidly increasing on the night of July 30, 2018. The first risk C1 has risen to a maximum value of nearly 1.0, and has been maintained at about 0.6 thereafter. Further, the second risk C2 rises to about 0.3 and then maintains about 0.3. In addition, the third risk C3 indicated by the chain double-dashed line and the fourth risk C4 indicated by the broken line rise to about 0.1 on the morning of July 31, 2018, and then maintain about 0.1. ing.
　図２１に示すデータによれば、少なくとも１チャンネルの色データについて、危険度が最大値近くまで上昇しており、生体１に血流障害が生じている蓋然性が高いと判断できる。 According to the data shown in FIG. 21, it can be determined that the risk of the color data of at least one channel has risen close to the maximum value, and there is a high probability that blood flow is impaired in the living body 1.
　以上説明した実施形態は、本発明の理解を容易にするためのものであり、本発明を限定して解釈するためのものではない。実施形態が備える各要素並びにその配置、材料、条件、形状及びサイズ等は、例示したものに限定されるわけではなく適宜変更することができる。また、異なる実施形態で示した構成同士を部分的に置換し又は組み合わせることが可能である。 The embodiments described above are for facilitating the understanding of the present invention and are not for limiting the interpretation of the present invention. Each element included in the embodiment and its arrangement, material, condition, shape, size and the like are not limited to the exemplified ones and can be appropriately changed. Further, the configurations shown in different embodiments can be partially replaced or combined.
　本発明は、生体の色データ及び温度データの少なくともいずれかに基づいて血流障害の危険度を算出し、危険度に基づいて血流障害を判定することができる血流障害判定装置、血流障害判定方法、血流障害判定プログラム及び血流障害判定システムを提供する。 The present invention calculates a risk of blood flow disorder based on at least one of color data and temperature data of a living body, and a blood flow disorder determination device capable of determining a blood flow disorder based on the risk. Provided are a failure determination method, a blood flow failure determination program, and a blood flow failure determination system.
　［付記１］
　生体の色の時間変化を測定した色データ及び前記生体の温度の時間変化を測定した温度データの少なくともいずれかを含む時系列データを取得する取得部と、
　前記時系列データを近似する所定の関数に含まれる１又は複数のパラメータの値を決定する決定部と、
　前記１又は複数のパラメータの値に基づいて、危険度を推定する第１推定部と、
　前記危険度に基づいて、前記生体に血流障害が発生しているか否かを判定する第２判定部と、
　を備える血流障害判定装置。 [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 a risk level based on the values of the one or more parameters;
A second determination unit that determines whether or not a blood flow disorder has occurred in the living body based on the risk level;
A device for determining blood flow disorders.
　［付記２］
　前記第１推定部は、前記１又は複数のパラメータの値及び前記１又は複数のパラメータの決定係数に基づいて指標を算出し、前記指標に基づいて前記危険度を更新することで、時間変化する前記危険度を推定する、
　付記１に記載の血流障害判定装置。 [Appendix 2]
The first estimation unit calculates an index based on the value of the one or more parameters and the coefficient of determination of the one or more parameters, and updates the risk based on the index, thereby changing with time. Estimating the risk,
The blood flow disorder determination device according to attachment 1.
　［付記３］
　時間をｔと表し、前記１又は複数のパラメータをＡ、Ａ０及びτと表すとき、
　前記所定の関数は、Ａ×ｅｘｐ（－ｔ／τ）＋Ａ０である、
　付記２に記載の血流障害判定装置。 [Appendix 3]
When time is represented by t and the one or more parameters are represented by A, A 0 and τ,
The predetermined function is A×exp(−t/τ)+A 0 ,
The blood flow disorder determination device according to attachment 2.
　［付記４］
　前記第１推定部は、
　前記指標の絶対値が第３閾値以上である場合、前記危険度の前回の値に前記指標を加算することで前記危険度を更新し、
　前記指標の絶対値が前記第３閾値未満である場合、前記危険度の前回の値と前記指標のいずれか大きい値により前記危険度を更新する、
　付記２又は３に記載の血流障害判定装置。 [Appendix 4]
The first estimation unit is
When the absolute value of the index is equal to or greater than a third threshold value, the risk level is updated by adding the index to the previous value of the risk level,
If the absolute value of the index is less than the third threshold value, the risk level is updated with a larger value of the previous value of the risk level and the index,
The blood flow disorder determination device according to attachment 2 or 3.
