WO2019146025A1 - Dispositif de calcul d'onde d'impulsion, méthode de calcul d'onde d'impulsion et programme de calcul d'onde d'impulsion - Google Patents

Dispositif de calcul d'onde d'impulsion, méthode de calcul d'onde d'impulsion et programme de calcul d'onde d'impulsion Download PDF

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WO2019146025A1
WO2019146025A1 PCT/JP2018/002170 JP2018002170W WO2019146025A1 WO 2019146025 A1 WO2019146025 A1 WO 2019146025A1 JP 2018002170 W JP2018002170 W JP 2018002170W WO 2019146025 A1 WO2019146025 A1 WO 2019146025A1
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waveform
pulse wave
section
pulse
unit
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PCT/JP2018/002170
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English (en)
Japanese (ja)
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大輔 内田
村瀬　有一
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富士通株式会社
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Priority to PCT/JP2018/002170 priority Critical patent/WO2019146025A1/fr
Priority to JP2019567451A priority patent/JP6947227B2/ja
Publication of WO2019146025A1 publication Critical patent/WO2019146025A1/fr

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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

Definitions

  • the present invention relates to a pulse wave calculation device, a pulse wave calculation method, and a pulse wave calculation program.
  • pulse waves which are fluctuations in blood volume in blood vessels accompanying the beating of the heart, using a dedicated instrument attached to a subject.
  • a technique for calculating the heart rate which is one aspect of a pulse wave
  • a peak of an electrocardiographic waveform measured by attaching an electrode of an electrocardiograph to a living body for example, a P wave or an R wave ECG method to calculate heart rate.
  • a photoplethysmogram is generated that irradiates infrared rays to peripheral blood vessels such as fingers and earlobe, and calculates a pulse approximately equivalent to a heartbeat from an optical change whose reflected light periodically changes due to blood flow and absorption characteristics.
  • the wave method is mentioned.
  • photographed test subject is proposed.
  • a power spectrum is obtained, for example, by FFT (Fast Fourier Transform) or maximum entropy method for signal components of an image in which the subject's face is photographed by a camera, and the heartbeat of the power spectrum is calculated from the peak value. Get the number.
  • JP 2014-221172 A JP 2004-316 A JP, 2016-220915, A JP, 2014-198201, A
  • the pulse wave calculation device includes an acquisition unit that acquires a first pulse waveform of the subject.
  • the pulse wave calculation device has a selection unit that selects one or more section waveforms from the first pulse waveform or the second waveform extracted from the first pulse waveform.
  • the pulse wave calculation device further includes a normalization processing unit that normalizes at least one of the time width and the amplitude of the interval waveform based on a model. Further, the pulse wave calculation device statistically processes the standardized section waveform and outputs it.
  • the pulse waveform can be acquired with high accuracy.
  • FIG. 1 is a diagram showing an example of processing for calculating a pulse wave from a photoelectric pulse wave sensor in the background art.
  • FIG. 2 is a diagram showing an example of processing for calculating a pulse wave from an image in the background art.
  • FIG. 3 is a diagram illustrating an example of the calculation device in the first embodiment.
  • FIG. 4 is a view showing an example of a pulse wave model in the first embodiment.
  • FIG. 5 is a diagram showing an example of a pulse wave model.
  • FIG. 6 is a view showing an example of the relationship between the pulse wave interval and the amplitude.
  • FIG. 7 is a diagram illustrating an example of the signal storage unit.
  • FIG. 8 is a diagram showing an example of the reference point identification processing result in the first embodiment.
  • FIG. 9 is a diagram showing an example of calculation processing of an autocorrelation coefficient of a pulse waveform.
  • FIG. 10 is a diagram showing an example of the calculation result of the autocorrelation coefficient.
  • FIG. 11 is a diagram illustrating an example of the normalization process and the statistical process in the first embodiment.
  • FIG. 12 is a flowchart illustrating an example of pulse wave calculation processing in the first embodiment.
  • FIG. 13 is a flowchart illustrating an example of pulse wave acquisition processing according to the first embodiment.
  • FIG. 14 is a flowchart illustrating an example of the reference point identification process according to the first embodiment.
  • FIG. 15 is a flowchart illustrating an example of the correlation calculation process according to the first embodiment.
  • FIG. 16 is a flowchart of an example of the section selection process according to the first embodiment.
  • FIG. 17 is a flowchart of an example of the waveform normalization process according to the first embodiment.
