JPH07284482A - Method and apparatus for analyzing heartbeat fluctuation waveform - Google Patents

Abstract

PURPOSE:To automatically eliminate or suppress heatbeat fluctuation waveform data containing arrhythmia exerting effect on the spectrum analyzing result of an HF component becoming the investigation object of HRV in the analysis of heartbeat fluctuation waveform due to a hearthbeat interval. CONSTITUTION:The original heartbeat fluctuation waveform is formed from a heartbeat interval and, further, the adjacent interval difference of the original heartbeat fluctuation waveform is calculated to form a relative displacement heartbeat fluctuation waveform or a 1/f fluctuation component waveform is formed from the original heartbeat fluctuation waveform to form a waveform wherein the 1/f fluctuation component waveform is subtracted from the original heartbeat fluctuation wavefonn. Next, the average value and standard deviation of the formed waveform part are calculated and an abnormal judge standard value is determined from the average value and the standard deviation and, when the waveform part is larger than the abnormal judge standard value, arrhythmia is judged and the waveform part is replaced with the value received within the normal distribution range thereof or the original heartbeat fluctuation waveform part is replaced with the average value of the predetermined range thereof and the frequency component thereof is estimated.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and apparatus for analyzing a heartbeat fluctuation waveform, and more particularly to an R wave of an electrocardiogram (voltage pulse corresponding to contraction of a ventricle, a voltage pulse having high frequency and easy detection).
The present invention relates to a method and an apparatus for analyzing a heartbeat fluctuation waveform. It should be noted that the present invention is naturally applicable to the case of using data capable of extracting a heartbeat interval such as a pulse wave and a peak value of heart sound instead of the R wave of the electrocardiogram.

By analyzing a heartbeat variability waveform generated from heartbeat intervals, an index called a heartbeat variability index (hereinafter sometimes abbreviated as HRV) can be obtained.

This HRV reflects the activity level of the sympathetic / parasympathetic nervous system, and has a low frequency (L) in its frequency component.
F) component (or frequency component of 0.05 to 0.15 cycle / beat called MWSA component), high frequency (HF) component (or frequency component of 0.15 to 0.45 cycle / beat called RSA component), etc. should be examined. It has been suggested that quantification of mental work load, mental work load, arousal level, and tension level can be performed, and it is known as a medically highly valuable index.

That is, the LF component is a component important because the blood pressure variability component reflecting the sympathetic nervous system has a low frequency, and its power is an increase in mental tension and an orthostatic stimulus ( It is recognized as increasing due to changes in posture). The HF component is so called because the respiratory variability component has a high frequency, and it is known that the HF component has a high value in a resting state or during sleep and tends to disappear due to an increase in tension. It is what

Therefore, whether the subject is at rest or not,
In other words, there is a demand for an HRV index that can easily determine whether or not the arousal level has decreased.

[0006]

2. Description of the Related Art A conventional method and apparatus for obtaining the power spectrum (or frequency component) value used for such HRV will be described below.

First, as shown in FIG. 7, biological electrodes 21 to 23 are attached to a human body 20, and the potential of the skin surface corresponding to the heart activity of the human body 20 is applied to the electrodes 21 and 23 and the electrodes 22 and 23 by an AC amplifier 24. The differential voltage is obtained, amplified, and sent to the A / D converter 25 as output signals A and B, respectively, where they are converted into digital signals, and then the arithmetic units 26
To the potential difference between the output signals A and B in FIG.
It is recorded as an electrocardiogram as shown in (1) and its power spectral density (PSD) is obtained.

FIG. 8 shows a procedure for generating a heartbeat fluctuation waveform. First, the R wave peak time is detected in (1) of the same figure, and the R wave peak time is detected from the R wave peak time as shown in (2) of the same figure. -R interval (hereinafter abbreviated as RRI) is measured.
For example, as shown in (1) of FIG.
If I1 is 0.8 seconds, the interval RRI1 is set to "0.8" as shown in FIG.

