Electrocardiograph and electrode slice information interaction method based on wireless data transmission

Abstract

The invention discloses an electrocardiograph and electrode slice information interaction method based on wireless data transmission, which relates to the field of medical systems and comprises the following steps: pasting a corresponding electrode slice to a specific body part of a patient; performing data compression processing on the potential information acquired by the electrode slice by using a multi-guide adaptive vector quantization compression technology; transmitting the compression potential information to an electrocardiograph through a Bluetooth chip in the electrode plate for subsequent data processing; the electrocardiograph judges whether the compression potential information data volume reaches a preset threshold value or not; carrying out filtering processing on the compression potential information; correcting baseline drift in the electrocardiogram signal by using a baseline tracking algorithm; converting the corrected electrocardiogram signal into electrocardiogram vector data; and comparing the electrocardio waveform feature point information with electrocardio waveform feature point information in an electrocardio database. Through wireless data transmission, the convenience and efficiency of clinical use are improved, and the comfort level of a patient is also improved.

Description

Technical Field

[0001] The present invention relates to the field of medical systems, and in particular to an information interaction method between an electrocardiograph and an electrode sheet based on wireless data transmission. Background Art

[0002] In recent years, with the improvement of people's living standards and the increasing social work pressure, there is a widespread phenomenon of excessive nutrition supply and lack of exercise for mental workers, which has led to an increase in the incidence of cardiovascular diseases year by year. At present, heart disease has become one of the main diseases that threaten human life and health. According to statistics, one-third of the world's deaths each year die from heart disease. Many people delay treatment due to failure to detect the disease in time, and their mortality rate ranks first among population disease mortality rates. In my country, with the continuous acceleration of the aging of the population, the incidence of heart disease has also tended to increase year by year, and the number of people who died from heart disease accounts for 44% of the total number of deaths. It can be seen that heart disease has become a common and frequently occurring disease that threatens human life and health. Timely detection of abnormal symptoms of heart disease is of great significance for the prevention and early diagnosis and treatment of the disease.

[0003] The electrocardiographs currently used in clinical practice have many wires that are easily tangled and the outer rubber is easily worn out over time, causing great trouble. This is especially true when encountering critically ill patients, wasting time and preventing them from being used effectively in the first place. Summary of the invention

[0004] In order to solve the above technical problems, a method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission is provided. This technical solution solves the problems raised in the above background technology.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission, comprising:

[0007] Adhere corresponding electrode sheets to specific body parts of the patient, wherein the specific body parts include the left hand, the right hand, the left leg, the right leg and the chest;

[0008] The potential information collected by the electrode sheet is compressed using multi-channel adaptive vector quantization compression technology to obtain compressed potential information;

[0009] By means of Bluetooth transmission, the compression potential information is transmitted to the electrocardiograph through the Bluetooth chip in the electrode sheet for subsequent data processing;

[0010] The electrocardiograph determines whether the amount of compressed potential information data reaches a preset threshold value. If so, a collection stop signal is fed back to each electrode sheet. If not, no output is made.

[0011] Construct a low-pass filter to filter the compressed potential information to obtain an electrocardiogram signal;

[0012] Correcting the baseline drift in the electrocardiogram signal by using a baseline tracking algorithm to obtain a corrected electrocardiogram signal;

[0013] Based on the principle of vectorcardiography, the corrected ECG signal is converted into vectorcardiography data, and the dynamic parameters of the vectorcardiography are used to identify and locate the characteristic points of the ECG waveform;

[0014] The ECG waveform feature point information is compared with the ECG waveform feature point information in the ECG database to diagnose and classify the patient's heart disease.