  • FIG. 18 is a flowchart illustrating an example of the output process in the first embodiment.
  • FIG. 19 is a diagram illustrating an example of the calculation device in the second embodiment.
  • FIG. 20 is a flowchart illustrating an example of pulse wave calculation processing according to the second embodiment.
  • FIG. 21 is a flowchart of an example of the luminance waveform acquisition process according to the second embodiment.
  • FIG. 22 is a flowchart of an example of the waveform filtering process according to the second embodiment.
  • FIG. 23 is a diagram illustrating an example of the reference point identification process according to the third embodiment.
  • FIG. 24 is a diagram illustrating an example of a computer that executes a pulse wave calculation program.
  • FIG. 1 is a diagram showing an example of processing for calculating a pulse wave from a photoelectric pulse wave sensor in the background art.
  • the photoelectric pulse wave sensor 111 is attached to, for example, a finger 112 of a subject, and calculates a pulse wave based on the fluctuation of reflected light such as infrared rays irradiated to a peripheral blood vessel.
  • the graph D1 in FIG. 1 shows a waveform obtained by filtering the pulse waveform obtained by the photoelectric pulse wave sensor 111.
  • the horizontal axis indicates the passage of time (seconds)
  • the vertical axis indicates the value (au) of the measured signal.
  • the horizontal axis indicates the passage of time
  • the vertical axis indicates the measured signal value, unless otherwise described.
  • noise is mixed in the measured signal as shown in the graph D1.
  • the pressing pressure of the finger 112 against the photoelectric pulse wave sensor 111 changes at each time point of R1 to R5
  • noise is mixed in the measured signal as shown in the graph D1.
  • a graph D2 of FIG. 1 shows an example of a graph obtained by performing second-order differentiation on a waveform mixed with such noise.
  • the vertical axis represents the second derivative of the pulse wave signal shown in D1.
  • FIG. 2 is a diagram showing an example of processing for calculating a pulse wave from an image in the background art.
  • an imaging device such as the camera 121 captures an image of the subject's face, for example, and calculates a pulse wave based on the fluctuation of a luminance signal (for example, green component) in a region F2 included in the captured image F1. .
  • a luminance signal for example, green component
  • the luminance signal detected using the image F1 is weak, and noise is likely to occur according to, for example, changes in external light, the positional relationship between the subject's living body and the camera, and the like.
  • the image F1 may change as shown in the image F1 ', for example, when the subject moves the body while taking a face image.
  • the region of the subject's face included in region F2 of image F1 does not match the region of the subject's face included in region F2 'of image F1'.
  • the continuity between the luminance signal detected by using the image F1 and the luminance signal detected by using the image F1 ' may be lost.
  • the graph D3 in FIG. 2 shows the waveform of the luminance signal detected when the image F1 changes as shown in the image F1 '.
  • the vertical axis represents the value of the measured luminance signal.
  • a graph D4 of FIG. 2 shows an example of a graph obtained by second-order differentiation of the waveform shown in D3.
  • the vertical axis represents a value obtained by performing second-order differentiation on the luminance signal shown in D3.
  • the calculation device 10 described below selects a section waveform corresponding to a pulse from a photoplethysmogram, a face image, etc., and based on a model of ventricular volume such as a Windkessel model described later
  • the pulse waveform is calculated by statistically processing the section waveform whose width is standardized.
  • the calculation device 10 can suppress the variation of the waveform and acquire the pulse wave with high accuracy.
  • the model used when the calculation device 10 normalizes the time width of the interval waveform is, for example, a model that reproduces a pulse wave, such as a Windkessel model, represented by a convex and monotonically increasing function.
  • FIG. 3 is a diagram illustrating an example of the calculation device in the first embodiment.
  • the calculation device 10 in the present embodiment includes a sensor 11, a storage unit 20, and a control unit 30.
  • the calculation device 10 is an example of a pulse wave calculation device.
  • the sensor 11 detects a signal or the like used to calculate a pulse wave.
  • the sensor 11 is, for example, a contact-type sensor mounted on a subject such as a photoelectric pulse wave sensor 111 shown in FIG.
  • the storage unit 20 is an example of a storage device that stores, for example, various data such as a program executed by the control unit 30, and is, for example, a memory, a processor, or the like.
  • the storage unit 20 includes a pulse wave model 21 and a signal storage unit 22.
