WO2018120636A1

WO2018120636A1 - Electrocardio monitoring method and system

Info

Publication number: WO2018120636A1
Application number: PCT/CN2017/086501
Authority: WO
Inventors: 包磊
Original assignee: 深圳市善行医疗科技有限公司
Priority date: 2016-12-30
Filing date: 2017-05-29
Publication date: 2018-07-05
Also published as: CN106725433B; CN106725433A

Abstract

An electrocardio monitoring system, comprising: electrocardio electrodes (1), a filter circuit (2), an electrocardio integration chip (3), a controller (4), a power supply (5), a wireless transmission circuit (6), and an alarm server (7), the electrocardio electrodes (1) being disposed on wearable electrocardio clothing; the electrocardio electrodes (1) send a collected electrocardio monitoring analog signal to the electrocardio integration chip (3) after the signal is filtered by the filter circuit (2), the electrocardio integration chip (3) then sends a converted electrocardio monitoring digital signal to the controller (4), while the controller (4) sends a compression-coded electrocardio monitoring digital signal and a user identification to the alarm server (7) by means of the wireless transmission circuit (6), and the alarm server (7) sends a comparison result, which is obtained by comparing historical data of the electrocardio monitoring digital signal and the user identification, to an emergency center. The electrocardio monitoring system may find an abnormality during a first time and aid a user by means of the emergency center, which may improve the timeliness of aiding the user.

Description

ECG monitoring method and system

Technical field

The invention belongs to the field of electrocardiogram monitoring, and in particular relates to an ECG monitoring method and system.

Background technique

Over the past two decades, digital innovation has seen unprecedented advances that not only increasingly affect our daily lives, but also quickly penetrate into the healthcare sector. In the 1990s, the practice of general medical treatment continued to develop in the direction of electronic medical archives, and the application of digital technology in the field of health care was also rapidly expanding. Digital health technologies have great potential to change the current health care model. However, many new technologies ended up in the “last mile” and did not meet the expectations. Face-to-face health consultation and diagnosis are still the mainstream mode of general practice, but real-time, wearable, undisturbed and multi-modal monitoring systems and corresponding solutions have been gradually applied to general practice to improve The rate of treatment.

Electrocardiogram is a commonly used clinical examination, which not only reflects the heart health, but also reflects changes in mood. However, due to the inspection method, the traditional ECG equipment cannot be easily monitored for a long time, and it is difficult to find an abnormal ECG at an early stage.

Summary of the invention

It is an object of the present invention to provide an ECG monitoring method and system for solving the problem that the prior art ECG device is inconvenient for long-term monitoring, and it is difficult to find an abnormal ECG early.

In a first aspect, an embodiment of the present invention provides an ECG monitoring system, where the system includes an electrocardiogram electrode, a filter circuit, an electrocardiogram integrated chip, a controller, a power source, a wireless transmission circuit, an early warning server, and the ECG electrode setting On the wearable electrocardiograph, the ECG electrode transmits the collected ECG monitoring analog signal to the ECG integrated chip through the filtering process of the filter circuit, and the ECG integrated chip Transmitting the converted ECG monitoring digital signal to the controller, the controller transmitting the compressed ECG monitoring digital signal and the user identifier to the early warning server via the wireless transmission circuit, and the early warning service will monitor the ECG digital The signal and the historical data of the user identification are compared, and the comparison result is sent to the emergency center.

In conjunction with the first aspect, in a first possible implementation of the first aspect, the electrocardiographic electrode is a fabric electrode disposed on the electrocardiograph, and the fabric electrode is connected by the filter circuit of the conductive textile thread.

With reference to the first aspect, or the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, the power supply includes a battery and a voltage conversion circuit, and an input end of the voltage conversion circuit Connected to the battery, the first output of the voltage conversion circuit is connected to the power supply pin of the electrocardiograph integrated chip, and the voltage of the first output is matched with the low voltage supply value of the electrocardiograph integrated chip, the voltage A second output of the conversion circuit is coupled to the controller.

