CN1552283A - Heart rate variability analysis method and device - Google Patents

Abstract

The invention discloses a heart rate variability analysis method with user affinity, which mainly comprises the following steps: an electrocardiosignal of a tested person is captured, analog-digital conversion is carried out on the electrocardiosignal, and the wave crest is selected. And counting the standard deviation of the peak height or duration parameter, and deleting the peak height or duration parameter if the peak height or duration of a certain electrocardiosignal falls outside a preset standard deviation. The qualified peaks are sampled and interpolated to form a continuous peak signal, which is subjected to spectral analysis. The analysis method can be implemented by using a heart rate variability analysis device, which comprises an electrocardiosignal detector for capturing the electrocardiosignals of a tested person, a signal amplifier for amplifying the electrocardiosignals, an analog-digital converter for digitizing the electrocardiosignals, a computer for counting, filtering and analyzing the electrocardiosignals and a digital input/output element used as a man-machine communication interface. The digital input/output device may be connected to an "execute" button to perform all the steps of the analysis method described above.

Description

Heart rate variability analysis method and device

technical field

The present invention relates to a heart rate variability analysis method and device, in particular to a programmable heart rate variability analysis method and device, so as to be used by various users.

Background technique

The sympathetic and parasympathetic nervous systems belong to the autonomic nervous system and are closely related to the daily operation of the human body. If the autonomic nervous system is out of balance, it may cause a variety of acute or chronic diseases, such as heart disease and high blood pressure, and even sudden death and other emergencies in severe cases. Even in generally healthy people, autonomic abnormalities are often accompanied by heart palpitations, dyspnea, gastrointestinal disturbances, and insomnia. Therefore, the health care of the autonomic nervous system is not only an important topic in the medical profession, but also a personal problem that everyone must face every day. The quality of autonomic nervous function can strongly affect a person's quality of life, and some early signs of severe disease can also be seen from abnormal autonomic nervous function. If the autonomic problems of individuals or patients can be known in advance, many human tragedies may be slowed down or even avoided.

Many instruments and methods for diagnosing autonomic nervous function have been developed in clinical medicine, including heart rate variation with deep breathing, Valsalva response, sudomotor function, Orthostatic blood pressure recordings during posture changes, cold pressure test caused by ice water, biochemistry test, etc. However, the above methods either require subjects to suffer for invasive testing, or require expensive instruments, and thus are not suitable for large-scale promotion. In addition, the accuracy or inconvenient use of some methods also increases the difficulty in its application.

A normal human heart beats about 70 times per minute. This regular beating comes from the rhythm system inside the heart, including the sinoatrial node, atrioventricular node and various nerve fibers. This rhythm system is quite precise and is responsible for maintaining the most basic rhythm of life. However, in order to adapt to the changing internal and external environments, the human body has developed a complete autonomic nervous system to regulate heart rate, which includes the sympathetic nervous system and the parasympathetic nervous system. The former can increase the heart rate, while the latter can decrease the heart rate, and the heart rate will produce the best balance under the interaction of the two. In addition to working differently, the two autonomic nervous systems also work at different speeds. The sympathetic nerves act more slowly, while the parasympathetic nerves (especially the vagus nerve, which controls the heart rate), act faster. The difference in the speed of action of the two types of nerves has long been known, but in an age of underdeveloped instrumental analysis, this property was not only difficult to assess, but was also considered of little use.

In addition, the researchers found that in addition to being statically constant and maintained at 70 beats per minute, the heart rate also concealed some regular or irregular fluctuations. These fluctuations may be fast or slow, regular or random, but because these fluctuations are not large, they were often ignored in past medical research. Later, some experts further found that some fluctuations are consistent with breathing movements, while others have nothing to do with breathing. However, the traditional analysis method has encountered obstacles here. On the one hand, the magnitude of these fluctuations is too small to be observed by the traditional recorder. It is often necessary to use some extremely harmful experimental techniques to stimulate them to the point where they can be measured. degree. On the other hand, even if these fluctuations occur, there is no appropriate method to quantify them.

