JPH067823B2 - Cardiac radio wave examination device - Google Patents

Description

TECHNICAL FIELD The present invention relates to an electrocardiographic examination apparatus, and in particular, to easily identify signs of a potential disease that an inexperienced person can easily overlook in a diagnosis by visual observation. The present invention relates to an electrocardiographic examination device capable of

(Problems to be Solved by Conventional Techniques and Inventions) At present, an electrocardiograph is indispensable for diagnosis of heart disease.

However, it is a reality that the correct reading of the electrocardiogram is not easily performed even in the modern times when the electrocardiograph was restored.

For this reason, it has become difficult for even an experienced specialist to gain insight into a potential disease and to investigate the cause of the disease simply by visually observing the electrocardiogram.

In addition, recently, it has become common to introduce a computer or the like into information processing to perform automatic measurement, but with a spectrum analyzer or the like using these, a disease that cannot be determined because waveform analysis has not been sufficient until now. was there.

Therefore, it is an object of the present invention to provide an electrocardiographic examination device that can detect a potential disease quickly and easily.

(Means for Solving the Problems) As a means for solving the above problems, the present invention provides a detector for detecting a change in action potential associated with myocardial activity as a cardiac wave, and an electrocardiographic wave detected by this detector. Input the detection signal,
The time domain of the detection signal is obtained from the autocorrelation function, and the frequency domain of the cardiac radio wave detection signal is obtained from the spectrum by a fast Fourier transform unit, and based on the fast Fourier transform output of this fast Fourier transform unit, the adjacent spectrum The information display processing unit is configured to display a cardiac radio wave spectrum such as a phase difference between spectra, which is a phase difference.

(Action) A change in action potential associated with myocardial activity is detected by an electrode which is a detector, and the electrocardiographic signal detected by this electrode is input to the fast Fourier transform unit.

Then, in this fast Fourier transform unit, the time domain of the cardiac wave detection signal is obtained from the autocorrelation function and the frequency domain is obtained from the spectrum.

Next, based on the fast Fourier transform output of the fast Fourier transform unit, a cardiac radio spectrum such as a phase difference between spectra which is a phase difference between adjacent spectra is obtained.

Then, the information display processing unit displays these cardiac radio spectrums.

In the above cases, the pattern of the electrocardiographic wave and the shape of each spike wave are not uniform, so the pattern changes each time the electrocardiographic waveform is captured, but the pattern is changed in diagnosing arrhythmia and variations in the electrocardiographic waveform. Since it is possible to recognize the variation quickly, it is suitable for these diagnoses.

Then, based on the electrocardiographic spectrum such as the amplitude spectrum and the phase difference between the spectra obtained from the spectrum analyzer, it is possible to reduce the harmonics of the electrocardiographic spectrum as much as possible, so that the electrocardiogram can not be distinguished at all. Since the change can also be discriminated, the measurement time in diagnosis, the speed of processing, and the accuracy are improved.

(Embodiment) Next, an embodiment of the present invention will be described with reference to FIG.

FIG. 1 is a block diagram showing an example of a spectrum examination apparatus for cardiac radio waves according to the present invention.

In this figure, the measuring terminal 1 is composed of two electrodes, but it is desirable to use the standard 12-lead method if necessary.

The cardiac radio wave signal input from the measurement terminal 1 is transmitted to the preamplifier 2
Is amplified by.

When the cardiac radio wave signal amplified by the preamplifier 2 is input to the fast Fourier transformer 3, first, the cardiac radio wave signal is input to the fast Fourier transformer 3.

The cardiac radio wave signal input to this fast Fourier transformer 3 is
After being sampled by a sampling unit (not shown), an analog signal is converted to a digital signal by an A / D converter (not shown).

The digital signal converted by the A / D converter is fast Fourier transformed by the fast Fourier transformer 3 to obtain an autocorrelation function and a power spectrum.