With reference to the first aspect, or the first possible implementation manner of the first aspect, in a third possible implementation manner of the first aspect, the signal input pin of the electrocardiograph integrated chip and the electrocardiographic electrode pass the magnet spring pin The plugin is connected to the outlet.

With reference to the first aspect, or the first possible implementation manner of the first aspect, in a fourth possible implementation manner of the first aspect, the wireless transmission circuit is a Bluetooth 4.0-based Bluetooth communication circuit.

In conjunction with the first aspect, or the first possible implementation of the first aspect, in a fifth possible implementation manner of the first aspect, the ECG monitoring system further includes a timing circuit, the timing circuit is integrated with the ECG A sleep control pin of the chip, and/or a sleep control pin of the controller, and/or a sleep control pin of the wireless transmission circuit are coupled.

In a second aspect, an embodiment of the present invention provides an ECG monitoring method including the ECG monitoring system of any of the above, the method comprising:

Collecting the user's ECG monitoring analog signal through the ECG electrode;

Filtering the ECG monitoring analog signal, and converting the ECG monitoring analog signal into an ECG monitoring digital signal by an electrocardiogram integrated chip;

The user identifier and the ECG monitoring digital signal are compression-encoded by the controller and sent to the pre- Police server

The early warning server obtains the historical data of the user according to the user identifier, compares the historical data of the user with the currently acquired ECG monitoring digital signal, and sends the comparison result to the early warning center.

With reference to the second aspect, in a first possible implementation manner of the second aspect, the filtering step of the ECG monitoring analog signal includes one or both of the following:

Eliminate potential power-frequency noise and ringing noise through dual bilateral filtering techniques and two iterative techniques;

Elimination of two parallel noise reductions and myoelectric and electrode noise interference.

In conjunction with the first possible implementation of the second aspect, in a second possible implementation of the second aspect, the step of eliminating potential power frequency noise and ringing noise by using the double bilateral filtering technique and the two iterative techniques includes :

After the image extension signal is input to the first filter, forward filtering is performed to obtain a first forward filtered signal;

Performing inverse filtering on the first forward filtered signal to obtain a first inverse filtered signal;

And iteratively inputting the first inverse filtered signal into the first filter, performing the forward filtering, and acquiring a second forward filtered signal;

Performing the inverse filtering on the second forward filtered signal to obtain the first filtered signal that does not include power frequency noise;

The first filter calculates the first filter according to a sampling rate, a notch frequency, and a first stopband width, and respective parameters in the original filter.

In conjunction with the first possible implementation of the second aspect, in a third possible implementation of the second aspect, the step of eliminating interference by two parallel noise reduction and electromyogram and electrode noise includes:

Parallel one: Decomposing the eigenmode function IMF containing noise by the empirical mode decomposition method, and dividing the signal sequence included in the eigenmode function according to a preset length to obtain a maximum threshold and a minimum threshold of the window, according to the Filtering the maximum threshold and the minimum threshold;

Parallel 2: Extract and filter the baseline drift in the ECG signal, using the wavelet method and the notch filter respectively Filtering the myoelectric interference and power frequency interference, adding the above three filtered signals as the reference signal of the adaptive filter, and adaptively filtering with the noisy ECG signal to generate an output signal.

In the present invention, the ECG monitoring analog signal is collected by the ECG electrode, and the ECG monitoring analog signal is filtered by the filter circuit, and the filtered signal is converted into the ECG monitoring digital signal by the ECG integrated chip, and the controller After the digital signal is encoded and compressed, and sent to the early warning server together with the user identifier, the early warning server generates a comparison result by comparing the current ECG monitoring digital signal and the historical data corresponding to the user identification, and sends the comparison result to the emergency center, so that the alarm server can The user performs real-time and effective monitoring. When the user's ECG data is abnormal, the abnormality can be found at the first time and the emergency center can help the user, which is beneficial to improve the timeliness of the user being rescued.