In recent years, many new autonomic nervous system diagnosis techniques have been successfully developed. Due to the maturity of computer hardware and software technology, it is now possible to detect and quantify heart rate variability (HRV) through small changes in heart rate when the human body is resting. autonomic nervous function. In other words, the autonomic nervous function can be analyzed or diagnosed without interfering with a person's normal work and rest. Heart rate variability analysis can stand out from many autonomic nerve diagnosis methods because it contains at least the following characteristics: (1) It is a non-invasive diagnostic technique, and the subjects do not need to bear any pain; (2) The required hardware The cost is low, so it has the potential of large-scale promotion; (3) After many animal and human experiments, it has been confirmed that it can correctly reflect the autonomic nervous function. Therefore, heart rate variability analysis technology has been popularized in recent years, and related researches are also carried out continuously.

In the early 1980s, due to the introduction of spectrum analysis technology, the heart rate variability analysis method can quantify the autonomic nervous function through the heartbeat cycle, thus gradually becoming the best non-invasive method to detect the autonomic nervous function.

With the aid of spectral analysis, the researchers found that the tiny fluctuations in heart rate variability can be clearly divided into two types, commonly referred to as high-frequency (HF) and low-frequency (LF) components. The high-frequency component is synchronized with the animal's breathing signal, so it is also called the breathing component, which is about once every 3 seconds in the human body. The source of the low-frequency component is unknown, and it is speculated that it may be related to vasomotor or pressure-sensitive reflex, which occurs once every 10 seconds in the human body. Some scholars further subdivide the low frequency components into very low frequency (VLF) and low frequency components. At present, many physiologists and cardiologists agree that the high-frequency component or total variability (total power, TP) of heart rate can represent the parasympathetic function, while the ratio of low-frequency component to high-frequency component (LF/HF) can reflect the sympathetic function. activity. In addition to being an indicator of autonomic nervous function, some studies have found that heart rate variability can reflect a variety of body information. For example, patients with increased brain pressure will have lower heart rate variability; if the low-frequency components of the heart rate of the elderly are reduced by one standard deviation, their chances of facing death are 1.7 times that of ordinary people; while the low-frequency variability of heart rate in brain-dead patients completely disappears. In addition, heart rate variability will also change if rejection occurs in heart transplant patients. In surgery, heart rate variability can reflect the depth of anesthesia. Gender and age do affect the function of sympathetic and parasympathetic nerves, including both predominance (such as in youth), both decline (such as in old age), sympathetic and parasympathetic decline (such as men), sympathetic and parasympathetic decline Sheng (such as women). It was later discovered in the hospital that women's sympathetic function increases during pregnancy, but if overreacted, it may be accompanied by (and may even lead to) the development of dangerous pre-epilepsy.

In 1996, the European and American Society of Cardiology standardized and made public the analysis method of heart rate variability (Circulation (1996) 17, pp.354-381). The method is shown in the flow chart of Figure 1 . Firstly, an ECG signal is captured, and a microcomputer is used for digital sampling and noise filtering. Afterwards, edit the RR information (that is, the RR peak distance) in the obtained ECG signal, and eliminate the unqualified RR peak distance, so as to obtain the RR peak information (that is, the NN information) generated by the normal node rate point. The NN information is interpolated and sampled, and finally the spectrum analysis in the frequency domain is performed to obtain the analysis information of the heart rate variability. However, this method is quite cumbersome to implement, and the noise identification, RR information editing and elimination all need to be manually processed, which is quite labor-intensive and time-consuming. The above-mentioned method forms a high barrier to use, making it difficult for non-related professionals to use the technology.

Since the current heart rate variability analysis is almost always performed by a digital computer, it is necessary to first capture the ECG signal, perform analog-to-digital conversion on the ECG signal, and then store it in a digital file. At this time, an identification code or file name must be given to the digital file. Correction and analysis of the digital files must be done manually. After the analysis is completed, the information still has to rely on manual processing when printing.

To sum up, the traditional method of analyzing heart rate variability still has to rely on manual processing from signal acquisition, file analysis to final printing. Therefore, in operation, the keyboard is often used as an interface for processing, which not only has a large number of key presses, but also has different types of keys. In addition, the design of the keyboard will increase the volume of the machine, which does not conform to the current trend of machine miniaturization.