  • the pulse wave model 21 is a model that reproduces a pulse wave, such as a Windkessel model (model of ventricular volume).
  • FIG. 4 is a view showing an example of a pulse wave model in the first embodiment.
  • the pulse wave model 21 stores a table in which “pulse wave interval” indicating the passage of time is associated with “amplitude” corresponding to the volume of the ventricle at each time point.
  • the “pulse wave interval” is, for example, milliseconds (ms).
  • the pulse wave model 21 is expressed by a function that is convex upward and monotonically increasing.
  • the pulse wave model 21 receives, for example, a table calculated in advance based on the following equation (1).
  • "Amp” indicates the signal amplitude and "RRI” indicates the pulse interval.
  • FIG. 5 is a diagram showing an example of a pulse wave model.
  • the ventricular volume is at a maximum at time t1 and then at a time t2 when time b has elapsed as the heart contracts.
  • the ventricular volume increases rapidly since blood pressure difference is large until time t3, that is, blood rapidly flows into the ventricle.
  • the blood inflow decreases because the blood pressure difference decreases, and the ventricular volume gradually increases until time t4.
  • contraction of the heart starts again and the ventricular volume decreases.
  • FIG. 6 is a view showing an example of the relationship between the pulse wave interval and the amplitude.
  • the model of the ventricular volume shown in FIG. 6 is a monotonically increasing model that is convex upward from time t2 to time t4 by excluding the period in which the heart contracts from time t1 to time t2.
  • FIG. 7 is a diagram illustrating an example of the signal storage unit. As shown in FIG. 7, the signal storage unit 22 stores “time” and “signal amplitude” in association with each other. The information stored in the signal storage unit 22 is input by, for example, an acquisition unit 31 described later.
  • control unit 30 is a processing unit that controls the entire calculation device 10 and is, for example, a processor.
  • the control unit 30 includes an acquisition unit 31, a section selection unit 35, a normalization unit 36, and an output unit 37.
  • the acquisition unit 31, the section selection unit 35, the standardization unit 36, and the output unit 37 are an example of an electronic circuit included in the processor and an example of a process executed by the processor.
  • the acquisition unit 31 acquires a signal related to a pulse wave.
  • the acquisition unit 31 acquires a signal detected by the sensor 11 and stores the signal in the signal storage unit 22.
  • the section selection unit 35 selects a section waveform from among the waveforms extracted from the acquired signal.
  • the interval selection unit 35 When selecting the interval waveform, the interval selection unit 35 generates, for example, a pulse waveform from the signal amplitude stored in the signal storage unit 22, and generates a filter according to the pulse wave frequency with respect to the generated pulse waveform. You may process.
  • the section selection unit 35 is an example of a selection unit, and the pulse waveform generated from the signal amplitude is an example of a first pulse waveform.
  • the section selection unit 35 performs band pass filtering processing in a range of frequencies that can be obtained by the pulse wave, such as 40 to 240 bpm. In addition, the section selection unit 35 corrects the amplitude such that, for example, the median value of the amplitude of the filtered extracted waveform is zero.
  • the extracted waveform is an example of a second waveform.
  • FIG. 8 is a diagram showing an example of the reference point identification processing result in the first embodiment.
  • a graph G1 in FIG. 8 shows a pulse waveform generated based on the signal amplitude stored in the signal storage unit 22.
  • the vertical axis represents the signal amplitude.
  • the section selection unit 35 performs, for example, band pass filtering processing on the graph G1 to extract a waveform from which noise is removed as illustrated in the graph G2 of FIG. 8.
  • the vertical axis represents the signal amplitude from which noise has been removed.
  • the interval selection unit 35 may specify, for example, a reference point of the extracted waveform.
  • the section selection unit 35 specifies, for example, a zero crossing point at which the signal amplitude of the extracted waveform is zero.
  • the section selection unit 35 specifies, for example, the time of the zero crossing point as a reference point for setting the section of the extracted waveform.
  • the section selection unit 35 converts the zero cross point Z1 at which the amplitude changes from negative to positive and the amplitude changes from positive to negative. Identify the zero crossing point Z2.
  • the interval selection unit 35 may calculate, for example, an autocorrelation coefficient for each interval waveform between the reference points.
  • the section selection unit 35 calculates, for example, the autocorrelation coefficient by the least square method of the error between the two superimposed waveforms, for example, the coincidence of the waveform when the reference segment waveform and the other segment waveform are superimposed. Do.