DRAWINGS

1 is a schematic structural diagram of an ECG monitoring system according to an embodiment of the present invention;

2 is a flowchart of implementing an ECG monitoring method according to an embodiment of the present invention;

FIG. 3 is a schematic structural diagram of an ECG monitoring apparatus according to an embodiment of the present invention.

detailed description

The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

The main purpose of the embodiments of the present invention is to provide an ECG monitoring system and an ECG monitoring method to solve the ECG monitoring system in the prior art, which is inconvenient for the user to perform long-term effective monitoring, thereby failing to appear in the user's physical state. When an abnormality occurs, the abnormality is found in the first time, so that it is not convenient for the user to take timely and effective assistance to the patient, which is not conducive to better protecting people's life and health problems. The invention will now be further described with reference to the accompanying drawings.

1 is a schematic structural diagram of an ECG monitoring system according to an embodiment of the present invention, where the system includes an electrocardiogram electrode 1, a filter circuit 2, an electrocardiogram integrated chip 3, a controller 4, a power source 5, and a wireless transmission circuit 6. The ECG electrode 1 is disposed on the wearable electrocardiograph, and the ECG electrode 1 transmits the collected ECG monitoring analog signal to the ECG integrated chip 3 through the filtering process of the filter circuit 2, The ECG integrated chip 3 sends the converted ECG monitoring digital signal to the controller 4, and the controller 4 transmits the compression-encoded ECG monitoring digital signal and the user identifier to the early warning server 7 via the wireless transmission circuit 6. The early warning service compares the ECG monitoring digital signal and the historical data of the user identification, and compares the result to the emergency center.

Specifically, the electrocardiographic electrode 1 is configured to acquire an ECG signal of a user. As a preferred embodiment of the present invention, the electrocardiographic electrode 1 is provided with a fabric electrode and is disposed on a wearable electrocardiograph. And, the fabric electrode 1 is connected to the filter circuit through a conductive textile wire. The fabric electrode is disposed on the electrocardiograph, which can facilitate the user to wear for a long time, and the fabric electrode can effectively conduct the ECG signal, so that the acquired ECG signal is stable and reliable.

The filter circuit 2 may perform filtering processing by using a combination of a low-pass filter circuit and a high-pass filter circuit, or may include a processor pre-set with a filtering algorithm to filter the ECG monitoring analog signal. The filtering algorithm is specifically described in the subsequent method section.

The ECG integrated chip 3, which may also be referred to as an ECG (English full name Electrocardiograph) chip, is used for performing gain amplification, analog-to-digital conversion, and the like on an analog signal collected by a recording electrode. The electrocardiography integrated chip 2 includes, but is not limited to, ADS1294, ADS1296, ADS1298, ADS1294R, ADS1296R, or ADS1298R.

An application or software for analyzing and processing the signal is disposed or installed in the controller 4, and the collected data may be filtered, compressed, encoded, or encrypted. The controller can adopt a high-performance 32-bit ARM Cortex-M4F processor with ultra-low power consumption, and the processor has a floating-point arithmetic unit, which can quickly perform calculation of algorithms such as filtering and compression of electrocardiogram data, and reduce system running time. . After each sampling of the ECG data, the timing signal of the timing circuit can be received, and the controller system enters the sleep mode. After a predetermined period of time, the controller wakes up the controller system for the next sampling. Moreover, the utility model can further disconnect or turn off the power supply pin circuit corresponding to the IO port corresponding to the unused peripherals in the processor according to different application scenarios, thereby further reducing power consumption. The invention The circuit structure can reduce the power consumption of the processor to less than 3mW.

The power source 5 may be a directly powered battery. As a preferred embodiment, the power source may include a battery and a voltage conversion circuit, and an input end of the voltage conversion circuit is connected to the battery, and the voltage conversion circuit is The first output end is connected to the power supply pin of the electrocardiograph integrated chip, and the voltage of the first output end is matched with the low voltage power supply value of the electrocardiograph integrated chip, and the second output end of the voltage conversion circuit is The controller is connected.

Of course, the signal transmission circuit 6 may be connected to the second output terminal or may be connected to the first output terminal.