　［付記５］
　前記取得部は、前記生体の脈波の時間変化を複数の異なる期間に測定した複数の脈波データを取得し、
　前記複数の脈波データをそれぞれフーリエ変換して複数のスペクトルデータを生成する生成部と、
　前記複数のスペクトルデータに含まれる１又は複数のピークを検出する検出部と、
　所定の周波数区間毎に前記１又は複数のピークが検出された頻度を算出する算出部と、
　前記頻度に基づいて、前記１又は複数のピークがアーティファクトであるか否かを判定する第１判定部と、をさらに備え、
　前記第２判定部は、前記１又は複数のピークがアーティファクトでないと判定された場合に、前記複数のスペクトルデータに基づいて、前記生体に血流障害が発生しているか否かを判定する、
　付記１から４のいずれか一項に記載の血流障害判定装置。 [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 generation unit that generates a plurality of spectrum data by Fourier transforming each of the plurality of pulse wave data,
A detector for detecting one or more peaks contained in the plurality of spectrum data;
A calculation unit that calculates the frequency at which the one or more peaks are detected for each predetermined frequency section;
A first determination unit that determines whether or not the one or more peaks are artifacts based on the frequency,
The second determination unit, when it is determined that the one or more peaks are not artifacts, determines whether or not a blood flow disorder has occurred in the living body based on the plurality of spectrum data,
5. The blood flow disorder determination device according to any one of appendices 1 to 4.
　［付記６］
　前記第１判定部は、前記複数のスペクトルデータのパワーの和が第１閾値以上である場合に、前記１又は複数のピークがアーティファクトであるか否かを判定する、
　付記５に記載の血流障害判定装置。 [Appendix 6]
The first determination unit determines whether or not the one or more peaks are artifacts when the sum of powers of the plurality of spectrum data is equal to or more than a first threshold value.
The blood flow disorder determination device according to attachment 5.
　［付記７］
　前記第２判定部は、前記アーティファクトでないと判定された前記１又は複数のピークのうち最も頻度が高い周波数区間を特定し、前記複数のスペクトルデータの前記周波数区間のパワーの平均値が第２閾値以下である場合に、前記生体に血流障害が発生していると判定する、
　付記６に記載の血流障害判定装置。 [Appendix 7]
The second determination unit identifies a frequency section having the highest frequency among the one or a plurality of peaks determined not to be the artifact, and an average value of powers of the frequency sections of the plurality of spectrum data is a second threshold value. When the following is determined to be a blood flow disorder in the living body,
The blood flow disorder determination device according to attachment 6.
　［付記８］
　前記第２判定部は、前記複数のスペクトルデータのパワーの和が第１閾値未満である場合、前記複数のスペクトルデータのパワーの和の平均値が第２閾値以下である場合に、前記生体に血流障害が発生していると判定する、
　付記６又は７に記載の血流障害判定装置。 [Appendix 8]
When the sum of the powers of the plurality of spectrum data is less than a first threshold, the second determination unit determines that the living body has the average value of the sum of the powers of the plurality of spectrum data is equal to or less than a second threshold. It is determined that a blood flow disorder has occurred,
The blood flow disorder determination device according to appendix 6 or 7.
　［付記９］
　所定期間に前記第１判定部及び前記第２判定部による判定を複数回行った場合における血流障害が発生していると判定された割合に基づいて、時間変化する脈波危険度を推定する第２推定部をさらに備える、
　付記５から８のいずれか一項に記載の血流障害判定装置。 [Appendix 9]
The time-varying pulse wave risk is estimated based on the rate at which it is determined that a blood flow disorder has occurred when the determinations by the first determination unit and the second determination unit are performed multiple times within a predetermined period. Further comprising a second estimation unit,
9. The blood flow disorder determination device according to any one of appendices 5 to 8.
　［付記１０］
　前記第２判定部は、前記１又は複数のピークがアーティファクトでないと判定された場合に、前記複数の脈波データを用いて前記生体に血流障害が発生しているか否かを判定した結果と、前記色データ及び前記温度データの少なくともいずれかを用いて前記生体に血流障害が発生しているか否かを判定した結果とに基づいて、前記生体に血流障害が生じているか否かを総合判定する、
　付記９に記載の血流障害判定装置。 [Appendix 10]
When the second determination unit determines that the one or more peaks are not artifacts, the second determination unit determines whether or not a blood flow disorder has occurred in the living body by using the plurality of pulse wave data. , Based on the result of determining whether the blood flow disorder has occurred in the living body using at least one of the color data and the temperature data, whether the blood flow disorder has occurred in the living body. Comprehensive judgment,
The blood flow disorder determination device according to attachment 9.