In the following, this RRI waveform is referred to as an original heartbeat variability waveform in order to distinguish it from a heartbeat variability waveform which has been subjected to various processes described later.

The R-wave interval RRI thus generated according to the heartbeat is linearly interpolated as shown in FIG. 3 (3), and the horizontal axis is the pulse rate and the vertical axis is the R-wave interval RRI. A heartbeat fluctuation waveform is generated.

The RRI waveform generated in this manner is used to cut out a certain section as shown in the figure, and the sampling frequency is 5 Hz.
FIG. 9 shows the power spectrum density obtained by FFT calculation (fast Fourier transform calculation) or AR (autoregressive model).

As can be seen from the power spectrum estimation diagram of FIG. 9, most of the estimated power is a drift component having a center frequency of 0 Hz, and this is due to many of the original heartbeat fluctuation waveforms shown in FIG. 8 (3). This is because it contains an aperiodic component.

For this reason, as described above, it becomes difficult to detect the LF component or the HF component (peak power) which is the original object of study as the HRV.

Therefore, in order to solve such a problem, the inventor of the present invention proposes a method and apparatus for obtaining a frequency component result with high accuracy so that differences in HRV can be compared.
It has already been disclosed in 8861.

This will be described in principle with reference to FIG.
First, R wave intervals RRI1 to RRIn are calculated from the R wave time from the electrocardiogram as shown in FIG.

After the R-wave interval is extracted in this way, the difference between adjacent RRIs is calculated this time to generate the waveform shown in FIG. 2B (hereinafter sometimes referred to as RRI 'waveform).

The thus generated RRIn-RRI (n-
By generating the waveform of 1) for a long period of time in the same manner as in FIG. 8C, a waveform RRI (n-1) with the abscissa representing the number of beats as shown in FIG. 10C is obtained.

As a result, the characteristic obtained by the spectrum calculation is as shown in FIG. 11, and due to this characteristic, the LF under the condition that the non-stationary and random transition of the heartbeat is different.
The peak power positions of the component and the HF component can be estimated relatively easily.

[0019]

The actually measured heartbeat variability waveform is not always a clean waveform, and an arrhythmia in which the heartbeat changes very rapidly may be mixed even when the subject is healthy.

On the left side of FIG. 12 (1), a heartbeat fluctuation waveform (RRI waveform) in which such an arrhythmia is mixed is shown. When this waveform data is subjected to frequency analysis as described above,
As shown on the right side of the figure, the data of the arrhythmia portion is treated as data having a large HF component.

That is, the heartbeat fluctuation waveform including this arrhythmia is
Like the heartbeat fluctuation waveform without HF components and without arrhythmia shown in (2) of the figure, it is not the frequency component of only LF components, and as shown in (3) of the figure, the same frequency component as the waveform containing many HF components. Become.

When the original heartbeat fluctuation waveform (RRI waveform) shown in FIG. 1A and the relative displacement heartbeat fluctuation waveform (RRI 'waveform) shown in FIG. 1B are generated, RR is generated.
A histogram for I has a normal distribution as shown in FIG. 13, but when an arrhythmia is mixed in the RRI waveform,
The distribution of the abnormal waveform data A, B, and C, which poses a problem in frequency analysis, is buried in the range of the normal distribution as shown in FIG. 13, which makes detection difficult.

Thus, the H that the HRV is trying to consider
The F component is a component of respiratory variability that appears greatly at rest, and in a device intended for studying the HF and LF components of HRV, there is a big problem in performing frequency analysis while including such arrhythmia data. Will occur.

Therefore, the present invention is a heartbeat variability waveform analysis method and apparatus capable of automatically deleting or suppressing heartbeat variability waveform data including an arrhythmia that affects the spectrum analysis result of the HF component subject to HRV examination. It is an object of the present invention to provide a method capable of giving a component substitute value of HRV by a method other than spectrum analysis.