The battery may be a lithium ion battery, a lithium manganese button battery or a zinc empty button battery. The voltage of the battery may be 3.0V, or may be 5.0V, 3.7V or the like. For example, when the voltage of a single button battery is 1.5V, an output voltage of 3.0V can be obtained by series connection.

The voltage conversion circuit in the ECG data acquisition circuit may be a DC-DC conversion, and the original DC power is controlled by adjusting its PWM (duty ratio) to control the effective voltage of the output, and may include a boost circuit or a step-down circuit. . The first output is coupled to the electrocardiography integrated chip to provide electrical energy to the electrocardiograph integrated chip. The voltage at the first output may be a low voltage match of the power supply pin of the electrocardiograph integrated chip. Therefore, the internal voltage regulator in the ECG integrated chip does not need to perform LDO voltage conversion, and the LDO voltage conversion generates a large power loss, thereby contributing to reducing the power consumption of the chip. Therefore, it is more advantageous for the user to wear the electrocardiogram for ECG detection for a long time.

The electrocardiogram integrated chip 2, such as ADS1294, ADS1296, ADS1298, ADS1294R, ADS1296R or ADS1298R. The system power supply is generally collected at 3.3V. However, in the present invention, the main core portion is internally converted to 1.8V using a low-dropout linear regulator LDO, which causes a large power loss during the conversion process. In the present invention, in order to effectively reduce the power consumption of the system, the 1.8V regulator inside the ECG chip is prohibited, but the battery is subjected to DC-DC conversion of the voltage conversion circuit, and the output is 1.8V filtered, and then directly supplied to the ECG chip. Used, this reduces power consumption from the power supply. In addition, unnecessary functions and pins in the ECG integrated chip can be turned off according to different application scenarios to reduce power consumption. The ECG part of the power consumption can be reduced to 20mW when the 12-lead is made.

Additionally, the present invention may further include a timer, which may be coupled to a power consumption control pin of the signal transmission circuit, and/or a power consumption control pin of the electrocardiograph integrated chip. When the signal acquisition is not required, the sleep mode is automatically entered, thereby saving more power. The timer can be implemented by a controller or a dedicated timing circuit.

The signal transmission circuit 6, preferably a Bluetooth communication circuit based on the Bluetooth 4.0 transmission protocol. The signal transmission circuit 6 can be connected to the first output, such as a 1.8V low power Bluetooth 4.0 transmission scheme.

In addition, in order to improve the convenience of installation of the electrocardiographic acquisition circuit, the signal input end of the electrocardiograph integrated chip is provided with an interface connectable to the recording electrode. In a preferred embodiment, the interface is a magnet spring needle insert. The powerful magnet makes the interface firmly sucked, even if the beating is very stable, the spring pin increases the insertion and insertion life, up to 1 million times. It has the advantages of convenience, good signal quality and firmness.

2 is a flowchart of implementing an ECG monitoring method according to an embodiment of the present invention, which is described in detail as follows:

The implementation of the ECG monitoring method is based on the ECG monitoring system of FIG. 1 , and the method specifically includes:

In step S201, the user's ECG monitoring analog signal is collected through the ECG electrode.

Specifically, the electrocardiographic electrode may be a fabric electrode, and the electrocardiographic electrode may be connected to the filter circuit through a conductive textile wire. The electrocardiographic electrode can be disposed on the electrocardiograph, and the user can effectively obtain the electrocardiogram monitoring analog signal through the fabric electrode when the user wears the electrocardiograph.

In step S202, the ECG monitoring analog signal is filtered, and the ECG monitoring analog signal is converted into an ECG monitoring digital signal by an electrocardiogram integrated chip.

Filtering the ECG monitoring analog signal can effectively remove power frequency interference, ringing noise, myoelectric noise and electrode noise in the ECG monitoring analog signal.

The filtering step of the ECG monitoring analog signal includes one or two of the following:

Specifically, the steps of eliminating potential power frequency noise and ringing noise by using a double bilateral filtering technique and two iterative techniques include:

The specific implementation process of the dual bilateral filtering technology is as follows:

1 initialization. The filter coefficients are calculated by equation (1) given the sampling rate, the notch frequency, and the stopband width of the notch.