The autocorrelation function is effective in detecting the periodicity of the waveform, and detects the pitch period of the speech source by speech synthesis.

Further, there is a relationship between the frequency spectrum and the autocorrelation function shown in FIG. 2 among the waveform, the autocorrelation function, the frequency spectrum, and the power spectrum.

The relationship between the frequency spectrum and the autocorrelation function in FIG. 2 will be described.

In FIG. 2, the correlation of the cardiac radio wave waveform is obtained by an autocorrelation function.

This autocorrelation function is expressed as a function of τ by integrating the product of the cardiac radio wave waveform (t) and the cardiac radio wave waveform (t + τ) that is shifted by τ in the time direction.

Therefore, the heart wave waveform (t) and the heart wave waveform (t + T ₁ )
Is emphasized, and the autocorrelation function ψ (τ) becomes a cardiac radio wave waveform having a sharp peak at τ = T ₁ .

That is, the time domain of the cardiac radio wave waveform (t) is determined by the correlation of the cardiac radio wave waveform (t) and the autocorrelation function ψ (τ) (process 1).

Further, the frequency domain is determined from the time domain of the cardiac radio wave waveform (t) by Fourier transforming the autocorrelation function ψ (τ) and the power spectrum (process 2).

Further, the frequency spectrum is obtained by Fourier transform of the cardiac radio wave waveform (t), and the amplitude region and the phase region of the cardiac radio wave waveform (t) are determined by the frequency spectrum (process 3).

Then, the frequency spectrum is squared to obtain a power spectrum, and the power spectrum is subjected to inverse Fourier transform to obtain an autocorrelation function, thereby determining the time domain from the frequency domain (process 4).

The cardiac radio wave waveform (t) is obtained by performing the inverse Fourier transform on the frequency spectrum.

In the electrocardiographic examination apparatus of this embodiment, a change in action potential due to myocardial activity is detected by an electrode which is a detector, the detected electrocardiographic waveform is taken from the measurement terminal 1, and the preamplifier 2 is used.
After being amplified by, the signal is processed by the fast Fourier transform unit (FFT) 3.

Then, the fast Fourier transform unit (FFT) 3 determines the frequency domain from the time domain of the cardiac radio wave waveform (t) by the above processing 1 to processing 4.

Further, the fast Fourier transformer (FFT) 3 obtains a frequency spectrum by Fourier transform of the cardiac radio wave waveform (t), determines the amplitude region and the phase region of the cardiac radio wave waveform (t) from the frequency spectrum, and The time domain can be determined from the frequency domain by squaring the spectrum to obtain a power spectrum, and performing an inverse Fourier transform on the power spectrum to obtain an autocorrelation function.

Therefore, in this embodiment, a fast Fourier transformer (FFT)
By determining the time domain, the amplitude domain, and the phase domain in 3, it is possible to obtain the distribution of the steep amplitude and the phase difference between spectra in a short time from the cardiac radio wave waveform (t).

In this case, by mounting at least one electrode at a desired induction electrode mounting position, the electrode is input to the fast Fourier transformer 3 through the measurement terminal 1 and the preamplifier 2.

Therefore, when there is an abnormality in the heart disease, etc., it becomes a characteristic diagram showing a particularly remarkable relationship between the phase difference between spectra and frequency, so by looking at this characteristic diagram, it is possible to perform a quicker and more reliable medical examination. it can.

For this reason, even an inexperienced specialist can easily gain insight into a potential disease and pursue the cause of the disease simply by visually observing the electrocardiogram.

FIG. 3 shows an example of spectrum analysis of V ₄ lead electrocardiograms of normal subjects and myocardial infarction patients.

For example, as shown in FIG. 3A, the high frequency component of the spectrum has the frequency 3 as shown in the spectrum distribution of the normal person.
Although the spectrum gradually decreases from 0 Hz to a frequency of 50 Hz, the fluctuation of the amplitude becomes large when the frequency is approximately 5 Hz.