[0025]

Means and Actions for Solving the Problems [1] Method of the Present Invention (No. 1): FIG. 1 As described above, the arrhythmia portion in the RRI waveform is buried in the range of the normal distribution as shown in FIG. But Figure 1
Since the points B'and C'in the arrhythmia portion in the RRI 'waveform appearing in (2) have values outside the range of the normal distribution as shown in (3) of the same figure, if the RRI' waveform is used, the arrhythmia can be detected. Easy to remove.

Therefore, according to the heartbeat fluctuation waveform analysis method of the present invention, first, the heartbeat fluctuation waveform (RRI) is calculated from the heartbeat interval.
Waveform). Then, a relative displacement heart rate variability waveform (RRI ′ waveform) is generated by obtaining the difference between adjacent RRI waveforms.

Further, the average value and standard deviation of the RRI 'waveform portion are calculated, and the abnormality determination reference value is determined from this average value and standard deviation.

The abnormality determination reference value is further compared with the RRI 'waveform portion, and when it is found that the abnormality determination reference value <RRI' waveform portion, it is determined that the heartbeat has changed abnormally, that is, arrhythmia. After replacing the RRI 'waveform portion with a value that falls within the range of the normal distribution, its frequency component is estimated.

By doing so, even if an arrhythmia is mixed in the heartbeat fluctuation waveform as shown in FIG. 1 (2),
As shown in FIG. 3C, since the arrhythmic points B ′ and C ′ deviate from the range of the normal distribution, if the abnormality determination reference value is calculated from the average value and standard deviation of the RRI ′ waveform, By comparing this with the arrhythmia points B ′ and C ′, its presence can be detected, and by substituting a value within the range of the normal distribution, RRI ′ as if there were no arrhythmia.
The waveform is obtained, and the frequency analysis in the subsequent stage becomes accurate.

[2] Device of the present invention (No. 1): As a heartbeat fluctuation waveform analysis device according to the present invention for realizing the above-mentioned method (No. 1) of the present invention, a heartbeat pickup and an output signal of the pickup are set to predetermined values. An amplifier for amplifying a frequency band, an A / D converter for converting an output signal of the amplifier into a digital signal, an original heartbeat fluctuation waveform is generated from a peak value of the digital signal, and the original heartbeat fluctuation waveform is adjacent to the waveform. Generate the relative displacement heart rate variability waveform by obtaining the interval difference,
Calculate the average value and standard deviation of the relative displacement heart rate variability waveform,
A value that falls within the normal distribution range of the relative displacement heart rate variability waveform portion as an arrhythmia when an abnormality determination reference value is determined from the average value and the standard deviation and the relative displacement heart rate variability waveform is larger than the abnormality determination reference value. And a calculation unit that estimates the frequency component.

[3] Method of the present invention (No. 2): FIG. 2 and FIG.
3 In the RRI 'waveform used in the present invention (No. 1), the originally slow change in heartbeat may be converted into a steep heartbeat change waveform.

This will be explained with reference to FIG. 2. For example, as shown in FIG. 1A, the change from RRI1 to RRI2 and the change from RRI3 to RRI are compared with the change from RRI2 to RRI3.
When a relative displacement heartbeat variability waveform is generated by calculating the adjacent interval difference of the RRI waveforms from the original heartbeat variability waveform (RRI waveform) whose change to 4 is small, the heartbeat variability is a slow rising tendency from RRI1 to RRI4. Despite this, the figure (2)
It is converted into a rapidly changing heart rate variability as shown in.

If a large amount of data is taken, such a heartbeat fluctuation waveform will become a waveform containing a large amount of HF components as shown in FIG.

Therefore, in the present invention, after the original heartbeat fluctuation waveform is generated from the heartbeat interval, the 1 / f fluctuation component waveform is generated from the original heartbeat fluctuation waveform and the 1 / f fluctuation waveform is generated from the original heartbeat fluctuation waveform.
A method of generating a waveform by subtracting the fluctuation component waveform is adopted.