Wherein, the formula (1) is specifically:

f _s is the sampling rate, f ₀ is the notch frequency, and Δf is the first stop band width.

2 first bilateral filtering. The image extension signal is passed through the system determined by equation (1) to obtain an output signal and a residual portion, and the residual portion includes potential power frequency noise PLI and ringing noise RAs. This process is equivalent to filtering the original signal twice: once from left to right; the other is from right to left. Since equation (1) is a causal system, the RAs caused by the same heartbeat pulse signal will be located on both sides of the pulse.

3 second bilateral filtering. The filtered signal is again passed through the same system to obtain an output signal. The PLI will be filtered out in this step. The residual portion contains only RAs and broadband noise located within the stop band.

4RAs positioning. Use the techniques of differential, low-pass filtering and threshold to the residual part of step 3. The RAs in the position are located.

5RAs are eliminated. The RAs are eliminated by using a certain threshold rule, that is, in the residual portion of step 3, the coefficient of one end of each heartbeat pulse that is not contaminated by RAs (the end of one end of the pulse is contaminated, and the other end is not contaminated) is selected as an output. In fact, the distortion caused by the transient effects of the system that the output signal lasts for a few seconds at the beginning will also be eliminated at this step.

The dual bilateral filtering technique implies an important assumption: the set stopband width parameter does not overlap the RAs generated by each of the two heartbeat pulse signals, and the technique cannot distinguish the overlapping RAs. The actual selected stopband width inevitably causes the RAs to overlap. Because the city's electrician frequency usually has a certain drift, the general national industrial standard is controlled within 1%; but the poor mains environment, the drift is as high as 3%. Two iteration techniques can solve this problem.

The two iterations of technical filtering are introduced as follows:

1 Use a larger first stopband width for PLI cancellation. Set a larger first stopband width (such as 6.0Hz) and use double bilateral filtering to filter out PLI interference. The residual part contains the PLI and the stronger but shorter duration RAs.

2 Use a smaller second stopband width for information reconstruction. Select a smaller second stopband width (the actual requirement is less than 6.0Hz, generally about 2.0Hz), and use the double bilateral filtering technique to process the residual part of the previous step (1). The step of obtaining the output filtering portion mainly utilizes that the residual portion is usually two levels lower than the original signal, and the RAs contained in the residual portion are negligible.

The use of larger and smaller resistance bandwidths in the two iterative techniques is complementary to the duration and strength requirements of the RAs. It can be seen that the simultaneous elimination of power frequency interference and RAs is a non-real-time processing, but by design (such as the low-pass filter coefficient set to a simple integer coefficient), quasi-real-time processing can be realized.

The steps for the elimination of the two parallel noise reduction and the myoelectric and electrode noise are as follows:

Parallel two: extract and filter the baseline drift in the ECG signal, use the wavelet method and the notch filter to filter the EMG interference and the power frequency interference respectively, and add the above three filtered signals as the reference of the adaptive filter. The signal is adaptively filtered with the noisy ECG signal to generate an output signal.

Specifically, in view of the fact that the frequency band of the ECG signal and the noise frequency band are aliased, the simple combined denoising method can only filter out noise outside the frequency range of the ECG signal, and denoise the noise of the aliasing. It is bound to affect the characteristics of each waveform, resulting in signal distortion. Therefore, it is necessary to fully consider the combination of various methods, and keep the ECG as undistorted as possible during the denoising process. In addition, each method has its own difficulties before combining various methods. For example, when using wavelet denoising, the selection of wavelet basis should be considered. When denoising by threshold method, the selection of optimal threshold should be considered. When using morphological denoising, the selection of structural elements should be considered. Therefore, when selecting the combination of denoising schemes, it is necessary to fully consider their respective advantages and disadvantages and make up for each other.