　［付記１１］
　前記第２判定部は、前記脈波危険度及び前記危険度の少なくともいずれかが第４閾値以上である場合に、前記生体に血流障害が生じていると総合判定する、
　付記１０に記載の血流障害判定装置。 [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 a fourth threshold value or more,
The blood flow disorder determination device according to attachment 10.
　［付記１２］
　生体の色の時間変化を測定した色データ及び前記生体の温度の時間変化を測定した温度データの少なくともいずれかを含む時系列データを取得することと、
　前記時系列データを近似する所定の関数に含まれる１又は複数のパラメータの値を決定することと、
　前記１又は複数のパラメータの値に基づいて、危険度を推定することと、
　前記危険度に基づいて、前記生体に血流障害が発生しているか否かを判定することと、
　を含む血流障害判定方法。 [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,
Determining values of one or more parameters included in a predetermined function approximating the time series data;
Estimating a risk level based on the values of the one or more parameters;
Based on the risk, to determine whether or not a blood flow disorder has occurred in the living body,
A blood flow disorder determination method including the following.
　［付記１３］
　血流障害判定装置に備えられたプロセッサを、
　生体の色の時間変化を測定した色データ及び前記生体の温度の時間変化を測定した温度データの少なくともいずれかを含む時系列データを取得する取得部、
　前記時系列データを近似する所定の関数に含まれる１又は複数のパラメータの値を決定する決定部、
　前記１又は複数のパラメータの値に基づいて、危険度を推定する第１推定部、及び
　前記危険度に基づいて、前記生体に血流障害が発生しているか否かを判定する第２判定部、
　として機能させる血流障害判定プログラム。 [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 measured with time of the color of a living body and temperature data measured with time 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 a risk level 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 risk level. ,
Blood flow disorder judgment program to function as.
　［付記１４］
　生体の色の時間変化を測定した色データ及び前記生体の温度の時間変化を測定した温度データの少なくともいずれかを測定し、前記色データ及び前記温度データの少なくともいずれかを含む時系列データを出力するセンサと、前記時系列データを用いて前記生体に血流障害が発生しているか否かを判定する血流障害判定装置とを備える血流障害判定システムであって、
　前記血流障害判定装置は、
　前記時系列データを近似する所定の関数に含まれる１又は複数のパラメータの値を決定する決定部と、
　前記１又は複数のパラメータの値に基づいて、危険度を推定する第１推定部と、
　前記危険度に基づいて、前記生体に血流障害が発生しているか否かを判定する第２判定部と、を有する、
　血流障害判定システム。 [Appendix 14]
At least one of the color data obtained by measuring the time change of the color of the living body and the temperature data obtained by measuring the time change of the temperature of the living body is measured, and the time series data including at least one of the color data and the temperature data is output. A sensor, and a blood flow disorder determination system comprising a blood flow disorder determination device that determines whether or not a blood flow disorder has occurred in the living body using the time series data,
The blood flow disorder determination device,
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 a risk level based on the values of the one or more parameters;
A second determination unit that determines whether or not a blood flow disorder has occurred in the living body based on the risk level.
Blood flow disorder determination system.