This will be described with reference to FIG. 3. First, a part of the RRI waveform in the case of long-time calculation as shown in FIG. 1A is enlarged and shown in FIG. 2B. By not performing the relative displacement heart rate variability waveform from the RRI waveform but performing the low-pass filtering process or the moving smoothing process as shown in (3) of the figure, the 1 / f fluctuation component waveform (1 / f (n ) Waveform) is estimated.

Then, by subtracting the 1 / f fluctuation component waveform of FIG. 4 (4) from the original heartbeat fluctuation waveform of FIG. 1 (1), a frequency other than the HRV studied frequency as shown in FIG. 5 (5) is obtained. Heart rate variability waveform (RRI '')
Waveform) will be obtained.

Therefore, in the present invention, the average value and standard deviation of the RRI '' waveform portion generated by subtraction as described above are calculated in the same manner as the above RRI 'waveform, and the average value and the standard deviation are calculated. After determining the abnormality determination reference value from the standard deviation and replacing it with a value that falls within the normal distribution range of the RRI '' waveform portion as an arrhythmia when the RRI '' waveform portion is larger than the abnormality determination reference value, The frequency component is estimated.

Therefore, also in the case of the present invention, as shown in FIG. 1 (3), it becomes easy to detect the arrhythmic points B'and C'in the RRI '' waveform portion, and the arrhythmia is corrected and the correct frequency in the subsequent stage is corrected. Analysis is possible.

[4] Device of the present invention (No. 2): A heartbeat fluctuation waveform analyzing device according to the present invention which realizes the above-mentioned method (No. 2) of the present invention includes a heartbeat pickup and an output signal of the pickup at a predetermined frequency. An amplifier that amplifies the band,
A / D for converting the output signal of the amplifier into a digital signal
An original heartbeat fluctuation waveform is generated from a converter and a peak value of the digital signal, a 1 / f fluctuation component waveform is generated from the original heartbeat fluctuation waveform, and the 1 / f fluctuation component waveform is subtracted from the original heartbeat fluctuation waveform. Waveform is generated, an average value and a standard deviation of the subtraction waveform are calculated, an abnormality determination reference value is determined from the average value and the standard deviation, and an arrhythmia is generated when the subtraction waveform is larger than the abnormality determination reference value. Is replaced with a value that falls within the range of the normal distribution of the subtracted waveform portion, and the frequency component is then estimated.

[5] Method and Device of the Present Invention (Part 3): FIG.
4 In the above-described method and apparatus of the present invention (No. 1; No. 2), when the arrhythmia is determined, the RRI 'waveform or R
The original heart rate variability waveform (RRI waveform) portion, instead of the RI ″ waveform portion, may be replaced with the average value of the predetermined surroundings.

That is, for example, the point A of the arrhythmia in FIG.
As shown in FIGS. 4 (1) and (2) for B and C, when an average value and “0” are given, respectively, the waveform becomes discontinuous and the arrhythmia cannot be removed. As shown in (3) of the same figure, the waveform portion (point A,
The average value (A ", of a portion including B and C) in a predetermined range
By obtaining B ", C"), a continuous waveform is obtained,
As in the above case, it can be seen that the relative displacement falls within the range of the normal distribution, and the arrhythmia is eliminated.

[0042]

FIG. 5 shows a common embodiment of the heartbeat variability waveform analyzing apparatus according to the present invention. Basically, the AC amplifier section 24 and the A / A unit are provided in the same manner as the apparatus configuration shown in FIG. It is composed of a D conversion unit 25 and a calculation unit 26, and the AC amplifier unit 2
Although not shown, the input signal of 4 is obtained from the biomedical electrode attached to the human body as in FIG.

In this embodiment, the AC amplifier section 24
Is constituted by a series circuit of the operation input amplifier 1 and the bandpass filter 2, and the bandpass filter 2 is set to a pass band of 8 to 18 Hz in order to extract only the R wave.

The A / D converter 25 includes an amplifier 3 connected to the bandpass filter 2 and a sample hold circuit 4.
And an A / D converter 5 and a buffer memory 6 in series.