The invention achieves the purpose of removing aliasing noise interference by two-way parallel noise reduction:

Parallel 1: The empirical mode decomposition method (EMD) is very suitable for processing nonlinear and non-stationary signals. The biggest advantage is that it does not require a predefined basic function to represent the signal, and adaptively selects the base-pair signal directly according to the characteristics of the signal itself. For analysis, unlike the wavelet method, the wavelet function needs to be defined, so that it faces the selection of wavelet base, so it is very suitable for processing ECG signals. However, due to the aliasing of the signal frequency band and the noise frequency band, the signal is distorted during the denoising process. Therefore, the present invention is considered to be combined with the threshold denoising method. However, the soft and hard thresholds are achieved by setting a value greater than the threshold to a given threshold and zeroing the value of the threshold to zero, thereby increasing the possibility of false denoising, and thus the present invention adopts Double threshold method. The method first finds the eigenmode function IMF containing noise from all the IMFs decomposed by the EMD, and then divides the signal sequence contained by these IMFs into "window", sets the length of the "window", and calculates the maximum in the "window". The minimum value is obtained by the maximum threshold and the minimum threshold, that is, the double thresholds of the respective "windows" are obtained and filtered.

Parallel 2: Mathematical morphology is a mathematical tool for analyzing images based on morphological structural elements. Its basic idea is to use a certain structural element to measure and extract the corresponding shape in the image to achieve the purpose of image analysis and recognition. The ECG signal is a one-dimensional periodic signal composed of PQRST waves. So when selecting structural elements, choosing a straight line will be more conducive to analysis and processing. However, this method is sensitive to singular points, which will cause distortion of QRS waveform. Therefore, this patent considers combining notch filter, wavelet method and adaptive filter, and adaptive filter can reflect real-time performance well. The method firstly uses the morphological method to extract the baseline drift and filter it out. Secondly, the wavelet method and the notch filter are used to filter the myoelectric interference and power frequency interference, and then the three filtered signals are added as adaptive filtering. The reference signal of the device is adaptively filtered with the noisy ECG signal to finally achieve the denoising effect.

In step S203, the controller identifies and compresses the user identifier and the ECG monitoring digital signal to the early warning server;

In step S204, the early warning server acquires the historical data of the user according to the user identifier, compares the historical data of the user with the currently acquired ECG monitoring digital signal, and sends the comparison result to the early warning center.

As a further optimized implementation manner of the present invention, the controller may further send the location information, the environment information, and the historical diagnosis information of the user to the early warning server, so that the early warning server can complete more accurate ECG data analysis. For example, based on the acquired data, a dynamic state data chart of the user may be established, and the historical diagnosis information may be combined to generate a targeted suggestion, which may be sent to a mobile terminal bound to the user identifier.

The ECG monitoring method of the present invention further introduces the filtering process of the ECG monitoring analog signal on the basis of the ECG monitoring system shown in Fig. 1. Through the above filtering process, a more reliable ECG can be obtained. Monitor the signal.

In addition, as shown in FIG. 3, the present invention further provides an ECG monitoring device, the device comprising:

The collecting unit 301 is configured to collect an ECG monitoring analog signal of the user through the ECG electrode;

The filter conversion unit 302 is configured to filter the ECG monitoring analog signal, and convert the ECG monitoring analog signal into an ECG monitoring digital signal by an ECG integrated chip;

The first sending unit 303 is configured to compress and encode the user identifier and the ECG monitoring digital signal by the controller, and send the signal to the early warning server;

The second sending unit 304 is configured to obtain, by the early warning server, the historical data of the user according to the user identifier, compare the historical data of the user with the currently acquired ECG monitoring digital signal, and send the comparison result to the early warning center.

The ECG monitoring device corresponds to the ECG monitoring method described above, and will not be repeated here.

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention, which is essential or contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium. A number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the methods described in various embodiments of the present invention. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), and a random memory. Take a variety of media that can store program code, such as RAM (Random Access Memory), disk, or optical disk.

The above is only the preferred embodiment of the present invention, and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection of the present invention. Within the scope.