On the other hand, FIG. 3 (b) shows an example of the spectrum distribution of a patient with myocardial infarction, in which the distribution of the harmonic components has a pattern that sharply decreases from the frequency of 5 Hz, so that the amplitude with respect to the frequency at that time is sharp. Since it becomes possible to easily determine that there is a heart disease rather than a decrease, it is possible to quickly and surely determine the heart disease.

FIGS. 4 and 5 show the spectrum analysis results of the cardiac waves of the second and V ₄ leads of a normal person. Both figures (a) are the charts showing the heartbeat data of the cardiac waves. b) is an amplitude spectrum showing the relationship between specific amplitude and frequency, and both figures (c) are characteristic diagrams showing the relationship between the phase difference between spectra and frequency.

As described above, in the case of a normal person, FIG. 4 (b) and FIG.
As is clear from FIG. 6 (b), the distribution of the amplitude spectrum of the harmonic component shows a gradual decrease, and as is clear from FIG. 4 (c) and FIG. Since the phase difference between spectra is distributed around 0 degree, the disturbance due to the distribution of the amplitude spectrum up to the frequency of 50 Hz is almost eliminated. Therefore, since there is no disturbance due to the distribution of the amplitude spectrum, it is easy to judge the normal person. You can

Next, FIGS. 6 and 7 show the second case of a patient with complete left bundle branch block.
3A and 3B show examples of spectrum analysis of V ₄ induction cardiac radio waves.

FIG. 6 (a) and FIG. 7 (a) are diagrams showing the heartbeat data of such a patient's cardiac wave, and FIG. 6 (b) and FIG. 7 (b) are the relationship between specific amplitude and frequency. 6 (b) and 7 (b) are characteristic diagrams showing the relationship between the phase difference between spectra and the frequency.

In these cases, the distribution of the harmonic components of the amplitude spectrum shows a pattern of sharp decrease as is clear from FIGS. 6 (b) and 7 (b), and the inter-spectral phase difference FIG. Since (c) and FIG. 7 (c) are randomly distributed, it can be seen from these distributions that this is a pattern peculiar to patients with leg block associated with QRS prolongation. Thus, it becomes possible to perform appropriate treatment for these diseases at an early stage.

8 to 10 show the first and second patients with myocardial asthma.
₃ is an example of spectrum analysis of V ₄ induction cardiac radio waves.

8 to 10 (a) are graphs showing the heartbeat data of the cardiac waves of a patient with myocardial infarction, and FIGS. 8 to 10 (b) are amplitude spectra showing the relationship between the specific amplitude and the frequency. 8 to 10 (c) are characteristic diagrams showing the relationship between the phase difference between spectra and the frequency. In these cases, the harmonic components of FIGS. 8 to 10 (b) are relatively strong in the low frequency band, but for example, since the amplitude rapidly decreases from around 20 Hz, this From the point where the amplitude suddenly decreases, it can be seen that there is an amplitude abnormality, and it can be seen that the amplitude abnormality is due to a heart disease.Therefore, by promptly addressing the patient, early diagnosis and treatment are performed. be able to.

Further, from the phase difference between spectra in FIGS. 8 to 10 (c), in any case, the disturbance of the distribution of the spectrum phase difference with respect to frequency is particularly large in the range of 0 to 50 Hz. Since the distribution disorder is less than in the case of the leg block patient shown in FIG. 7, it can be seen that the patient is not the leg block but the myocardial infarction.

As described above, in the present example, by observing the pattern of the amplitude spectrum and the phase difference between the spectra as a result of the spectrum analysis of the cardiac radio waves, by comparing and examining the distribution situation of the phase difference at that time, it is possible to determine the heart disease. Since it can be ensured very early, highly reliable diagnosis and examination can be performed.