[0015] Preferably, the step of attaching the corresponding electrode sheet to a specific body part of the patient specifically includes:

[0016] Place the electrodes on the left hand, right hand, left leg, and right leg respectively;

[0017] Place the electrode in the fourth intercostal space on the right side of the sternum, i.e. the first right ventricle;

[0018] Place the electrode in the fourth space on the left side of the sternum, i.e. the second right ventricle;

[0019] Place the electrode on the midpoint of the line connecting the fourth rib on the left side of the sternum and the fifth rib on the midclavicular line, which is the first ventricular septum.

[0020] Place the electrode at the intersection of the left midclavicular line and the ventricular interspace, i.e., the second ventricular septum;

[0021] Place the electrode pad at the intersection of the second ventricular septum level and the anterior axillary line, i.e., the first left ventricle;

[0022] Place the electrode at the intersection of the second ventricular septum level and the mid-axillary line, that is, the second left ventricle.

[0023] Preferably, the method of performing data compression processing on the potential information collected by the electrode sheet using multi-channel adaptive vector quantization compression technology to obtain compressed potential information specifically includes:

[0024] A codebook is predefined to represent possible input vectors;

[0025] Combine the data samples from the same time points of different electrodes into one input vector;

[0026] Based on each input vector, the Euclidean distance between each output vector and each vector in the codebook is calculated using the Euclidean distance formula;

[0027] Output the codebook vector with the smallest Euclidean distance as the approximate representation of the input vector;

[0028] Replace each input vector with the index of the codebook vector it approximates;

[0029] Summarize and output all the approximate codebook vectors as compressed potential information;

[0030] The Euclidean distance formula is:

[0031]

[0032] In the formula, is the Euclidean distance between the i-th input vector and the j-th codebook vector, a i，k is the k-th dimension data of the i-th input vector, b j，k is the k-th dimension data of the j-th codebook vector, and n is the dimension of the vector.

[0033] Preferably, the method of transmitting the compression potential information to the electrocardiograph through the Bluetooth chip in the electrode sheet for subsequent data processing by Bluetooth specifically includes:

[0034] The Bluetooth chip built into the electrode sheet presets relevant Bluetooth parameters, which include Bluetooth address, pairing key and transmission protocol;

[0035] The electrocardiograph turns on the Bluetooth function and searches for nearby Bluetooth devices;

[0036] When the electrocardiograph finds the Bluetooth chip built into the electrode, the connection between the Bluetooth chip and the electrocardiograph is established by manually inputting the pairing key;

[0037] The Bluetooth chip transmits the compression potential information to the electrocardiograph via Bluetooth transmission.

[0038] Preferably, the electrocardiograph determines whether the amount of compression potential information data reaches a preset threshold value specifically including:

[0039] Based on the limitation of the storage space of the electrocardiograph, a first preset threshold is preset;

[0040] Manually adjust the first preset threshold to the second preset threshold according to real-time requirements or specific conditions of the patient;

[0041] The electrocardiograph determines whether the amount of compressed potential information data reaches a second preset threshold value, and if so, feeds back a collection stop signal to each electrode sheet, and if not, does not output;

[0042] Each electrode sheet stops collecting potential information after receiving the collection stop signal.

[0043] Preferably, the step of constructing a low-pass filter and filtering the compressed potential information to obtain an electrocardiogram signal specifically includes:

[0044] A low-pass filter is constructed by using resistor and capacitor elements;

[0045] The corner frequency of the low-pass filter is calculated using a corner frequency formula based on the resistance value of the resistor element and the capacitance value of the capacitor element;

[0046] Using a low-pass filter to filter the compressed potential information;

[0047] Determine whether the frequency of the input signal is lower than the turning frequency. If so, the output is an electrocardiogram signal; if not, the output is a noise signal.

[0048] The transition frequency formula is:

[0049]

[0050] Where f0 is the corner frequency of the low-pass filter, R is the resistance value of the resistor, and C is the capacitance value of the capacitor.

