RRI measurement device, RRI measurement method and RRI measurement program

Abstract

This RRI measurement device comprises: an R wave detection unit (223) which detects a peak point of an R wave from a sampling data series of an electrocardiogram signal of a subject; an R wave detection unit (224) which estimates a waveform near the R wave of the electrocardiogram signal on the basis of the peak point of the R wave detected by the R wave detection unit (223) and sampling data of the electrocardiogram signal before and after of the peak point, and redetects the peak point of the R wave on the basis of the estimated waveform; and an RRI calculation unit (225) which calculates an RRI from the time series data of the peak point of the R wave detected by the R wave detection unit (224).

Description

[Technical field]

[0001] The present invention relates to an RRI measurement device, an RRI measurement method, and an RRI measurement program for detecting an RRI, which is the interval between two adjacent R waves, from an electrocardiogram signal. [Background technology]

[0002] The RR interval (RRI) in an electrocardiogram (ECG) is used for heart rate variability analysis, arrhythmia diagnosis, detection of cardiac disease and autonomic nervous system disorders, etc. With the recent development of technology, it has become possible to obtain ECG and detect RRI in real time using wearable devices (see Non-Patent Document 1).

[0003] For example, an application has been proposed in which a wearable device attached to clothing acquires time-series data of ECG signals while the clothing is being worn, calculates the heart rate and RRI from the ECG signal, and wirelessly transmits the resulting data set to an external terminal such as a smartphone (see Patent Document 1).

[0004] Generally, the accuracy of detecting the RRI from an ECG signal depends on the sampling rate of the ECG signal, and in heart rate variability analysis, a sampling rate of 2 msec or more, that is, 500 samples / sec or more, is required. On the other hand, when acquiring signals at such high sampling rates in a wearable device, there is a problem that the amount of calculation processing increases and the power consumption of the device increases. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Re-tabled publication No. 2016-24495 [Non-patent literature]

[0006] [Non-Patent Document 1] M. Elgandi et al., “Revisiting QRS Detection Methodologies for Portable, Wearable, Battery-Operated, and Wireless ECG Systems”, PLOS ONE, Vol. 9, No. 1, e84018, 2014, DOI: 10.1371 / journal.pone.0084018 Summary of the Invention [Problem to be solved by the invention]

[0007] The present invention has been made to solve the above-mentioned problems, and aims to provide an RRI measurement device, an RRI measurement method, and an RRI measurement program that can accurately measure a subject's RRI from sampling data of an electrocardiogram signal acquired at a low sampling rate. [Means for solving the problem]

[0008] The RRI measurement device of the present invention includes a first detection unit configured to detect an R-wave peak point from a sampling data sequence of an electrocardiogram signal of a subject, a second detection unit configured to obtain an approximation curve that fits three points, the R-wave peak point detected by the first detection unit and the electrocardiogram signal sampling points before and after the peak point, and to re-detect the R-wave peak point based on the approximation curve, and a time T of the R-wave peak point detected by the second detection unit. peak A calculation unit configured to calculate the RRI from the time series data, the first detection unit calculates a time difference value for each piece of sampling data from a sequence of sampling data of the electrocardiogram signal, and detects a positive peak point immediately before a negative peak point of the time difference value as a peak point of the R wave; The second detection unit detects the approximate curve A=aT when the value of the sampling data of the electrocardiogram signal is A and the sampling time is T. 2 The coefficients a, b, and c of +bT+c are calculated, and the time T[n]-b / 2a of the peak point of the approximation curve is calculated based on the time T[n] of the peak point of the R wave detected by the first detection unit and the coefficients a and b. peak The present invention is characterized in that the calculation is performed as follows:

[0009] The RRI measurement method of the present invention includes a first step of detecting an R-wave peak point from a sampling data sequence of an electrocardiogram signal of a subject, a second step of finding an approximation curve that fits the R-wave peak point detected in the first step and three sampling points of the electrocardiogram signal before and after the peak point, and detecting the R-wave peak point again based on the approximation curve, and a second step of finding the time T of the R-wave peak point detected in the second step. peak and a third step of calculating the RRI from the time series data, the first step includes a step of calculating a time difference value for each piece of sampling data from a sampling data sequence of the electrocardiogram signal, and detecting a positive peak point immediately before a negative peak point of the time difference value as a peak point of the R wave; In the second step, when the value of the sampling data of the electrocardiogram signal is A and the sampling time is T, the approximation curve A=aT 2 The coefficients a, b, and c of +bT+c are calculated, and the time T[n]-b / 2a of the peak point of the approximation curve is calculated based on the time T[n] of the peak point of the R wave detected in the first step and the coefficients a and b. peak The method is characterized by including a step of calculating: Further, the RRI measurement program of the present invention is characterized in that it causes a computer to execute each of the above steps. Effect of the Invention