　１…生体、１０…血流障害判定装置、１０ａ…ＣＰＵ、１０ｂ…ＲＡＭ、１０ｃ…ＲＯＭ、１０ｄ…通信部、１０ｅ…入力部、１０ｆ…表示部、１１…取得部、１２…生成部、１３…検出部、１４…算出部、１５…第１判定部、１６…第２判定部、１７…決定部、１８…第１推定部、１９…第２推定部、２０…センサ、２１…脈波センサ、２２…色センサ、２３…温度センサ、２５…フレキシブル基板、３０…トランスミッタ、１００…血流障害判定システム 1... Living body, 10... Blood flow disorder determination device, 10a... CPU, 10b... RAM, 10c... ROM, 10d... Communication part, 10e... Input part, 10f... Display part, 11... Acquisition part, 12... Generation part, 13 ...Detection unit, 14...Calculation unit, 15...First determination unit, 16...Second determination 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)

  1. 　生体の脈波の時間変化を複数の異なる期間に測定した複数の脈波データを取得する取得部と、
    　前記複数の脈波データをそれぞれフーリエ変換して複数のスペクトルデータを生成する生成部と、
    　前記複数のスペクトルデータに含まれる１又は複数のピークを検出する検出部と、
    　所定の周波数区間毎に前記１又は複数のピークが検出された頻度を算出する算出部と、
    　前記頻度に基づいて、前記１又は複数のピークがアーティファクトであるか否かを判定する第１判定部と、
    　前記１又は複数のピークがアーティファクトでないと判定された場合に、前記複数のスペクトルデータに基づいて、前記生体に血流障害が発生しているか否かを判定する第２判定部と、
    　を備える血流障害判定装置。     An acquisition unit that 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 generation unit that generates a plurality of spectrum data by Fourier transforming each of the plurality of pulse wave data,
    A detector for detecting one or more peaks contained in the plurality of spectrum data;
    A calculation unit that calculates the frequency at which the one or more peaks are detected for each predetermined frequency section;
    A first determination unit that determines whether the one or more peaks are artifacts based on the frequency;
    A second determination unit that determines whether or not a blood flow disorder has occurred in the living body based on the plurality of spectrum data when it is determined that the one or more peaks are not artifacts,
    A device for determining blood flow disorders.
  2. 　前記第１判定部は、前記複数のスペクトルデータのパワーの和が第１閾値以上である場合に、前記１又は複数のピークがアーティファクトであるか否かを判定する、
    　請求項１に記載の血流障害判定装置。     The first determination unit determines whether or not the one or more peaks are artifacts when the sum of powers of the plurality of spectrum data is equal to or more than a first threshold value.
    The blood flow disorder determination device according to claim 1.
  3. 　前記第２判定部は、前記アーティファクトでないと判定された前記１又は複数のピークのうち最も頻度が高い周波数区間を特定し、前記複数のスペクトルデータの前記周波数区間のパワーの平均値が第２閾値以下である場合に、前記生体に血流障害が発生していると判定する、
    　請求項２に記載の血流障害判定装置。     The second determination unit identifies a frequency section having the highest frequency among the one or a plurality of peaks determined not to be the artifact, and an average value of powers of the frequency sections of the plurality of spectrum data is a second threshold value. When the following is determined to be a blood flow disorder in the living body,
    The blood flow disorder determination device according to claim 2.
  4. 　前記第２判定部は、前記複数のスペクトルデータのパワーの和が第１閾値未満である場合、前記複数のスペクトルデータのパワーの和の平均値が第２閾値以下である場合に、前記生体に血流障害が発生していると判定する、
    　請求項２又は３に記載の血流障害判定装置。     When the sum of the powers of the plurality of spectrum data is less than a first threshold, the second determination unit determines that the living body has the average value of the sum of the powers of the plurality of spectrum data is equal to or less than a second threshold. It is determined that a blood flow disorder has occurred,
    The blood flow disorder determination device according to claim 2 or 3.
  5. 　前記取得部は、前記生体の色の時間変化を測定した色データ及び前記生体の温度の時間変化を測定した温度データの少なくともいずれかを含む時系列データを取得し、
    　前記時系列データを近似する所定の関数に含まれる１又は複数のパラメータの値を決定する決定部と、
    　前記１又は複数のパラメータの値に基づいて、危険度を推定する第１推定部と、をさらに備え、
    　前記第２判定部は、前記危険度に基づいて、前記生体に血流障害が発生しているか否かを判定する、
    　請求項１から４のいずれか一項に記載の血流障害判定装置。     The acquisition unit acquires 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,
    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 estimating unit for estimating a risk degree based on the values of the one or more parameters,
    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 determination device according to any one of claims 1 to 4.
  6. 　前記第１推定部は、前記１又は複数のパラメータの値及び前記１又は複数のパラメータの決定係数に基づいて指標を算出し、前記指標に基づいて前記危険度を更新することで、時間変化する前記危険度を推定する、
    　請求項５に記載の血流障害判定装置。     The first estimation unit calculates an index based on the value of the one or more parameters and the coefficient of determination of the one or more parameters, and updates the risk based on the index, thereby changing with time. Estimating the risk,
    The blood flow disorder determination device according to claim 5.