  • the section selection unit 35 calculates the autocorrelation coefficient for one section waveform, the present invention is not limited to this, and the autocorrelation coefficient may be calculated for a plurality of section waveforms.
  • the section selection unit 35 repeats, for example, the process of calculating an autocorrelation coefficient for each section waveform between the reference points with respect to all the reference points.
  • FIG. 9 is a diagram showing an example of calculation processing of an autocorrelation coefficient of a pulse waveform.
  • the section selection unit 35 moves the range S1 of the window width U including the four section waveforms by the shift width ⁇ and superimposes it on the different range S2 to calculate the degree of coincidence of the graph.
  • FIG. 10 is a diagram showing an example of the calculation result of the autocorrelation coefficient.
  • the numerical value C1 indicates the autocorrelation coefficient with the reference section waveform.
  • section waveforms having an autocorrelation coefficient close to 1 are similar to each other, and the difference from the reference section waveform becomes larger as the autocorrelation coefficient approaches 0.
  • the section selecting unit 35 selects a section waveform to be output based on the calculated autocorrelation coefficient.
  • the section selection unit 35 selects, for example, a section whose autocorrelation coefficient is equal to or greater than a predetermined threshold value ⁇ .
  • a predetermined threshold value ⁇ For example, in the calculation result of the autocorrelation coefficient as shown in FIG. 11, the interval selection unit 35 selects an interval waveform whose autocorrelation coefficient is “0.5” or more as an interval waveform to be output.
  • the section selection unit 35 may set the threshold value ⁇ so that, for example, a plurality of section waveforms are selected.
  • the normalization unit 36 normalizes the selected plurality of interval waveforms based on the model.
  • FIG. 11 is a diagram illustrating an example of the normalization process and the statistical process in the first embodiment.
  • the standardization unit 36 is an example of a standardization processing unit.
  • the normalization unit 36 superimposes the plurality of selected section waveforms as shown in the graph G5 of FIG.
  • the normalization unit 36 normalizes, for example, the time width of the superimposed interval waveform based on the pulse wave model 21.
  • the normalization unit 36 may use, for example, an average pulse wave time interval obtained from the zero crossing point in the past 10 seconds as the time width.
  • the standardization unit 36 outputs, to the output unit 37, a plurality of standardized section waveforms as shown in the graph G6 of FIG.
  • the output unit 37 performs statistical processing on the normalized section waveform, and outputs the processing result.
  • the output unit 37 calculates, for example, an average value of a plurality of standardized section waveforms as illustrated in a graph G6 of FIG.
  • the output unit 37 may calculate the median value of the plurality of standardized section waveforms. Then, the output unit outputs a statistically processed waveform as shown in the graph G7 of FIG. 11 as a processing result.
  • FIG. 12 is a flowchart illustrating an example of pulse wave calculation processing in the first embodiment.
  • the acquisition unit 31 of the calculation device 10 stands by until an instruction to start the pulse wave calculation process is received through, for example, an operation unit (not shown) (S10: No).
  • the acquisition unit 31 executes a pulse wave acquisition process (S11).
  • FIG. 13 is a flowchart illustrating an example of pulse wave acquisition processing according to the first embodiment.
  • the acquisition unit 31 activates a sensor 11 such as a photoelectric pulse wave sensor (S110), and acquires a sensor signal (S111).
  • the acquisition unit 31 repeats the process as long as the next data is received from the sensor 11 (S112: Yes).
  • the acquiring unit 31 does not acquire signal data from the sensor 11 (S112: No)
  • the acquiring unit 31 stops the sensor 11 (S114), and returns to the process of FIG.
  • the section selection unit 35 filters noise from the waveform as shown in the graph G1 of FIG. 8 to generate an extracted waveform as shown in the graph G2 of FIG. 8 (S12). Then, the section selection unit 35 executes the reference point identification process (S13).
  • FIG. 14 is a flowchart illustrating an example of the reference point identification process according to the first embodiment.
  • the section selection unit 35 specifies a zero crossing point as shown in the graph G3 from the extracted waveform as shown in the graph G2 of FIG. 8 (S130). Then, the section selection unit 35 outputs the identified zero cross point (S131), and returns to the processing of FIG.
  • FIG. 15 is a flowchart illustrating an example of the correlation calculation process according to the first embodiment.
  • the section selecting unit 35 specifies an extraction data range which is a section to be subjected to calculation of the autocorrelation coefficient (S140).