[0010] According to the present invention, by providing a first detection unit, a second detection unit, and a calculation unit, it is possible to accurately measure the RRI of a subject from sampling data of an electrocardiogram signal acquired at a low sampling rate. Since it is not necessary to acquire an electrocardiogram signal at a high sampling rate, the power consumption of the RRI measurement device can be reduced. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing a configuration of an RRI measurement device according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a functional block diagram of an MCU of an RRI measurement device according to an embodiment of the present invention. [Diagram 3]FIG. 3 is a flowchart illustrating the operation of the MCU of the RRI measurement device according to the embodiment of the present invention. [Figure 4] FIG. 4 is a waveform diagram showing an example of an ECG signal. [Figure 5A-5B] 5A and 5B are diagrams for explaining the processing of the R wave detection unit of the RRI measurement device according to an embodiment of the present invention. [Figure 6] FIG. 6 is a block diagram showing an example of the configuration of a computer that realizes an RRI measurement device according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Fig. 1 is a block diagram showing the configuration of an RRI measurement device according to an embodiment of the present invention. The RRI measurement device includes a sensor 1, a signal processing unit 2, a storage unit 3, a communication unit 4, and a power supply unit 5. The signal processing unit 2 includes an AFE (Analog Front End) 20, an ADC (Analog Digital Converter) 21, and an MCU (Micro Control Unit) 22.

[0013] The sensor 1 detects an ECG signal of a subject. The AFE 20 amplifies the weak ECG signal detected by the sensor 1. The ADC 21 converts the ECG signal amplified by the AFE 20 into digital data at a predetermined sampling rate. Examples of the sampling rate include 125 samples / sec and 250 samples / sec.

[0014] The MCU 22 is a circuit that performs signal processing to calculate the RRI. Fig. 2 is a functional block diagram of the MCU 22. The MCU 22 functions as a data storage unit 220, a data acquisition unit 221, a filter unit 222, an R wave detection unit 223 (first detection unit), an R wave detection unit 224 (second detection unit), an RRI calculation unit 225, and a heart rate calculation unit 226.

[0015] The storage unit 3 stores the program of the MCU 22, sampled data of the ECG signal output from the ADC 21, and data calculated by the MCU 22. The data storage unit 220 of the MCU 22 adds information on the sampling time to each sampled data of the ECG signal output from the ADC 21 and stores the data in the memory unit 3 .

[0016] The communication unit 4 includes a circuit that wirelessly transmits sampled data of the ECG signal and data calculated by the MCU 22 to an external device (not shown) such as a smartphone. The power supply unit 5 is a circuit that is responsible for supplying power to the entire RRI measurement device.

[0017] 3 is a flow chart for explaining the operation of the MCU 22. The data acquisition unit 221 acquires a sampling data sequence of an ECG signal stored in the storage unit 3 (step S100 in FIG. 3).

[0018] The filter unit 222 performs filtering using an anti-aliasing filter or a band-pass filter on the sampling data string acquired by the data acquisition unit 221 (step S101 in FIG. 3).

[0019] The R-wave detection unit 223 detects the peak point of the R-wave from the filtered sampling data string (step S102 in FIG. 3). A simple method for detecting the peak point of the R-wave is to use a threshold. Specifically, the R-wave detection unit 223 detects a section in which the sampling data exceeds a predetermined threshold as an R-wave, and determines the point with the highest potential among the data exceeding the threshold as the peak point of the R-wave.

[0020] The R wave detection unit 223 may detect the peak point of the R wave using other methods. Another method is to use the time difference of the ECG signal. In this embodiment, the value (electric potential) of the sampling data of the ECG signal is A(n), and the sampling time is T(n). n is a number given to one sampling of data. It goes without saying that the larger the number n, the later the sampling time.