[0051] Preferably, the method of correcting the baseline drift in the electrocardiogram signal by using a baseline tracking algorithm to obtain a corrected electrocardiogram signal specifically includes:

[0052] Preset the sliding window size and sliding step size according to the characteristics of the electrocardiogram signal;

[0053] The sliding window is placed at the starting position of the electrocardiogram signal, and the baseline position of the window is estimated by calculating the median value of the electrocardiogram signal within the sliding window;

[0054] As the window slides, the baseline estimate of the new window is smoothed with the baseline estimate of the previous window, and the baseline estimate is continuously updated;

[0055] Determine whether the sliding window traverses the ECG signal. If so, output the baseline estimation value as the baseline value. If not, no output is made.

[0056] A baseline drift correction operation is performed on the electrocardiogram signal, and the baseline value is subtracted from the electrocardiogram signal to obtain a corrected electrocardiogram signal.

[0057] Preferably, the converting of the corrected electrocardiogram signal into electrocardiogram vector data based on the principle of vector cardiology, and identifying and locating electrocardiogram waveform feature points using dynamic parameters of the electrocardiogram vector specifically includes:

[0058] Using a normalization formula to perform data normalization processing on the corrected electrocardiogram signal to obtain a normalized electrocardiogram signal;

[0059] Define a three-dimensional coordinate system for the human body, where the X-axis is the horizontal direction, the Y-axis is the vertical direction passing through the center of the heart, and the Z-axis is from bottom to top and perpendicular to the X-axis and Y-axis;

[0060] Perform a dot product operation on the normalized electrocardiogram signal and the basis vectors of the coordinate system to obtain the component of the signal on each coordinate axis;

[0061] The components of the signal on each coordinate axis are synthesized into a three-dimensional electrocardiogram vector;

[0062] Track the changing trajectory of the ECG vector and calculate its velocity and acceleration dynamic parameters;

[0063] Identify and locate ECG waveform feature points based on dynamic parameters of ECG vectors, including the start and end points and peak points of P waves, QRS waves, T waves and U waves;

[0064] The normalization formula is:

[0065]

[0066] In the formula, x i ' is the i-th normalized ECG signal, x i is the ith corrected ECG signal, x max , x min are the maximum and minimum values ​​of the corrected ECG signal respectively.

[0067] Preferably, comparing the ECG waveform feature point information with the ECG waveform feature point information in the ECG database to diagnose and classify the patient's heart disease specifically includes:

[0068] Determine whether each ECG waveform feature point information is not within a normal threshold range, if so, output the ECG waveform feature point information as abnormal information, if not, output the ECG waveform feature point information as normal information;

[0069] Perform similarity matching between the abnormal information and the ECG waveform feature point information in the ECG database, and output the ECG waveform feature point information with the highest similarity;

[0070] The ECG waveform feature point information with the highest similarity is identified to correspond to heart disease, and is output as a possible disease of the current patient.

[0071] Compared with the prior art, the present invention has the following beneficial effects:

[0072] The baseline tracking algorithm can effectively eliminate the impact of baseline drift on ECG detection, improve the accuracy of ECG analysis, convert multi-lead information into heart vectors, and use the spatial information of heart vectors to quickly and accurately identify ECG feature points. The algorithm has important application value in the field of automatic ECG analysis and automatic diagnosis, and provides a reliable basis for the diagnosis and treatment of cardiovascular diseases. It improves the convenience and efficiency of clinical use through wireless data transmission, and also improves the comfort of patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 It is a flow chart of the information interaction method between an electrocardiograph and an electrode sheet based on wireless data transmission of the present invention;

[0074] Figure 2 A flow chart of a method for attaching corresponding electrode sheets to specific body parts of a patient according to the present invention;

[0075] Figure 3 It is a flow chart of the multi-channel adaptive vector quantization compression technology method of the present invention;

[0076] Figure 4 This is a flow chart of the method for transmitting compression potential information to an electrocardiograph through a Bluetooth chip in an electrode sheet according to the present invention;