It should be pointed out that it should be noted that even if it is impossible to discriminate the above from the electrocardiogram waveform (a) as in the case of the first lead in FIG. The presence of a heart disease can be estimated and determined by observing the distributions of the amplitude spectrum of FIG. 8 (b) and the phase difference between spectra of FIG. 8 (c).

This also applies to other induction sites where the above is less likely to appear as the electrocardiographic waveform of the electrocardiograph.

Therefore, according to the present embodiment, it is possible to determine most of the diseases by only one lead, not by using the standard 12-lead method that is currently generally used, so that only a quick diagnosis can be made. In addition, since the complexity of multipolar induction, which is a difficulty in measuring an electrocardiogram, is eliminated, the measurement can be performed very easily.

Therefore, according to the present embodiment, when many people need to undergo the minimum necessary medical examination within a limited time, such as a group medical examination, by using the device of the above-mentioned embodiment, Thus, it is possible to perform a diagnosis related to heart disease extremely efficiently.

(Effect of the invention) As described above, according to the present invention, it is possible to appropriately determine the presence or absence of a heart disease in a large number of humans as in the case of mass screening, so that even a potential disease can be detected early. Can be diagnosed.

[Brief description of drawings]

FIG. 1 is a block diagram showing an example of a spectrum detection apparatus for cardiac radio waves according to the present invention, FIG. 2 is a diagram showing a relationship between a frequency spectrum and an autocorrelation function, and FIG. 3 is V _{4 of a} normal person and a patient with myocardial infarction. illustrates an embodiment of a spectral analysis of lead electrocardiogram, FIGS. 4 and 5, the second and V ₄ of the normal person
The results of the spectrum analysis of the inductive cardiac wave are shown in Fig. 2 (a), which shows the raw data of the cardiac wave, and in Fig. 2 (b), the amplitude spectrum showing the relationship between the specific amplitude and the frequency. FIG. 6 (c) is a characteristic diagram showing the relationship between the phase difference between spectra and frequency, and FIGS. 6 and 7 are second diagrams of patients with complete left bundle branch block.
And an example of spectrum analysis of V ₄ lead cardiac radio waves,
FIG. 6 (a) and FIG. 7 (a) are diagrams showing the heartbeat data of such a patient's cardiac wave, and FIG. 6 (b) and FIG. 7 (b) are the relationship between specific amplitude and frequency. FIG. 6 (b) and FIG. 7 (b) are characteristic diagrams showing the relationship between the phase difference between spectra and frequency, and FIGS. 8 to 10 are the first and the second of the patients with myocardial infarction. FIGS. 8 to 10 (a) are graphs showing the heartbeat data of the cardiac wave of a patient with myocardial infarction, and FIGS. 8 to 10 (b) are spectrum analysis examples of the second and V ₄ -leading cardiac waves. FIG. 8 to FIG. 10C are characteristic diagrams showing the relationship between the phase difference between spectra and the frequency, which is an amplitude spectrum showing the relationship between the specific amplitude and the frequency. Reference numeral 1 is a measurement terminal, 2 is a preamplifier, 3 is a spectrum analyzer, 4 is a microprocessor, and 5 is an output display unit.

 ─────────────────────────────────────────────────── ─── Continuation of front page (72) Inventor Naotaka Watanabe 4-3-1 Kuwano, Koriyama City, Fukushima Prefecture (56) References JP 47-28778 (JP, A) JP 55-62964 (JP, A) ) JP-A-51-62764 (JP, A) JP-A-52-36880 (JP, A) JP-A-51-27175 (JP, A)

Claims (1)

[Claims] 1. A detector for detecting a change in action potential associated with myocardial activity as a cardiac wave and a cardiac wave detection signal detected by this detector are input, and the time domain of the detected signal is calculated from an autocorrelation function. A fast Fourier transform unit that obtains the frequency region of the cardiac radio wave detection signal from the spectrum together with the fast Fourier transform output of the fast Fourier transform unit. An electrocardiographic examination device comprising an information display processing unit for displaying a spectrum.