Claims

An electrocardiogram monitoring system, characterized in that the system comprises an electrocardiogram electrode, a filter circuit, an electrocardiogram integrated chip, a controller, a power source, a wireless transmission circuit, an early warning server, and the ECG electrode is disposed on the wearable electrocardiograph The ECG electrode sends the collected ECG monitoring analog signal to the ECG integrated chip through the filtering process of the filter circuit, and the ECG integrated chip sends the converted ECG monitoring digital signal to the controller. The controller sends the compressed and encoded ECG monitoring digital signal and the user identifier to the early warning server via the wireless transmission circuit, and the early warning service compares the ECG monitoring digital signal and the historical data of the user identification, And the result of the comparison is sent to the emergency center.
The electrocardiographic monitoring system according to claim 1, wherein said electrocardiographic electrodes are fabric electrodes disposed on a core garment, said fabric electrodes being connected by said filter circuit of a conductive textile thread.
The electrocardiographic monitoring system according to claim 1 or 2, wherein the power source comprises a battery and a voltage conversion circuit, an input end of the voltage conversion circuit is connected to the battery, and a first output of the voltage conversion circuit The terminal is connected to the power supply pin of the electrocardiograph integrated chip, and the voltage of the first output terminal is matched with the low voltage power supply value of the electrocardiograph integrated chip, and the second output end of the voltage conversion circuit is connected to the controller .
The electrocardiographic monitoring system according to claim 1 or 2, wherein the signal input pin of the electrocardiograph integrated chip and the electrocardiographic electrode are connected through a magnet spring pin insert and a socket.
The ECG monitoring system according to claim 1 or 2, wherein the wireless transmission circuit is a Bluetooth communication circuit based on Bluetooth 4.0.
The ECG monitoring system according to claim 1 or 2, wherein the ECG monitoring system further comprises a timing circuit, a sleep control pin of the ECG integrated chip, and/or the control The sleep control pin of the device and/or the sleep control pin of the wireless transmission circuit are connected.
An ECG monitoring method comprising the ECG monitoring system according to any one of claims 1 to 6, wherein the method comprises:

Collecting the user's ECG monitoring analog signal through the ECG electrode;

Filtering the ECG monitoring analog signal, and converting the ECG monitoring analog signal into an ECG monitoring digital signal by an electrocardiogram integrated chip;

The user identifier and the ECG monitoring digital signal are compression-encoded by the controller and sent to the early warning server;

The early warning server obtains the historical data of the user according to the user identifier, compares the historical data of the user with the currently acquired ECG monitoring digital signal, and sends the comparison result to the early warning center.
The method according to claim 7, wherein the step of filtering the ECG monitoring analog signal comprises one or both of the following:

Eliminate potential power-frequency noise and ringing noise through dual bilateral filtering techniques and two iterative techniques;

Elimination of two parallel noise reductions and myoelectric and electrode noise interference.
The method of claim 8 wherein said step of eliminating potential power-frequency noise and ringing noise by dual bilateral filtering techniques and two iterative techniques comprises:

After the image extension signal is input to the first filter, forward filtering is performed to obtain a first forward filtered signal;

Performing inverse filtering on the first forward filtered signal to obtain a first inverse filtered signal;

And iteratively inputting the first inverse filtered signal into the first filter, performing the forward filtering, and acquiring a second forward filtered signal;

Performing the inverse filtering on the second forward filtered signal to obtain the first filtered signal that does not include power frequency noise;

The first filter calculates the first filter according to a sampling rate, a notch frequency, and a first stopband width, and respective parameters in the original filter.
The method of claim 8 wherein said step of eliminating noise by two parallel noise reductions and electromyogram and electrode noise comprises:

Parallel one: Decomposing the eigenmode function IMF containing noise by empirical mode decomposition method, The signal sequence included in the modulo function is divided into windows according to a preset length to obtain a maximum threshold and a minimum threshold of the window, and filtering is performed according to the maximum threshold and the minimum threshold;

Parallel two: extract and filter the baseline drift in the ECG signal, use the wavelet method and the notch filter to filter the EMG interference and the power frequency interference respectively, and add the above three filtered signals as the reference of the adaptive filter. The signal is adaptively filtered with the noisy ECG signal to generate an output signal.