[0077] Figure 5 This is a flow chart of a method for determining whether the amount of compression potential information data reaches a preset threshold value according to the present invention;

[0078] Figure 6 This is a flow chart of a method for filtering compressed potential information according to the present invention;

[0079] Figure 7 A flow chart of a method for correcting baseline drift in an electrocardiogram signal using a baseline tracking algorithm according to the present invention;

[0080] Figure 8 A flow chart of the method for identifying and locating characteristic points of an electrocardiogram waveform using dynamic parameters of an electrocardiogram vector according to the present invention;

[0081] Fig. 9 This is a flow chart of the method for diagnosing and classifying heart diseases in patients according to the present invention. DETAILED DESCRIPTION

[0082] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0083] Reference Figure 1 As shown, a method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission includes:

[0084] Adhere corresponding electrode sheets to specific body parts of the patient, wherein the specific body parts include the left hand, the right hand, the left leg, the right leg and the chest;

[0085] The potential information collected by the electrode sheet is compressed using multi-channel adaptive vector quantization compression technology to obtain compressed potential information;

[0086] By means of Bluetooth transmission, the compression potential information is transmitted to the electrocardiograph through the Bluetooth chip in the electrode sheet for subsequent data processing;

[0087] The electrocardiograph determines whether the amount of compressed potential information data reaches a preset threshold value. If so, a collection stop signal is fed back to each electrode sheet. If not, no output is made.

[0088] Construct a low-pass filter to filter the compressed potential information to obtain an electrocardiogram signal;

[0089] Correcting the baseline drift in the electrocardiogram signal by using a baseline tracking algorithm to obtain a corrected electrocardiogram signal;

[0090] Based on the principle of vectorcardiography, the corrected ECG signal is converted into vectorcardiography data, and the dynamic parameters of the vectorcardiography are used to identify and locate the characteristic points of the ECG waveform;

[0091] The ECG waveform feature point information is compared with the ECG waveform feature point information in the ECG database to diagnose and classify the patient's heart disease.

[0092] Reference Figure 2 As shown, attaching the corresponding electrode pads to the specific body parts of the patient specifically includes:

[0093] Place the electrodes on the left hand, right hand, left leg, and right leg respectively;

[0094] Place the electrode in the fourth intercostal space on the right side of the sternum, i.e. the first right ventricle;

[0095] Place the electrode in the fourth space on the left side of the sternum, i.e. the second right ventricle;

[0096] Place the electrode on the midpoint of the line connecting the fourth rib on the left side of the sternum and the fifth rib on the midclavicular line, which is the first ventricular septum.

[0097] Place the electrode at the intersection of the left midclavicular line and the ventricular interspace, i.e., the second ventricular septum;

[0098] Place the electrode pad at the intersection of the second ventricular septum level and the anterior axillary line, i.e., the first left ventricle;

[0099] Place the electrode at the intersection of the second ventricular septum level and the mid-axillary line, that is, the second left ventricle.

[0100] The leads of the electrode are the basis for obtaining electrocardiogram information. Only with the leads of the electrode can we record the electrocardiogram signals and have an electrocardiogram, which in turn serves the diagnosis of diseases.

[0101] Reference Figure 3As shown, the potential information collected by the electrode sheet is compressed using multi-channel adaptive vector quantization compression technology to obtain compressed potential information including:

[0102] A codebook is predefined to represent possible input vectors;

[0103] Combine the data samples from the same time points of different electrodes into one input vector;

[0104] Based on each input vector, the Euclidean distance between each output vector and each vector in the codebook is calculated using the Euclidean distance formula;

[0105] Output the codebook vector with the smallest Euclidean distance as the approximate representation of the input vector;

[0106] Replace each input vector with the index of the codebook vector it approximates;

[0107] Summarize and output all the approximate codebook vectors as compressed potential information;

[0108] The Euclidean distance formula is:

[0109]

[0110] In the formula, is the Euclidean distance between the i-th input vector and the j-th codebook vector, a i，k is the k-th dimension data of the i-th input vector, b j，k is the k-th dimension data of the j-th codebook vector, and n is the dimension of the vector.