Contents of the invention

The main purpose of the present invention is to provide a heart rate variability analysis method and device for simplifying the analysis process and implementing fully automatic operation. In addition, the present invention uses a statistical method to filter noise, which can improve the accuracy of heart rate variability analysis.

The heart rate variability analysis method of the present invention mainly includes the following steps: (1) extracting an ECG signal of a subject; (2) performing analog-to-digital conversion on the ECG signal; (3) selecting the ECG signal (peak); (4) filtering unqualified peaks; (5) sampling and interpolating qualified peaks to form a continuous peak signal; (6) performing frequency domain spectrum analysis on the peak signal. In addition, the peak spacing can also be filtered to remove noise.

The above step of filtering unqualified peaks and peak distances is to first count the standard deviation of parameters such as the peak height, duration or peak distance of the ECG signal. If the peak height, duration or peak distance of an ECG signal falls outside their respective preset standard deviations, it will be considered as noise and deleted.

The heart rate variability analysis device of the present invention includes an electrocardiographic signal detector, a signal amplifier, an analog-to-digital converter, a computer and a digital input/output element. The electrocardiographic signal detector is used for capturing the electrocardiographic signal of the subject. The signal amplifier is connected with the ECG signal detector and is used for amplifying the ECG signal. The analog-to-digital converter is connected to the signal amplifier for digitizing the electrocardiographic signal. The computer is connected to the analog-to-digital converter, which includes a program for counting, filtering, and analyzing the digitized ECG signal, and can control the steps of the above-mentioned heart rate variability analysis method. The digital input/output element is connected with the computer as a man-machine communication interface of the heart rate variability analysis device. In addition, the digital input/output element can be connected with an "execute" button for executing the above-mentioned heart rate variability analysis method.

The present invention replaces the design of the traditional keyboard with the "execute" button, and automates it through the control of the program, allowing the user to reduce the number of keystrokes required for heart rate variability analysis to one time to execute all the above-mentioned functions. step. Therefore, the present invention can not only be implemented in small models, but also largely eliminates the possibility of operating errors.

Description of drawings

The invention will be described with reference to the accompanying drawings, in which:

Figure 1 is a known heart rate variability analysis process;

Fig. 2 is the heart rate variability analysis device of the present invention;

Fig. 3 is the flow chart of heart rate variability analysis of the present invention;

Fig. 4 shows the selected QRS wave of the heart rate variability analysis method of the present invention;

Fig. 5 is the analysis result of heart rate variability in the present invention.

Detailed ways

Fig. 2 is the heart rate variability analyzing device 20 of the present invention, and it mainly comprises a signal amplifier 21, an analog-to-digital converter 22, a computer 23, a digital input/output element 24, an electrocardiogram signal detector 25, a " Execute" button 26 and a casing 32. The casing 32 can be a rectangular three-dimensional structure whose length, width and height are respectively 11, 14 and 4.5 centimeters, and is used to accommodate the signal amplifier 21, the analog-to-digital converter 22, the computer 23 and the digital input/output element 24 and other major devices. The electrocardiogram detector 25 can be made up of three detection electrodes 251, one end of which is connected to the subject, and the other end passes through the casing 32 and is connected to the signal amplifier 21 for picking up the subject's electrocardiogram , and transmit it to the signal amplifier 21. After the electrocardiographic signal is amplified by the signal amplifier 21 , it is converted into a digital signal by the analog-to-digital converter 22 and input to the computer 23 . The computer 23 executes a program 231 to perform a series of analysis and control tasks, the content of which will be described in detail later. The digital input/output element 24 serves as a transmission interface between the computer 23 and the “execute” button 26 . In fact, the digital input/output element 24 is a man-machine interface communicating with the outside world, and it can also be connected with a "noise" indicator light 33, a "no signal" indicator light 34, a "printing" indicator light 35, A "recording" indicator light 36 and a "standby" indicator light 37, etc., to show the use status of the heart rate variability analysis device 20; or a "cancel" button 27 can be connected to provide the function of manually interrupting the process . The above-mentioned buttons 26, 27 and various indicator lights 33 to 37 can be installed on the same side of the casing 32 to facilitate monitoring. Between the signal amplifier 21 and the analog-to-digital converter 22, between the analog-to-digital converter 22 and the computer 23, and between the computer 23 and the digital input/output element 24, cables 38 can be connected for signal transmission .