  7. 　時間をｔと表し、前記１又は複数のパラメータをＡ、Ａ０及びτと表すとき、
    　前記所定の関数は、Ａ×ｅｘｐ（－ｔ／τ）＋Ａ０である、
    　請求項６に記載の血流障害判定装置。     When time is represented by t and the one or more parameters are represented by A, A 0 and τ,
    The predetermined function is A×exp(−t/τ)+A 0 ,
    The blood flow disorder determination device according to claim 6.
  8. 　前記第１推定部は、
    　前記指標の絶対値が第３閾値以上である場合、前記危険度の前回の値に前記指標を加算することで前記危険度を更新し、
    　前記指標の絶対値が前記第３閾値未満である場合、前記危険度の前回の値と前記指標のいずれか大きい値により前記危険度を更新する、
    　請求項６又は７に記載の血流障害判定装置。     The first estimation unit is
    When the absolute value of the index is equal to or greater than a third threshold value, the risk level is updated by adding the index to the previous value of the risk level,
    If the absolute value of the index is less than the third threshold value, the risk level is updated with a 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.
  9. 　所定期間に前記第１判定部及び前記第２判定部による判定を複数回行った場合における血流障害が発生していると判定された割合に基づいて、時間変化する脈波危険度を推定する第２推定部をさらに備える、
    　請求項５から８のいずれか一項に記載の血流障害判定装置。     The time-varying pulse wave risk is estimated based on the rate at which it is determined that a blood flow disorder has occurred when the determinations by the first determination unit and the second determination unit are performed multiple times within a predetermined period. Further comprising a second estimation unit,
    The blood flow disorder determination device according to any one of claims 5 to 8.
  10. 　前記第２判定部は、前記１又は複数のピークがアーティファクトでないと判定された場合に、前記複数の脈波データを用いて前記生体に血流障害が発生しているか否かを判定した結果と、前記色データ及び前記温度データの少なくともいずれかを用いて前記生体に血流障害が発生しているか否かを判定した結果とに基づいて、前記生体に血流障害が生じているか否かを総合判定する、
    　請求項９に記載の血流障害判定装置。     When the second determination unit determines that the one or more peaks are not artifacts, the second determination unit determines whether or not a blood flow disorder has occurred in the living body by using the plurality of pulse wave data. , Based on the result of determining whether the blood flow disorder has occurred in the living body using at least one of the color data and the temperature data, whether the blood flow disorder has occurred in the living body. Comprehensive judgment,
    The blood flow disorder determination device according to claim 9.
  11. 　前記第２判定部は、前記脈波危険度及び前記危険度の少なくともいずれかが第４閾値以上である場合に、前記生体に血流障害が生じていると総合判定する、
    　請求項１０に記載の血流障害判定装置。     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 a fourth threshold value or more,
    The blood flow disorder determination device according to claim 10.
  12. 　前記色データは、赤外データを含み、
    　前記決定部は、前記赤外データに基づいてノイズ除去された前記時系列データを近似する前記所定の関数に含まれる前記１又は複数のパラメータの値を決定する、
    　請求項５から１１のいずれか一項に記載の血流障害判定装置。     The color data includes infrared data,
    The determining unit determines the value 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 determination device according to any one of claims 5 to 11.
  13. 　前記算出部は、前記複数の異なる期間のうち基準期間に測定した脈波データの確率分布と、前記複数の異なる期間のうち対象期間に測定した脈波データの確率分布とが等しいか否かを検定する検定統計量を算出し、
    　前記第２判定部は、前記検定統計量に基づいて、前記生体に血流障害が発生しているか否かを判定する、
    　請求項１から１２のいずれか一項に記載の血流障害判定装置。     The calculation unit, whether the probability distribution of the pulse wave data measured in the reference period of the plurality of different periods and the probability distribution of the pulse wave data measured in the target period of the plurality of different periods is equal or not. Calculate the test statistic to test,
    The second determination unit determines whether a blood flow disorder has occurred in the living body based on the test statistic.
    The blood flow disorder determination device according to any one of claims 1 to 12.