[0111] By implementing the above algorithm design, the amount of data transmitted in real time by the network electrocardiograph can be effectively reduced, the efficiency and security of data transmission can be improved, and more reliable and efficient technical support can be provided for application scenarios such as emergency treatment.

[0112] Reference Figure 4 As shown, by means of Bluetooth transmission, the compression potential information is transmitted to the electrocardiograph through the Bluetooth chip in the electrode sheet for subsequent data processing, specifically including:

[0113] The Bluetooth chip built into the electrode sheet presets relevant Bluetooth parameters, which include Bluetooth address, pairing key and transmission protocol;

[0114] The electrocardiograph turns on the Bluetooth function and searches for nearby Bluetooth devices;

[0115] When the electrocardiograph finds the Bluetooth chip built into the electrode, the connection between the Bluetooth chip and the electrocardiograph is established by manually inputting the pairing key;

[0116] The Bluetooth chip transmits the compression potential information to the electrocardiograph via Bluetooth transmission.

[0117] Bluetooth technology is an open global standard for wireless data and voice communications. It is a special short-range wireless technology connection based on low-cost short-range wireless connection to establish a communication environment for fixed and mobile devices.

[0118] Reference Figure 5 As shown, the electrocardiograph determines whether the amount of compressed potential information data reaches a preset threshold value, specifically including:

[0119] Based on the limitation of the storage space of the electrocardiograph, a first preset threshold is preset;

[0120] Manually adjust the first preset threshold to the second preset threshold according to real-time requirements or specific conditions of the patient;

[0121] The electrocardiograph determines whether the amount of compressed potential information data reaches a second preset threshold value, and if so, feeds back a collection stop signal to each electrode sheet, and if not, does not output;

[0122] Each electrode sheet stops collecting potential information after receiving the collection stop signal.

[0123] When determining whether the data volume has reached a preset threshold, it is necessary to ensure the integrity of the data, that is, the received data should be complete and correct, without any data loss or damage due to problems during the transmission process.

[0124] Reference Figure 6 As shown, a low-pass filter is constructed to filter the compressed potential information to obtain the electrocardiogram signal including:

[0125] A low-pass filter is constructed by using resistor and capacitor elements;

[0126] The corner frequency of the low-pass filter is calculated using a corner frequency formula based on the resistance value of the resistor element and the capacitance value of the capacitor element;

[0127] Using a low-pass filter to filter the compressed potential information;

[0128] Determine whether the frequency of the input signal is lower than the turning frequency. If so, the output is an electrocardiogram signal; if not, the output is a noise signal.

[0129] The transition frequency formula is:

[0130]

[0131] Where f0 is the corner frequency of the low-pass filter, R is the resistance value of the resistor, and C is the capacitance value of the capacitor.

[0132] The filter that the signal can pass through, or the filter connected to the ground through the capacitor, has less attenuation for low-frequency signals than high-frequency signals. It is called a low-pass filter. It uses the principle that capacitors pass high frequencies and block low frequencies, and inductors pass low frequencies and block high frequencies. For high frequencies that need to be cut off, the capacitor absorbs the inductor and blocks it from passing; for low frequencies that need to be released, the high resistance of the capacitor and the low resistance of the inductor are used to allow it to pass.

[0133] Reference Figure 7 As shown, the baseline drift in the electrocardiogram signal is corrected by using a baseline tracking algorithm to obtain a corrected electrocardiogram signal, which specifically includes:

[0134] Preset the sliding window size and sliding step size according to the characteristics of the electrocardiogram signal;

[0135] The sliding window is placed at the starting position of the electrocardiogram signal, and the baseline position of the window is estimated by calculating the median value of the electrocardiogram signal within the sliding window;

[0136] As the window slides, the baseline estimate of the new window is smoothed with the baseline estimate of the previous window, and the baseline estimate is continuously updated;

[0137] Determine whether the sliding window traverses the ECG signal. If so, output the baseline estimation value as the baseline value. If not, no output is made.