In addition, the computer 23 can be connected with a monitor 29 and a printer 30 for displaying or printing the heart rate variability analysis results of the ECG signal. The signal amplifier 21 can be further connected to a battery 31 or directly connected to an AC power source to provide its own required power.

The heart rate variability analysis process of the present invention is shown in FIG. 3 , and will be described sequentially below in conjunction with the heart rate variability analysis device 20 in FIG. 2 .

When the heart rate variability analysis device 20 is powered on, the "standby" indicator light 37 will light up, telling the user that the heart rate variability analysis device 20 is in a ready-to-use state. All procedures of the heart rate variability analysis are activated via the “execute” button 26 . When the "execute" button 26 is pressed, the "recording" indicator light 36 will light up, and the electrocardiogram detector 25 begins to pick up a brief electrocardiogram, which is amplified or added by the signal amplifier 21. After being filtered by the upper band-pass filter, it is transmitted to the analog-to-digital converter 22 . Next, the program 231 is used to control the analog-to-digital converter 22 to perform analog-to-digital conversion on the ECG signal and to sample 256 to 2048 times per second. This program 231 can also add the function of detecting the 50/60Hz signal therein at the same time, if the signal is too strong, the "noise" indicator light 33 lights up. Afterwards, the ECG signal is found at the peak of each heartbeat, that is, the QRS wave of the heartbeat (please refer to FIG. 4 ), as a representative of each heartbeat. If there is no peak, the "no signal" light 34 is on. The program 231 can measure parameters such as height and duration from the peak of each heartbeat, and calculate the average value and standard deviation of each parameter as a standard template. Next, each heartbeat peak is compared with this template. If the comparison result of a certain heartbeat peak falls outside the first preset standard deviation of the standard template, it will be considered as noise and deleted. Generally, in practical operation, three standard deviations are mostly used as the default value of the first preset standard deviation.

The distance between the peaks of two adjacent heartbeats is measured as the heartbeat cycle of this time, and the average and standard deviation of all heartbeat distances are calculated, and then all heartbeat distances are confirmed. If a heartbeat interval falls outside a second predetermined standard deviation, it is also considered as noise or unstable signal and deleted. As above, three standard deviations are generally used as the default value of the second preset standard deviation. All qualified peaks are sampled and interpolated at an appropriate frequency (eg, 7.11 Hz) to maintain their temporal coherence. Use this program 231 to detect whether the "Cancel" button 27 is pressed. If yes, return to the standby state; otherwise, proceed to the following steps. With this program 231, it is judged whether the amount of information is sufficient. If it is not enough, continue to capture the ECG signal to form a loop; if so, continue to perform the following steps.

Spectrum analysis uses the Fourier transform method. First, the linear drift of the signal is eliminated to prevent interference in the low frequency band, and the Hamming operation is used to avoid the mutual leakage of individual frequency components in the spectrum. Next, take 288 seconds of information (2048 points) and perform fast Fourier transform to obtain the power density spectrum (heart rate power spectral density, HPSD), and compensate for the influence caused by sampling and Hamming operations. The power density spectrum of heart rate variability quantifies the power of two of the frequency bands by means of integration, including LF (0.04-0.15Hz) and HF (0.15-0.4Hz) power, and simultaneously obtains quantitative parameters such as LF/HF or TP. The result is shown in Figure 5.

Finally, the result is displayed on the display 29, or printed out by the printer 30. When the printer 30 is printing, the "print" indicator light 35 is on. The display 29 and the printer 30 can also be directly built into the heart rate variability analysis device 20 besides being externally connected.