Further, the arithmetic unit 26 includes a RAM 8 interconnected to the data bus 7 connected to the buffer memory 6, a ROM 9 for arithmetic algorithm, a CPU 10 and these RAMs 8.
And R without being connected to the CPU 10 and passing through the CPU 10.
DMA controller 1 for storing data in AM8
1 and a crystal oscillating circuit 12 for applying a constant clock signal to the CPU 10 and the DMA controller 11.

The A / D converter 25 includes the crystal oscillator circuit 1
A frequency divider 13 for dividing the frequency of the clock signal from 2 and giving it to the A / D converter 5 is provided. The DMA controller 11 includes a sample hold circuit 4 and an A / D converter 5.
Is also controlled.

FIG. 6 shows a processing procedure of the CPU 10 shown in FIG. 5 and shows an embodiment corresponding to the above-mentioned method / apparatus (No. 1) of the present invention. The operation of the embodiment of FIG. 5 will be described with reference to the waveform diagrams of FIG. 1 and FIG.

First, the output signal from the heartbeat pickup for detecting the heartbeat intervals such as the R wave of the electrocardiogram, the pulse wave, the peak value of the heart sound, etc. is amplified by the differential input amplifier 1 in the AC amplifier section 24 and the bandpass filter 2 is also applied. At, only R wave is extracted.

The R wave is amplified by the amplifier 3 in the A / D converter 25, sampled and held by the sample hold circuit 4 under the control of the DMA controller 11, and converted into a digital signal by the A / D converter 5. , From the buffer memory 6 via the data bus 7 into the CPU 10.

When the processing is started, the CPU 10 reads the R waveform data (step S1) and detects the R wave time (step S2).

From the R wave time obtained in this way, FIG.
As shown in (2), the original heart rate variability waveforms RRI1 to RRI
n is calculated (step S3).

After extracting the R-wave interval RRI in this way, this time the difference between adjacent RRIs is calculated (step S
4), the waveform shown in FIG. 10B is generated.

RRI (n-1) -RRI generated in this way
By generating the waveform of n over a long period of time as in the case of FIG. 8C, a waveform having the horizontal axis as the number of beats as shown in FIG. 1B is obtained.

When this converted data is RRI'n, this data RRI'n is stored in the RAM 8 (step S5).

Next, the CPU 10 causes the waveform data RRI '.
From n, the average value * RRI'n (RRI in the figure
Is used as an overline, but here, * is used) and the standard deviation SRRI'n is calculated (step S
6).

[0056]

[Equation 1]

[0057]

[Equation 2]

Then, using the average value * RRI'n and the standard deviation SRRI'n, the abnormality determination reference value k is obtained by the following equation (step S7).

[0059]

[Equation 3]

However, g is a constant arbitrarily set according to the nature of the waveform, and 2.5 is usually given. Further, k is 2.5 or less when the number of waveform data is small, and 2.5 or more when the number of data is large.

Here, after the initial value of the parameter i indicating the sample point position of the RRI 'waveform is set to "1" (step S8), the process is repeated until the parameter i> n (step S9). In step S10, the data RRIi at the point i is read from the RAM 8.

Then, it is determined whether or not RRI'i ≧ k (step S11).

This determines whether or not the value of the sample point i of the RRI 'waveform exceeds the value k indicating an abnormal heartbeat change, that is, whether or not the arrhythmia is present. As a result, RR
If I′i ≧ k, this point i
RRI 'Waveform value of RAM is replaced by a predetermined value "x"
8 (step S12).

The predetermined value x in this case is normally "0", but an average value around the abnormal values A ', B', C'shown in FIG. 1 (2) may be calculated and used. As a result,
As shown in (3), the points B ′ and C ′ in the RRI ′ histogram fall within the range of normal distribution.

If RRI'i <k in step S11, the process proceeds to step S13 without executing step S12, increments the parameter i by "1" and repeats until i> n in step S9, i>n> When it becomes n, the RRI'n data is read from the RAM 8 and the process is transferred to a frequency analysis statistical processing unit (not shown) or the like.