[0138] A baseline drift correction operation is performed on the electrocardiogram signal, and the baseline value is subtracted from the electrocardiogram signal to obtain a corrected electrocardiogram signal.

[0139] The effect of the sliding window method is greatly affected by the sliding window size and the sliding step size, and needs to be adjusted according to the specific ECG signal and detection requirements.

[0140] Reference Figure 8 As shown, based on the principle of vectorcardiography, the corrected ECG signal is converted into vectorcardiography data, and the dynamic parameters of the vectorcardiography are used to identify and locate the characteristic points of the ECG waveform, including:

[0141] Using a normalization formula to perform data normalization processing on the corrected electrocardiogram signal to obtain a normalized electrocardiogram signal;

[0142] Define a three-dimensional coordinate system for the human body, where the X-axis is the horizontal direction, the Y-axis is the vertical direction passing through the center of the heart, and the Z-axis is from bottom to top and perpendicular to the X-axis and Y-axis;

[0143] Perform a dot product operation on the normalized electrocardiogram signal and the basis vectors of the coordinate system to obtain the component of the signal on each coordinate axis;

[0144] The components of the signal on each coordinate axis are synthesized into a three-dimensional electrocardiogram vector;

[0145] Track the changing trajectory of the ECG vector and calculate its velocity and acceleration dynamic parameters;

[0146] Identify and locate ECG waveform feature points based on dynamic parameters of ECG vectors, including the start and end points and peak points of P waves, QRS waves, T waves and U waves;

[0147] The normalization formula is:

[0148]

[0149] In the formula, x i ' is the i-th normalized ECG signal, x i is the ith corrected ECG signal, x max , x min are the maximum and minimum values ​​of the corrected ECG signal respectively.

[0150] After converting multi-lead ECG data into vectorcardiogram data, the spatial information of vectorcardiogram can be used to quickly and accurately identify ECG feature points. This method has broad application prospects in automatic analysis of ECG, detection and diagnosis of arrhythmias, etc. In addition, vectorcardiogram also provides richer information than traditional ECG, which helps to more comprehensively understand the electrophysiological state of the heart.

[0151] Reference Fig. 9 As shown, the ECG waveform feature point information is compared with the ECG waveform feature point information in the ECG database, and the diagnosis and classification of the patient's heart disease specifically include:

[0152] Determine whether each ECG waveform feature point information is not within a normal threshold range, if so, output the ECG waveform feature point information as abnormal information, if not, output the ECG waveform feature point information as normal information;

[0153] Perform similarity matching between the abnormal information and the ECG waveform feature point information in the ECG database, and output the ECG waveform feature point information with the highest similarity;

[0154] The ECG waveform feature point information with the highest similarity is identified to correspond to heart disease, and is output as a possible disease of the current patient.

[0155] It has important application value in the field of automatic electrocardiogram analysis and diagnosis, and provides a reliable basis for the diagnosis and treatment of cardiovascular diseases.

[0156] Furthermore, the present solution also proposes a computer-readable storage medium on which a computer-readable program is stored. When the computer-readable program is called, the above-mentioned method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission is executed.

[0157] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state drive (SSD).

[0158] To sum up, the advantages of the present invention are: the baseline tracking algorithm can effectively eliminate the influence of baseline drift on electrocardiogram detection, improve the accuracy of electrocardiogram analysis, convert multi-lead information into heart vectors, and use the spatial information of heart vectors to quickly and accurately identify electrocardiogram feature points. The algorithm has important application value in the field of automatic electrocardiogram analysis and automatic diagnosis, provides a reliable basis for the diagnosis and treatment of cardiovascular diseases, improves the convenience and efficiency of clinical use through wireless data transmission, and also improves the comfort of patients.