  • the section selection unit 35 calculates an autocorrelation coefficient between the extraction data range and another data range (S141).
  • the section selection unit 35 identifies the maximum correlation value among the autocorrelation coefficients between the extracted data range and the other data range (S 142), and shifts the distance to the data range corresponding to the maximum correlation value ⁇ Is calculated (S143).
  • the section selection unit 35 determines whether there is a next reference point that has not been processed (S144). If the section selection unit 35 determines that there is a next reference point (S144: Yes), the process returns to S140 and repeats. On the other hand, when it is determined that the phase relationship calculation process has been completed for all the reference points (S144: No), the section selection unit 35 returns to the process of FIG.
  • FIG. 16 is a flowchart of an example of the section selection process according to the first embodiment. As shown in FIG. 16, the section selecting unit 35 specifies a target section (S150). Next, the section selection unit 35 determines whether the correlation value of the section is equal to or more than the threshold value ⁇ (S151).
  • the section selection unit 35 determines that the correlation value of the section is greater than or equal to the threshold value ⁇ (S151: Yes), the section selection unit 35 selects the section as a section to be standardized (S152), and proceeds to S153. On the other hand, when it is determined that the correlation value of the section is less than the threshold value ⁇ (S151: No), the section selection unit 35 proceeds to S153 without selecting the section.
  • the section selection unit 35 determines whether there is a section that has not been processed (S153). If the section selection unit 35 determines that there is a section that has not been processed (S153: Yes), the process returns to S150 to repeat the processing. On the other hand, when it is determined that the processing has been completed for all the sections (S153: No), the section selecting unit 35 outputs the selected section to the standardization section 36 (S154), and returns to the processing of FIG.
  • FIG. 17 is a flowchart of an example of the waveform normalization process according to the first embodiment.
  • the normalization unit 36 acquires the time width and the amplitude of the selected section (S160).
  • the normalization unit 36 refers to, for example, a waveform model such as the pulse wave model 21 (S161).
  • the normalization unit 36 normalizes the time width or the amplitude using the waveform model (S162).
  • the standardization unit 36 determines whether there is a section that has not been processed (S163). If the normalization unit 36 determines that there is a section that has not been processed (S163: Yes), the process returns to S162 and repeats the processing. On the other hand, when determining that the processing has been completed for all the sections (S163: No), the normalization section 36 outputs the normalized section waveform to the output section 37, and returns to the processing of FIG.
  • FIG. 18 is a flowchart illustrating an example of the output process in the first embodiment.
  • the output unit 37 acquires a standardized section waveform (S170), and executes statistical processing such as averaging processing and median calculation (S171). Then, the output unit 37 outputs the processing result through the display unit (not shown) or the like (S172), returns to the processing of FIG. 12, and ends the processing.
  • the calculation apparatus 10 in the present embodiment acquires the first pulse waveform of the subject, and from the first pulse waveform or the second waveform extracted from the first pulse waveform, Select one or more interval waveforms.
  • the calculation apparatus normalizes at least one of the time width and the amplitude of the segment waveform based on the model.
  • the calculation device 10 uses, as a model, a Windkessel model (model of ventricular volume) that reproduces a pulse wave, which is expressed by a function that is convex upward and monotonically increasing.
  • the calculation device 10 can accurately acquire the pulse waveform.
  • the calculation device 10 acquires, for example, a signal acquired from a subject by a photoelectric pulse wave sensor as a first pulse waveform.
  • the calculation device 10 may calculate and output an average value or a median value of a plurality of standardized section waveforms. As a result, it is possible to detect the pulse wave with high accuracy by suppressing the variation of each section waveform.
  • the calculation device 10 filters noise from the first pulse waveform, extracts a second waveform, specifies a reference point of the waveform, and calculates an autocorrelation coefficient of the section waveform between the reference points.
  • the calculation device 10 is any one of a plurality of section waveforms specified by the reference point from the first pulse waveform or the second waveform, in which the maximum value of the autocorrelation coefficient is equal to or more than a predetermined threshold.
  • the above section waveform may be selected. This makes it possible to select a plurality of section waveforms that are less affected by noise.
  • calculation device 10 may extract the second waveform by performing band pass filtering on the first pulse waveform in the range of frequencies that can be obtained by the pulse wave. Thereby, since the noise is removed from the pulse waveform, the pulse wave can be detected accurately.