In the above embodiment, the average value, the standard deviation, and the abnormality judgment reference value are obtained from the relative displacement heartbeat fluctuation waveform (RRI 'waveform) according to the present invention (No. 1), and the arrhythmia points are within the normal distribution range. However, when the RRI '' waveform (RRI waveform-1 / f fluctuation component waveform) of FIG. 3 (5) is used in accordance with the present invention (part 2), the control of FIG. Steps S4, S5, S6, S10, S1
This RRI ″ waveform may be replaced in steps 1 and S12.

The 1 / f fluctuation component waveform is shown in FIG.
In the RRI waveforms shown in (1) and (2), the 1 / f fluctuation component waveform can be estimated by obtaining an average value (movement smoothing value) from three-point samples as in the following equation.

[0068]

[Equation 4]

This average value can also be obtained by using a low pass filter as an analog circuit.

Further, when correcting the original heartbeat fluctuation waveform (RRI waveform) as in the present invention (part 3), the RRI 'waveform is replaced by the RRI' in step S12 of FIG.
Data replacement may be performed using a waveform as shown in FIG.

In this case, as an example, point A ″ in FIG.
Is the average value of the sample points two points before the point A shown in FIG. 1A, the point C ″ is the average value of the sample points two points after the point C, and the point B ″ is the point. The average value of A "and C" may be used.

[0072]

As described above, according to the heartbeat variability waveform analysis method and apparatus of the present invention, the original heartbeat variability waveform is generated from the heartbeat interval, and the adjacent interval difference between the original heartbeat variability waveforms is calculated. Or a relative displacement heartbeat variability waveform is obtained, or a 1 / f fluctuation component waveform is generated from the original heartbeat variability waveform and a waveform obtained by subtracting the 1 / f fluctuation component waveform from the original heartbeat variability waveform is generated, An average value and a standard deviation of the generated waveform portion are calculated, an abnormality determination reference value is determined from the average value and the standard deviation, and when the waveform portion is larger than the abnormality determination reference value, the waveform portion is regarded as an arrhythmia. Is replaced with a value that falls within the range of the normal distribution, or the original heart rate variability waveform part is replaced with an average value of the predetermined surroundings, and then the frequency component is estimated. That the LF / HF power medically examined possible HRV from the driver's heartbeat data can be estimated with high accuracy, it is possible to issue a warning, such as accurate drowsy driving.

[Brief description of drawings]

FIG. 1 is a waveform diagram for explaining the operation principle of a heartbeat fluctuation waveform analysis method and device (No. 1) according to the present invention.

FIG. 2 is a waveform chart for explaining problems of the heartbeat fluctuation waveform analysis method and device (No. 1) according to the present invention.

FIG. 3 is a waveform diagram for explaining the operation principle of the heartbeat fluctuation waveform analysis method and device (No. 2) according to the present invention.

FIG. 4 is a waveform diagram for explaining the operation principle of the heartbeat fluctuation waveform analysis method and device (No. 3) according to the present invention.

FIG. 5 is a block diagram showing a common embodiment of the heartbeat fluctuation waveform analyzing apparatus according to the present invention.

FIG. 6 is a heartbeat fluctuation waveform analyzer according to the present invention (No. 1).
It is a flowchart figure which showed the example of a calculation process in the calculating part.

FIG. 7 is a block diagram showing a power spectrum measurement system as a general heart rate variability waveform analyzer.

FIG. 8 is a waveform diagram showing a conventional heart rate variability waveform generation procedure.

FIG. 9 is a graph diagram in which a power spectrum is estimated by a conventional example.

FIG. 10 is a waveform diagram for explaining the operation principle of the heartbeat fluctuation waveform analysis method and apparatus according to Japanese Patent Application No. 5-189961.

FIG. 11 is a waveform diagram in which a power spectrum is estimated in a heartbeat fluctuation waveform analysis method and device according to Japanese Patent Application No. 5-189961.

FIG. 12 is a waveform diagram for explaining problems in the conventional example.

FIG. 13 is a characteristic graph showing an RRI histogram in a conventional example.