[0021] The R wave detection unit 223 calculates a time difference value Y(n) of the sampling data A(n) using the data A(n+1) one sampling after the sampling data A(n) and the data A(n-1) one sampling before the sampling data A(n) as follows. Y(n) = A(n+1) - A(n-1) (1)

[0022] The R-wave detection unit 223 calculates such a time difference value Y(n) for each sampling time (for each sampling data). As shown in Fig. 4, an ECG signal is made up of continuous heartbeat waveforms, and one heartbeat waveform is made up of components such as P waves, Q waves, R waves, S waves, and T waves that reflect the activities of the atria and ventricles. Therefore, in the time difference value Y(n), a peak due to a sharp change from an R wave to an S wave appears as a negative value. When the R-wave detection unit 223 detects a negative peak point in the time difference value Y(n), it regards the positive peak point immediately before this negative peak point as the peak point of the R wave.

[0023] Next, the R wave detection unit 224 estimates the waveform near the R wave of the ECG signal based on the peak point of the R wave detected by the R wave detection unit 223 and the sampling data before and after it, and detects the R wave peak point again based on the estimated waveform (FIG. 3, step S103). Specifically, the R wave detection unit 224 obtains an approximation curve (quadratic curve) like the formula (2) that fits the R wave peak point and three points of the sampling data of the ECG signal before and after it, and determines the peak of this approximation curve as the R wave peak. A=aT 2 +bT+c ···(2)

[0024] The potential of the peak point of the R wave detected by the R wave detection unit 223 is A[n], the time is T[n], the potential of the sampling point m before the peak point is A[nm], and the time is T[nm]=T[n]-mΔt (Δt is the sampling period), * The potential of the next sampling point is A[n+m * ], time is T[n+m * ]=T[n]+m *The R wave detection unit 224 detects the peak point of the R wave, the mth sampling point before the peak point, and the mth sampling point before the peak point. * The coefficients a, b, and c of the approximation curve that fits the sample points are calculated as follows:

[0025]

number

[0026] 5A and 5B are diagrams for explaining the processing of the R wave detection unit 224. Fig. 5A is a diagram showing an example of a sampling data string of an ECG signal, and Fig. 5B is an enlarged diagram of the section from 0.95 seconds to 1.05 seconds in Fig. 5A. In the examples of Figs. 5A and 5B, m=m * = 1, and an approximation curve that fits the R-wave peak point and the sampling points immediately before and after it is obtained. D2 in Fig. 5B is the R-wave peak point detected by the R-wave detection unit 223, D1 is the sampling point immediately before the peak point D2, and D3 is the sampling point immediately after the peak point D2. The approximation curve L can be expressed as in equation (2).

[0027] Once the coefficients a, b, and c of the approximation curve L are found, the peak point D of the approximation curve L is peak This peak point D peak The time of the peak point D2 of the R wave detected by the R wave detection unit 223 is shifted by −b / 2a from the time T[n] of the peak point D2 of the R wave detected by the R wave detection unit 223. peak The time of the peak of the R wave is T peak It is calculated as follows. T peak = T[n] - b / 2a (4)

[0028] The R wave detection unit 224 performs the above process for each peak point of the R wave detected by the R wave detection unit 223. peak Time T peak The time series data of the potential A is stored in the storage unit 3. The peak point of the approximation curve may be calculated by other methods.

[0029] Next, the RRI calculation unit 225 calculates the peak point D peak Time T peak From the time series data, two adjacent time points T peak The RRI calculation unit 225 calculates the time interval between the peak points D peak The calculated RRI time series data is stored in the storage unit 3. The RRI calculation unit 225 may calculate an average value of the RRI in addition to the RRI.

[0030] The heart rate calculation section 226 calculates an instantaneous heart rate X (beats / min) for each RRI based on the RRI calculated by the RRI calculation section 225 (step S105 in FIG. 3). X=60000 / RRI (5)

[0031] The calculated time series data of the instantaneous heart rate X is stored in the storage unit 3. The heart rate calculation unit 226 may calculate an average value of the instantaneous heart rate X in addition to the instantaneous heart rate X.

[0032] The communication unit 4 wirelessly transmits the sampling data sequence of the ECG signal, the time series data of the RRI and the average value of the RRI calculated by the RRI calculation unit 225, and the time series data of the instantaneous heart rate X and the average value of the instantaneous heart rate X calculated by the heart rate calculation unit 226 to an external device such as a smartphone.