  • the calculation device 10 may specify a point at which the amplitude value of the second waveform crosses a zero value as a reference point.
  • the base point of the pulse wave can be easily determined without using the R wave or the like acquired from the electrocardiogram sensor.
  • the calculation device 10 may calculate the maximum value of the autocorrelation coefficient and the shift width of the time from the reference point of the section waveform to the reference point of the section waveform corresponding to the maximum value. As a result, it is possible to superimpose a plurality of section waveforms having high autocorrelation coefficients, and to suppress variation among section waveforms.
  • calculation device 10 explained composition which uses a signal acquired from a photoelectric pulse wave sensor, an embodiment is not restricted to this.
  • the calculation device may be configured to extract a luminance signal from an image captured by a camera or the like to calculate a pulse wave signal.
  • FIG. 19 is a diagram illustrating an example of the calculation device in the second embodiment.
  • the same parts as the parts shown in the above-described drawings are denoted by the same reference numerals, and redundant description will be omitted.
  • the calculation device 50 in the present embodiment has a camera 12, a storage unit 20, and a control unit 60.
  • the camera 12 is a non-contact sensor such as the camera 121 shown in FIG. 2, for example, and acquires an image obtained by photographing a subject.
  • the control unit 60 is a processing unit that controls the entire calculation device 50, and is, for example, a processor.
  • the control unit 60 includes an acquisition unit 61, a waveform extraction unit 62, a reference point identification unit 63, a correlation calculation unit 64, a section selection unit 65, a normalization unit 36, and an output unit 37.
  • the acquisition unit 61, the waveform extraction unit 62, the reference point identification unit 63, the correlation calculation unit 64, and the section selection unit 65 are also an example of an electronic circuit included in the processor and an example of a process executed by the processor.
  • the acquisition unit 61 acquires a luminance signal from the image captured by the camera 12 and stores the luminance signal in the signal storage unit 22.
  • the waveform extraction unit 62 extracts a waveform obtained by filtering noise from the acquired luminance signal.
  • the waveform extraction unit 62 extracts waveforms by performing statistical processing for each wavelength component on each pixel value of an image obtained by photographing a subject, which is stored in the signal storage unit 22, for example.
  • the waveform extraction unit 62 is an example of an extraction unit.
  • the waveform extraction unit 62 may extract the waveform using the green component of the pixel value. Also, the waveform extraction unit 62 may filter the pulse waveform using a region calculated from the red component and the green component of the pixel value as a noise region.
  • the reference point identification unit 63 executes, for example, a reference point identification process as shown in S13 of FIG. 12 among the processes executed by the section selection unit 35 in the first embodiment.
  • the reference point identification unit 63 outputs the identified reference point to the correlation calculation unit 64.
  • the correlation calculating unit 64 executes, for example, a correlation calculating process as shown in S14 of FIG. 12 among the processes performed by the section selecting unit 35 in the first embodiment.
  • the correlation calculation unit 64 outputs the calculated autocorrelation coefficient to the section selection unit 65.
  • the section selecting unit 65 executes, for example, a section selecting process as shown in S15 of FIG. 12 among the processes executed by the section selecting unit 35 in the first embodiment.
  • FIG. 20 is a flowchart illustrating an example of pulse wave calculation processing according to the second embodiment.
  • the same reference numerals as in the steps shown in FIGS. 12 to 18 denote the same steps, so detailed description will be omitted.
  • FIG. 21 is a flowchart of an example of the luminance waveform acquisition process according to the second embodiment.
  • the acquisition unit 61 activates the camera 12 (S210), and detects a face from the captured image (S211). Next, the acquisition unit 61 averages the detected area (S212), and extracts a luminance signal (S213).
  • the acquisition unit 61 repeats the process as long as the next data is received from the camera 12 (S214: Yes).
  • the acquisition unit 61 stops the camera 12 (S215), and returns to the process of FIG.
  • FIG. 22 is a flowchart of an example of the waveform filtering process according to the second embodiment.
  • the waveform extraction unit 62 acquires a luminance waveform from the signal storage unit 22 (S220). Next, the waveform extraction unit 62 extracts a noise area from the luminance waveform (S221). Then, the waveform extraction unit 62 extracts a pulse wave region from the luminance waveform excluding the noise waveform (S222). Thereafter, the waveform extraction unit 62 calculates the extracted waveform (S223), and returns to the process of FIG.