[0159] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission, characterized in that: include: Adhere corresponding electrode sheets to specific body parts of the patient, wherein the specific body parts include the left hand, the right hand, the left leg, the right leg and the chest; The potential information collected by the electrode sheet is compressed using multi-channel adaptive vector quantization compression technology to obtain compressed potential information; By means of Bluetooth transmission, the compression potential information is transmitted to the electrocardiograph through the Bluetooth chip in the electrode sheet for subsequent data processing; The electrocardiograph determines whether the amount of compressed potential information data reaches a preset threshold value. If so, a collection stop signal is fed back to each electrode sheet. If not, no output is made. Construct a low-pass filter to filter the compressed potential information to obtain an electrocardiogram signal; Correcting the baseline drift in the electrocardiogram signal by using a baseline tracking algorithm to obtain a corrected electrocardiogram signal; Based on the principle of vectorcardiography, the corrected ECG signal is converted into vectorcardiography data, and the dynamic parameters of the vectorcardiography are used to identify and locate the characteristic points of the ECG waveform; The ECG waveform feature point information is compared with the ECG waveform feature point information in the ECG database to diagnose and classify the patient's heart disease.

2. The method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission according to claim 1, characterized in that: The step of attaching the corresponding electrode sheet to the specific body part of the patient specifically includes: Place the electrodes on the left hand, right hand, left leg, and right leg respectively; Place the electrode in the fourth intercostal space on the right side of the sternum, i.e. the first right ventricle; Place the electrode in the fourth space on the left side of the sternum, i.e. the second right ventricle; Place the electrode on the midpoint of the line connecting the fourth rib on the left side of the sternum and the fifth rib on the midclavicular line, which is the first ventricular septum. Place the electrode at the intersection of the left midclavicular line and the ventricular interspace, i.e., the second ventricular septum; Place the electrode pad at the intersection of the second ventricular septum level and the anterior axillary line, i.e., the first left ventricle; Place the electrode at the intersection of the second ventricular septum level and the mid-axillary line, that is, the second left ventricle.

3. The method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission according to claim 2, characterized in that: The method of using multi-channel adaptive vector quantization compression technology to compress the potential information collected by the electrode sheet to obtain compressed potential information specifically includes: A codebook is predefined to represent possible input vectors; Combine the data samples from the same time points of different electrodes into one input vector; Based on each input vector, the Euclidean distance between each output vector and each vector in the codebook is calculated using the Euclidean distance formula; Output the codebook vector with the smallest Euclidean distance as the approximate representation of the input vector; Replace each input vector with the index of the codebook vector it approximates; Summarize and output all the approximate codebook vectors as compressed potential information; The Euclidean distance formula is: In the formula, is the Euclidean distance between the i-th input vector and the j-th codebook vector, a i，k is the k-th dimension data of the i-th input vector, b j，k is the k-th dimension data of the j-th codebook vector, and n is the dimension of the vector.

4. The method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission according to claim 3, characterized in that: The method of transmitting the compression potential information to the electrocardiograph through the Bluetooth chip in the electrode sheet for subsequent data processing specifically includes: The Bluetooth chip built into the electrode sheet presets relevant Bluetooth parameters, which include Bluetooth address, pairing key and transmission protocol; The electrocardiograph turns on the Bluetooth function and searches for nearby Bluetooth devices; When the electrocardiograph finds the Bluetooth chip built into the electrode, the connection between the Bluetooth chip and the electrocardiograph is established by manually inputting the pairing key; The Bluetooth chip transmits the compression potential information to the electrocardiograph via Bluetooth transmission.