[Description of Reference Signs] 20 human body 21 to 23 biomedical electrode 24 AC amplifier 25 AD conversion unit 26 arithmetic unit 8 RAM 9 ROM 10 CPU In the drawings, the same reference numerals indicate the same or corresponding portions.

Claims (8)

[Claims] 1. A heartbeat variability waveform is generated from heartbeat intervals, a difference between adjacent heartbeat variability waveforms is determined to generate a relative displacement heartbeat variability waveform, and an average value of the relative displacement heartbeat variability waveform portion. And a standard deviation are calculated, an abnormality determination reference value is determined from the average value and the standard deviation, and when the relative displacement heartbeat fluctuation waveform portion is larger than the abnormality determination reference value, the relative displacement heartbeat fluctuation waveform portion is regarded as an arrhythmia. Is replaced with a value that falls within the range of the normal distribution, and then the frequency component is estimated. 2. A waveform obtained by generating an original heartbeat fluctuation waveform from a heartbeat interval, generating a 1 / f fluctuation component waveform from the original heartbeat fluctuation waveform, and subtracting the 1 / f fluctuation component waveform from the original heartbeat fluctuation waveform. Is generated, an average value and a standard deviation of the subtraction waveform portion are calculated, an abnormality determination reference value is determined from the average value and the standard deviation, and an arrhythmia is generated when the subtraction waveform portion is larger than the abnormality determination reference value. The method of analyzing a heartbeat fluctuation waveform is characterized by replacing the subtracted waveform portion with a value that falls within the normal distribution range and then estimating the frequency component. 3. The heartbeat variability waveform according to claim 2, wherein the 1 / f fluctuation component waveform is generated by subjecting the original heartbeat variability waveform to low pass filter processing or moving smoothing processing. analysis method. 4. The heartbeat variability waveform according to claim 1, wherein when the arrhythmia is determined, the original heartbeat variability waveform portion is replaced with an average value of a predetermined surrounding thereof instead of the waveform portion. analysis method. 5. A heartbeat pickup, an amplifier for amplifying an output signal of the pickup in a predetermined frequency band, and an A for converting an output signal of the amplifier into a digital signal.
A D / D converter and an original heartbeat variability waveform are generated from the peak value of the digital signal, and an adjacent interval difference between the original heartbeat variability waveforms is obtained to generate a relative displacement heartbeat variability waveform. Is calculated and the standard deviation is determined, and an abnormality determination reference value is determined from the average value and the standard deviation. A heartbeat variability waveform analysis apparatus, comprising: a calculation unit that estimates a frequency component of the waveform portion after replacing the waveform portion with a value that falls within a normal distribution range. 6. A heartbeat pickup, an amplifier for amplifying the output signal of the pickup in a predetermined frequency band, and an A for converting the output signal of the amplifier into a digital signal.
A D / D converter and an original heartbeat fluctuation waveform are generated from the peak value of the digital signal, a 1 / f fluctuation component waveform is generated from the original heartbeat fluctuation waveform, and a 1 / f fluctuation waveform is generated from the original heartbeat fluctuation waveform.
A waveform obtained by subtracting the fluctuation component waveform is generated, an average value and a standard deviation of the subtracted waveform are calculated, an abnormality determination reference value is determined from the average value and the standard deviation, and the subtracted waveform is calculated from the abnormality determination reference value. A heartbeat variability waveform analysis apparatus comprising: a arrhythmia when it is large and replacing it with a value that falls within the range of the normal distribution of the subtraction waveform portion, and then estimating the frequency component thereof. 7. The calculation unit according to claim 6, wherein the 1 / f fluctuation component waveform is generated by low-pass filtering or moving smoothing the original heartbeat fluctuation waveform. Heart rate variability waveform analyzer. 8. The heartbeat variability waveform according to claim 5, wherein when the arrhythmia is determined, the original heartbeat variability waveform portion, not the waveform portion, is replaced with an average value of a predetermined surrounding thereof. Analyzer.