  • the calculation apparatus 50 in the present embodiment may acquire the luminance signal extracted from the image obtained by photographing the subject as the first pulse waveform.
  • the pulse wave can be accurately calculated using a general user terminal such as a smartphone.
  • the calculation apparatus 50 may extract the second waveform by performing statistical processing for each wavelength component on each pixel value of the image obtained by capturing the subject. Thereby, the pulse wave region can be extracted more accurately.
  • the calculation device 10 is a device integrated with a sensor
  • the present invention is not limited to this, and the main body of the calculation device 10 does not have a sensor, and is configured to obtain a signal from an external photoelectric pulse wave sensor or the like through an interface. It may be Similarly, the main body of the calculation apparatus 50 may not have the camera 12 and may be configured to acquire a luminance signal from an external camera or the like through an interface.
  • the configuration has been described in which the zero crossing point at which the amplitude value of the extracted waveform crosses the zero value is specified as the reference point, but the embodiment is not limited to this.
  • the calculation device 10 may specify at least one of the maximum point and the minimum point in the vicinity of the zero crossing point as the reference point as the reference point.
  • FIG. 23 is a diagram illustrating an example of the reference point identification process according to the third embodiment.
  • the section selection unit 35 of the calculation device 10 may specify the local maximum point Smax near the zero cross point Z3 and the local minimum point Smin near the zero cross point Z3 as the reference points.
  • the calculation device 10 specifies at least one of the local maximum point and the local minimum point near the point where the amplitude value of the second waveform crosses the zero value as the reference point. It is also good. This makes it possible to easily determine the base point of the pulse wave even when the variation of the zero crossing point is large.
  • the calculation apparatus 10 selects the section waveform from at least one of the signal acquired by the photoplethysmograph sensor and the luminance signal extracted from the image, instead of the extraction waveform in which the noise is filtered. It is also good. As a result, when the influence of noise due to a disturbance factor or the like is small, the processing load for pulse wave calculation can be reduced.
  • the normalization unit 36 may normalize the amplitude instead of the time width, or may normalize both the time width and the amplitude.
  • a plurality of pulse wave models may be used depending on the age, sex, and the like of the subject.
  • the calculation device 10 may be configured to further estimate the stress index, the blood vessel age, the blood pressure and the like of the subject using the pulse waveform calculated in each embodiment.
  • the calculation device 10 may perform linear interpolation on the acquired signal amplitude. Thus, even if the number of sampled signal amplitudes is small, it is possible to calculate the pulse waveform accurately.
  • part of the process described as being automatically performed can be manually performed.
  • all or part of the processing described as being performed manually may be performed automatically by a known method.
  • the processing procedures, control procedures, specific names, and information including various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified.
  • each component of each device illustrated is functionally conceptual, and does not necessarily have to be physically configured as illustrated. That is, the specific form of distribution and integration of each device is not limited to the illustrated one. That is, all or part of them can be configured to be functionally or physically dispersed and integrated in arbitrary units in accordance with various loads, usage conditions, and the like.
  • the correlation calculation unit 64 and the section selection unit 65 shown in FIG. 19 may be integrated.
  • the section selection unit 35 illustrated in FIG. 3 may be distributed to the waveform extraction unit 32, the reference point identification unit 33, the correlation calculation unit 34, and the section selection unit 65.
  • all or any part of each processing function performed in each device may be implemented by a processor and a program analyzed and executed by the processor, or may be implemented as wired logic hardware.
  • FIG. 24 is a diagram illustrating an example of a computer that executes a pulse wave calculation program.
  • the calculation device 10 will be described below as an example, the same applies to the corresponding devices in the second to third embodiments.
  • the computer 100 includes an operation unit 110 a, a sensor 110 b, a display 120, and a communication unit 130.
  • the computer 100 further includes a processor 150, a read only memory (ROM) 160, an external storage device 170, and a random access memory (RAM) 180.
  • the components 110 to 180 are connected via a bus 140.
  • Examples of the RAM 180 include memories such as synchronous dynamic random access memory (SDRAM) and flash memory.
  • Examples of the processor 150 include a central processing unit (CPU), a digital signal processor (DSP), a field programmable gate array (FPGA), and a programmable logic device (PLD).
  • CPU central processing unit
  • DSP digital signal processor
  • FPGA field programmable gate array
  • PLD programmable logic device
  • a pulse wave calculation program 170a that exerts the same function as each functional unit shown in the first to third embodiments is stored in advance.