In addition to the statistics, filtering and analysis of ECG signals, the program 231 can also increase the function of controlling the steps of the above-mentioned heart rate variability analysis method as in this embodiment, so that the user only needs to press the "execute" button 26, to complete all the steps.

A lot of information must be input in the traditional heart rate variability analysis. The present invention integrates and controls the computer through the program, which can reduce the number of key presses required by the user to analyze the heart rate variability to one time, and only one button can replace the original The design of the keyboard not only can be implemented in small models, but also provides a user-friendly operation interface. In addition to greatly eliminating the possibility of operation errors, it is also easy to promote to non-professionals. In addition, the actual operation of the heart rate variability analysis device of the present invention only takes about five minutes from pressing the button to printing out the subject's heart rate variability analysis results and autonomic nerve information, which is very time-saving and convenient.

The technical content and technical features of the present invention have been disclosed above, but those skilled in the art may still make various replacements and modifications based on the teaching and disclosure of the present invention without departing from the spirit of the present invention. Therefore, the protection scope of the present invention should not be limited to the content disclosed in the embodiments, but should include various replacements and modifications that do not depart from the present invention, and are covered by the claims of this patent application.

Claims (16)

1. heart rate variability analysis method comprises the following step:

Capture the electrocardiosignal of a testee;

This electrocardiosignal is carried out analog-digital conversion;

Choose the crest of this electrocardiosignal;

Add up the height of this crest or the standard deviation of persistent period;

If the height or the persistent period of the crest of a certain electrocardiosignal drop on outside the one first preset standard difference, will be considered to noise and deleted;

Qualified crest taken a sample and interpolation to become a successive crest signal;

This crest signal is carried out the spectrum analysis of frequency domain.

2. heart rate variability analysis method according to claim 1 is characterized in that the described first preset standard difference is three standard deviations.

3. heart rate variability analysis method according to claim 1 is characterized in that it comprises the step that a corrugation pitch and of calculating this electrocardiosignal is filtered defective corrugation pitch in addition.

4. heart rate variability analysis method according to claim 3, the step that it is characterized in that the defective corrugation pitch of described filtration is the standard deviation of adding up the corrugation pitch of this electrocardiosignal earlier, if the corrugation pitch of a certain electrocardiosignal drops on outside the one second preset standard difference, will be considered to noise and deleted.

5. heart rate variability analysis method according to claim 4 is characterized in that the described second preset standard difference is three standard deviations.

6. heart rate variability analysis method according to claim 1 is characterized in that its instruction input via a button, can finish institute in regular turn in steps.

7. heart rate variability analysis method according to claim 1 is characterized in that whether enough it comprise a sample intelligence detection step in addition.

8. heart rate variability analysis method according to claim 1 is characterized in that described crest signal Spectrum Analysis result is presented on the screen or printout.

9. heart rate variability analysis method according to claim 1 is characterized in that described crest is a QRS ripple.

10. heart rate variability analysis device comprises:

Electrical signal detection device wholeheartedly is used to capture the electrocardiosignal of testee;

One signal amplifier is used to amplify this electrocardiosignal;

One analogue-to-digital converters are with this electrocardiosignal digitized;

One computer is used for statistics, filters and analyze this numeral electrocardiosignal; And

One digital I/O element is connected to this computer, is the man-machine communication interface as this heart rate variability analysis device.

11. heart rate variability analysis device according to claim 10 is characterized in that described digital I/O element is connected to a button, is used to drive this computer and carries out statistics, filters and analyze this numeral electrocardiosignal.

12. heart rate variability analysis device according to claim 10 is characterized in that described signal amplifier, analogue-to-digital converters, computer and digital I/O element are to be installed in the casing.

13. heart rate variability analysis device according to claim 10 is characterized in that it comprises at least one display lamp that is connected in this numeral I/O element in addition, is used to show the state that carries out.

14. heart rate variability analysis device according to claim 10 is characterized in that it comprises a display that is connected to this computer in addition.

15. heart rate variability analysis device according to claim 10 is characterized in that it comprises a printer that is connected to this computer in addition.

16. heart rate variability analysis device according to claim 10 is characterized in that described electrocardiosignal detector is to be made of at least two detecting electrodes.

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