  14. 　生体の脈波の時間変化を複数の異なる期間に測定した複数の脈波データを取得することと、
    　前記複数の脈波データをそれぞれフーリエ変換して複数のスペクトルデータを生成することと、
    　前記複数のスペクトルデータに含まれる１又は複数のピークを検出することと、
    　所定の周波数区間毎に前記１又は複数のピークが検出された頻度を算出することと、
    　前記頻度に基づいて、前記１又は複数のピークがアーティファクトであるか否かを判定することと、
    　前記１又は複数のピークがアーティファクトでないと判定された場合に、前記複数のスペクトルデータに基づいて、前記生体に血流障害が発生しているか否かを判定することと、
    　を含む血流障害判定方法。     Acquiring 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,
    Generating a plurality of spectral data by Fourier transforming each of the plurality of pulse wave data,
    Detecting one or more peaks contained in the plurality of spectral data;
    Calculating the frequency at which the one or more peaks are detected for each predetermined frequency section;
    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, based on the plurality of spectrum data, determining whether or not a blood flow disorder has occurred in the living body,
    A blood flow disorder determination method including the following.
  15. 　血流障害判定装置に備えられたプロセッサを、
    　生体の脈波の時間変化を複数の異なる期間に測定した複数の脈波データを取得する取得部、
    　前記複数の脈波データをそれぞれフーリエ変換して複数のスペクトルデータを生成する生成部、
    　前記複数のスペクトルデータに含まれる１又は複数のピークを検出する検出部、
    　所定の周波数区間毎に前記１又は複数のピークが検出された頻度を算出する算出部、
    　前記頻度に基づいて、前記１又は複数のピークがアーティファクトであるか否かを判定する第１判定部、及び
    　前記１又は複数のピークがアーティファクトでないと判定された場合に、前記複数のスペクトルデータに基づいて、前記生体に血流障害が発生しているか否かを判定する第２判定部、
    　として機能させる血流障害判定プログラム。     The processor provided in the blood flow disorder determination device,
    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,
    A generation unit that generates a plurality of spectrum data by Fourier transforming each of the plurality of pulse wave data.
    A detector that detects one or more peaks included in the plurality of spectrum 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, a first determination unit that determines whether the one or more peaks are artifacts, and, if the one or more peaks are determined to be not artifacts, in the plurality of spectral data A second determination unit that determines whether or not a blood flow disorder has occurred in the living body,
    Blood flow disorder judgment program to function as.
  16. 　生体の脈波の時間変化を複数の異なる期間に測定し、複数の脈波データを出力する脈波センサと、前記複数の脈波データを用いて前記生体に血流障害が発生しているか否かを判定する血流障害判定装置とを備える血流障害判定システムであって、
    　前記血流障害判定装置は、
    　前記複数の脈波データをそれぞれフーリエ変換して複数のスペクトルデータを生成する生成部と、
    　前記複数のスペクトルデータに含まれる１又は複数のピークを検出する検出部と、
    　所定の周波数区間毎に前記１又は複数のピークが検出された頻度を算出する算出部と、
    　前記頻度に基づいて、前記１又は複数のピークがアーティファクトであるか否かを判定する第１判定部と、
    　前記１又は複数のピークがアーティファクトでないと判定された場合に、前記複数のスペクトルデータに基づいて、前記生体に血流障害が発生しているか否かを判定する第２判定部と、を有する、
    　血流障害判定システム。     A pulse wave sensor that measures the 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 whether or not a blood flow disorder has occurred in the living body using the plurality of pulse wave data. A blood flow disorder determination system comprising a blood flow disorder determination device for determining whether
    The blood flow disorder determination device,
    A generation unit that generates a plurality of spectrum data by Fourier transforming each of the plurality of pulse wave data,
    A detector for detecting one or more peaks contained in the plurality of spectrum data;
    A calculation unit that calculates the frequency at which the one or more peaks are detected for each predetermined frequency section;
    A first determination unit that determines whether the one or more peaks are artifacts based on the frequency;
    A second determination unit that determines whether or not a blood flow disorder has occurred in the living body based on the plurality of spectrum data when it is determined that the one or more peaks are not artifacts,
    Blood flow disorder determination system.
PCT/JP2019/046671 2018-11-29 2019-11-28 Blood flow obstruction determination device, blood flow obstruction determination method, blood flow obstruction determination program, and blood flow obstruction determination system WO2020111203A1 (en)

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