  • the pulse wave calculation program 170 a may be integrated or separated as appropriate as each component shown in FIG. 3 or 19. That is, it is not necessary for all data to be stored in the external storage device 170 at all times in the external storage device 170, and only data necessary for processing may be stored in the external storage device 170.
  • the processor 150 reads out the pulse wave calculation program 170 a from the external storage device 170 and develops it in the RAM 180.
  • the pulse wave calculation program 170a functions as a pulse wave calculation process 180a.
  • the pulse wave calculation process 180a appropriately expands various data read from the external storage device 170 in an area allocated to itself on the RAM 180, and executes various processes based on the expanded various data.
  • the pulse wave calculation process 180a includes the processing executed by each functional unit shown in FIG. 3 or FIG. 19, for example, the processing shown in FIG. 12 to FIG. 18 and FIG. 20 to FIG. Further, in each processing unit virtually realized on the processor 150, all the processing units need not always operate on the processor 150, and only the processing units necessary for the processing may be virtually realized.
  • the pulse wave calculation program 170a described above does not have to be stored in the external storage device 170 or the ROM 160 from the beginning.
  • each program is stored in a "portable physical medium" inserted into the computer 100.
  • a portable physical medium any medium such as a flexible disk, a so-called FD, a CD-ROM (Compact Disc Read Only Memory), a DVD (Digital Versatile Disc), a magneto-optical disc, an IC (Integrated Circuit) card can be adopted.
  • the computer 100 may acquire each program from these portable physical media and execute it.
  • each program is stored in another computer or server device connected to the computer 100 via a public line, the Internet, LAN, WAN, etc., and the computer 100 acquires and executes each program from these. You may

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Abstract

Selon la présente invention, une forme d'onde d'onde d'impulsion est acquise avec précision. Ce dispositif de calcul (10) comprend une unité d'acquisition (31) qui acquiert une première forme d'onde d'impulsion d'un sujet. Le dispositif de calcul comprend une unité de sélection de section (35) qui sélectionne une ou plusieurs formes d'onde de section à partir de la première forme d'onde d'onde d'impulsion ou d'une seconde forme d'onde extraite de la première forme d'onde d'onde d'impulsion. De plus, le dispositif de calcul comporte une unité de normalisation (36) qui normalise, sur la base d'un modèle, au moins l'une parmi la largeur temporelle et l'amplitude de la forme d'onde de section. En outre, le dispositif de calcul traite statistiquement la forme d'onde de section normalisée et délivre le résultat traité.
PCT/JP2018/002170 2018-01-24 2018-01-24 Dispositif de calcul d'onde d'impulsion, méthode de calcul d'onde d'impulsion et programme de calcul d'onde d'impulsion WO2019146025A1 (fr)

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JP2019567451A JP6947227B2 (ja) 2018-01-24 2018-01-24 脈波算出装置、脈波算出方法及び脈波算出プログラム

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JP2021041070A (ja) * 2019-09-13 2021-03-18 サクサ株式会社 脈波解析装置及び脈波解析プログラム
JP2021127750A (ja) * 2020-02-14 2021-09-02 株式会社島津製作所 ポンプ監視装置および真空ポンプ
JP7387802B2 (ja) 2022-04-27 2023-11-28 キヤノン株式会社 検査装置、検査方法及びプログラム

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JP2014176584A (ja) * 2013-03-15 2014-09-25 Fujitsu Ltd 信号処理装置、信号処理方法及び信号処理プログラム
JP2014221172A (ja) * 2013-05-14 2014-11-27 富士通株式会社 脈波検出装置、脈波検出プログラム、脈波検出方法及びコンテンツ評価システム
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JP2021041070A (ja) * 2019-09-13 2021-03-18 サクサ株式会社 脈波解析装置及び脈波解析プログラム
JP7272196B2 (ja) 2019-09-13 2023-05-12 サクサ株式会社 脈波解析装置及び脈波解析プログラム
JP2021127750A (ja) * 2020-02-14 2021-09-02 株式会社島津製作所 ポンプ監視装置および真空ポンプ
JP7480517B2 (ja) 2020-02-14 2024-05-10 株式会社島津製作所 ポンプ監視装置および真空ポンプ
JP7387802B2 (ja) 2022-04-27 2023-11-28 キヤノン株式会社 検査装置、検査方法及びプログラム

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