[0033] In this way, in this embodiment, the RRI and heart rate of a subject can be accurately measured from sampling data of an ECG signal acquired at a low sampling rate, such as 125 samples / sec or 250 samples / sec. In this embodiment, since it is not necessary to acquire an ECG signal at a high sampling rate of 500 samples / sec or more, the power consumption of the RRI measurement device can be reduced.

[0034] In this embodiment, the peak of the R wave is detected after filtering the sampling data string of the ECG signal, but the filter unit 222 is not an essential component of the present invention.

[0035] The storage unit 3 and MCU 22 described in this embodiment can be realized by a computer equipped with a CPU (Central Processing Unit), a storage device, and an interface, and a program that controls these hardware resources. An example of the configuration of this computer is shown in FIG. 6. The computer includes a CPU 200, a storage device 201, and an interface device (hereinafter, abbreviated as I / F) 202. The ADC 21, the communication unit 4, and the like are connected to the I / F 202. In such a computer, an RRI measurement program for realizing the RRI measurement method of the present invention is stored in the storage device 201. The CPU 200 executes the processing described in this embodiment in accordance with the program stored in the storage device 201. It is also possible to provide the program through a network. [Industrial Applicability]

[0036] The present invention can be applied to a technique for measuring RRI. [Explanation of symbols]

[0037] 1...sensor, 2...signal processing unit, 3...memory unit, 4...communication unit, 5...power supply unit, 20...AFE, 21...ADC, 22...MCU, 220...data storage unit, 221...data acquisition unit, 222...filter unit, 223, 224...R wave detection unit, 225...RRI calculation unit, 226...heart rate calculation unit.

Claims

1. A first detector configured to detect an R-wave peak point from a sampling data sequence of an electrocardiogram signal of a subject; a second detection unit configured to obtain an approximation curve that fits three points, the peak point of the R wave detected by the first detection unit and the sampling points of the electrocardiogram signal before and after the peak point, and to detect the peak point of the R wave again based on the approximation curve; The time T of the peak point of the R wave detected by the second detection unit ｐｅａｋ A calculation unit configured to calculate an RRI from the time series data of the first detection unit calculates a time difference value for each piece of sampling data from a sequence of sampling data of the electrocardiogram signal, and detects a positive peak point immediately before a negative peak point of the time difference value as a peak point of the R wave; The second detection unit detects the approximate curve A=aT, where A is a value of the sampling data of the electrocardiogram signal and T is a sampling time. ２ and calculating coefficients a, b, and c of the R-wave peak point time T[n]-b / 2a of the approximation curve based on the R-wave peak point time T[n] detected by the first detection unit and the coefficients a and b. ｐｅａｋ The RRI measuring device is characterized in that it calculates the RRI as follows.

2. 2. The RRI measurement device according to claim 1, a filter unit configured to perform anti-aliasing filtering or band-pass filtering on the sampling data sequence of the electrocardiogram signal, the filter unit being disposed in front of the first and second detection units; The RRI measuring device according to the present invention is characterized in that the first and second detection units detect peak points of R waves using the sampling data string processed by the filter unit.

3. A first step of detecting an R-wave peak point from a sampling data sequence of an electrocardiogram signal of a subject; a second step of finding an approximation curve that fits the three points of the R-wave peak point detected in the first step and the electrocardiogram signal sampling points before and after the peak point, and re-detecting the R-wave peak point based on the approximation curve; The time T of the peak point of the R wave detected in the second step ｐｅａｋ and a third step of calculating an RRI from the time series data of the first step includes a step of calculating a time difference value for each piece of sampling data from a series of sampling data of the electrocardiogram signal, and detecting a positive peak point immediately before a negative peak point of the time difference value as a peak point of the R wave; In the second step, when the value of the sampling data of the electrocardiogram signal is A and the sampling time is T, the approximation curve A=aT ２ The coefficients a, b, and c of the formula (1) are calculated based on the time T[n] of the peak point of the R wave detected in the first step and the coefficients a and b, and the time T[n]-b / 2a of the peak point of the approximation curve is calculated based on the time T[n] of the peak point of the R wave detected in the first step. ｐｅａｋ 4. A method for measuring an RRI comprising the steps of:

4. 4. An RRI measurement program for causing a computer to execute each step according to claim 3.

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