5. The method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission according to claim 4, characterized in that: The electrocardiograph determines whether the amount of compression potential information data reaches a preset threshold value specifically including: Based on the limitation of storage space of the electrocardiograph, a first preset threshold is preset; Manually adjust the first preset threshold to the second preset threshold according to real-time requirements or specific conditions of the patient; The electrocardiograph determines whether the amount of compressed potential information data reaches a second preset threshold value, and if so, feeds back a collection stop signal to each electrode sheet, and if not, does not output; Each electrode sheet stops collecting potential information after receiving the collection stop signal.

6. The method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission according to claim 5, characterized in that: The construction of a low-pass filter to filter the compressed potential information to obtain an electrocardiogram signal specifically includes: A low-pass filter is constructed by using resistor and capacitor elements; The corner frequency of the low-pass filter is calculated using a corner frequency formula based on the resistance value of the resistor element and the capacitance value of the capacitor element; Using a low-pass filter to filter the compressed potential information; Determine whether the frequency of the input signal is lower than the turning frequency. If so, the output is an electrocardiogram signal; if not, the output is a noise signal. The transition frequency formula is: Where f0 is the corner frequency of the low-pass filter, R is the resistance value of the resistor, and C is the capacitance value of the capacitor.

7. The method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission according to claim 6, characterized in that: The method of correcting the baseline drift in the electrocardiogram signal by using the baseline tracking algorithm to obtain the corrected electrocardiogram signal specifically includes: Preset the sliding window size and sliding step size according to the characteristics of the electrocardiogram signal; The sliding window is placed at the starting position of the electrocardiogram signal, and the baseline position of the window is estimated by calculating the median value of the electrocardiogram signal within the sliding window; As the window slides, the baseline estimate of the new window is smoothed with the baseline estimate of the previous window, and the baseline estimate is continuously updated; Determine whether the sliding window traverses the ECG signal. If so, output the baseline estimation value as the baseline value. If not, no output is made. A baseline drift correction operation is performed on the electrocardiogram signal, and the baseline value is subtracted from the electrocardiogram signal to obtain a corrected electrocardiogram signal.

8. The method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission according to claim 7, characterized in that: The method of converting the corrected ECG signal into ECG vector data based on the principle of vector cardiology and using the dynamic parameters of the ECG vector to identify and locate ECG waveform feature points specifically includes: Using a normalization formula to perform data normalization processing on the corrected electrocardiogram signal to obtain a normalized electrocardiogram signal; Define a three-dimensional coordinate system for the human body, where the X-axis is the horizontal direction, the Y-axis is the vertical direction passing through the center of the heart, and the Z-axis is from bottom to top and perpendicular to the X-axis and Y-axis; Perform a dot product operation on the normalized electrocardiogram signal and the basis vectors of the coordinate system to obtain the component of the signal on each coordinate axis; The components of the signal on each coordinate axis are synthesized into a three-dimensional electrocardiogram vector; Track the changing trajectory of the ECG vector and calculate its velocity and acceleration dynamic parameters; Identify and locate ECG waveform feature points based on dynamic parameters of ECG vectors, including the start and end points and peak points of P waves, QRS waves, T waves and U waves; The normalization formula is: In the formula, x i ′ is the i-th normalized ECG signal, x i is the ith corrected ECG signal, x max , x min are the maximum and minimum values ​​of the corrected ECG signal respectively.

9. The method for information interaction between an electrocardiograph and an electrode sheet based on wireless data transmission according to claim 8, characterized in that: The comparing of the ECG waveform feature point information with the ECG waveform feature point information in the ECG database to diagnose and classify the patient's heart disease specifically includes: Determine whether each ECG waveform feature point information is not within a normal threshold range, if so, output the ECG waveform feature point information as abnormal information, if not, output the ECG waveform feature point information as normal information; Perform similarity matching between the abnormal information and the ECG waveform feature point information in the ECG database, and output the ECG waveform feature point information with the highest similarity; The ECG waveform feature point information with the highest similarity is identified to correspond to heart disease, and is output as a possible disease of the current patient.

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