QRS wave morphology detection method and system based on QRS wave position

Abstract

The present disclosure provides a QRS wave form detection method and system based on electrocardiogram QRS wave position, relates to the technical field of electrocardiogram signal processing, and comprises the following steps: acquiring electrocardiogram data to be detected, and pre-processing the electrocardiogram data; identifying the start and end point positions of QRS waves in the electrocardiogram data, and intercepting the QRS wave segments corresponding to all the identified QRS wave start and end point positions; performing a shift operation on the QRS wave segments to record the QRS wave data positions, sequentially numbering, then cutting the QRS wave data according to the recorded position data points and the front and rear two position data points, calculating the absolute value of the cut QRS wave data, taking the maximum value, and judging the current QRS wave form according to a threshold value; and the present disclosure can improve the efficiency of QRS wave form detection.

Description

Technical Field

[0001] This disclosure relates to the field of electrocardiogram signal processing technology, specifically to a method and system for detecting QRS wave morphology based on the location of the electrocardiogram QRS wave. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] The QRS complex reflects the changes in depolarization potential and time between the left and right ventricles. The first downward wave is the Q wave, the upward wave is the R wave, and the following downward wave is the S wave. The time from the beginning to the end of the QRS complex is the QRS duration, representing the potential changes during ventricular depolarization, that is, the new changes that occur during the contraction process of the left and right ventricles. The morphology of the QRS complex indicates whether the heartbeat is within normal fluctuations. In an electrocardiogram, the correct identification of the QRS complex morphology has great clinical reference value. Therefore, the detection of QRS wave morphology plays a very important role in monitoring whether cardiac activity is normal.

[0004] Existing methods for detecting the shape of QRS waves use the extremum method to find the peaks and troughs in the QRS wave. Then, by combining the found extrema with the potential value and amplitude, the various sub-waveforms of the QRS wave are found. Alternatively, the Q wave and S wave are found based on the R wave value obtained from the QRS wave and the number of milliseconds before and after. This method greatly slows down the detection time of QRS wave shape, cannot adapt to QRS wave groups with different widths and amplitudes, and will cause identification errors if there are multiple extrema. Summary of the Invention

[0005] To address the aforementioned issues, this disclosure proposes a method and system for detecting QRS wave morphology based on the location of the electrocardiogram QRS wave. The Pan-Tompkins algorithm is used to identify the start and end points of the QRS wave, and the QRS wave morphology is detected using the start and end point locations.

[0006] According to some embodiments, the present disclosure adopts the following technical solutions:

[0007] Methods for detecting QRS morphology based on the location of the QRS wave on electrocardiogram include:

[0008] Acquire the ECG data to be tested and preprocess the ECG data;

[0009] The start and end points of the QRS waves in the electrocardiogram data are identified, and the QRS segments corresponding to all the identified start and end points of the QRS waves are extracted.

[0010] The QRS band is shifted and the QRS wave data position is recorded and numbered sequentially. Then, the QRS wave data is segmented according to the recorded position data points and the two preceding and following position data points. The absolute value of the segmented QRS wave data is calculated and the maximum value is taken. The current QRS wave morphology is determined based on the threshold.

[0011] According to some embodiments, the present disclosure adopts the following technical solutions:

[0012] A QRS morphology detection system based on ECG QRS location includes:

[0013] The data acquisition module is used to acquire the ECG data to be tested and to preprocess the ECG data;

[0014] The morphology detection module is used to identify the start and end points of the QRS wave in the electrocardiogram data and to extract the QRS segments corresponding to all the identified start and end points of the QRS wave.

[0015] The QRS band is shifted and the QRS wave data position is recorded and numbered sequentially. Then, the QRS wave data is segmented according to the recorded position data points and the two preceding and following position data points. The absolute value of the segmented QRS wave data is calculated and the maximum value is taken. The current QRS wave morphology is determined based on the threshold.

[0016] Compared with the prior art, the beneficial effects of this disclosure are as follows:

[0017] This disclosure provides a QRS wave morphology detection method based on the location of the electrocardiogram (ECG) QRS wave. The Pan-Tompkins algorithm is used to identify the start and end points of the QRS wave. Based on the identified start and end point locations of all QRS waves, the morphology of the QRS band is detected. Before morphology detection, the ECG data is filtered and baseline shifted to eliminate high-frequency interference. This morphology detection method can adapt to QRS groups with different widths and amplitudes, and can solve recognition errors caused by two or more extreme values. Based on the actual acquired QRS groups, it has high recognition accuracy and fast recognition speed. Attached Figure Description

[0018] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0019] Figure 1 This is a flowchart illustrating the method processing of an embodiment of the present disclosure; Detailed Implementation

[0020] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0021] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0022] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0023] Example 1

[0024] One embodiment of this disclosure provides a method for detecting QRS wave morphology based on the location of the electrocardiogram QRS wave, including:

[0025] Step 1: Acquire the ECG data to be tested and preprocess the ECG data;

[0026] Step 2: Identify the start and end points of the QRS waves in the ECG data, and extract the QRS segments corresponding to all identified start and end points of the QRS waves.

[0027] Step 3: Perform a translation operation on the QRS band and record the QRS wave data position, number them sequentially, and then divide the QRS wave data according to the recorded position data points based on the two preceding and following position data points. Take the absolute value of the divided QRS wave data and take the maximum value. Determine the current QRS wave morphology based on the threshold.

[0028] As one embodiment, the specific implementation process of the QRS wave morphology detection method based on the location of the electrocardiogram QRS wave disclosed herein includes:

[0029] Step 1: Acquire the ECG data to be tested and preprocess the ECG data;

[0030] Obtain the ECG dataset ALL_ECG.

[0031]

[0032] In the formula Let i be the i-th electrocardiogram signal, i∈{1,…,n};

[0033] Preprocessing methods include:

[0034] Filter the ALL_ECG electrocardiogram data to eliminate high-frequency interference;

[0035] Baseline drift was removed from the filtered ECG data ALL_ECG, and then the processed ECG data was saved as Original_ECG.

[0036] Step 2: Identify the start and end points of the QRS waves in the ECG data, and extract the QRS segments corresponding to all identified start and end points of the QRS waves;

[0037] The Pan-Tompkins algorithm is used to identify the start and end points of the QRS wave. The QRS bands corresponding to all the identified start and end points of the QRS wave are extracted from the signal and the signal is saved.

[0038] Specifically, the Pan-Tompkins algorithm is used to identify the start and end points of the QRS wave. Based on the identified start and end points of the QRS wave, the corresponding waveforms on the Original_ECG signal are extracted and the signal is saved as Cut_ECG.

[0039] Step 3: Perform a translation operation on the QRS band and record the QRS wave data position, number them sequentially, and then divide the QRS wave data according to the recorded position data points based on the two preceding and following position data points;

[0040] The QRS bands are translated and the QRS wave data positions are recorded and numbered sequentially. This includes: acquiring one QRS band data, translating the first data point of the QRS band data to the position where the vertical axis is zero, and performing the same translation operation on the other data points of the other QRS band data according to the direction and magnitude of the translation of the first data point.

[0041] The QRS band data are numbered according to their positions. The position of the first data point is recorded. If the product of the current data point and the next data point is greater than or equal to zero, the position of the next data point is recorded, except for the first data point. The position of the last data point is recorded.

[0042] The recorded data point positions are screened by comparing the positions of the data points one after the other. If the distance is equal to 1, the previous data point position is removed and only the next data point is kept.

[0043] Specifically, we will select a data point from the Cut_ECG signal and denote it as QRS_Sample as an example to illustrate QRS wave morphology identification.

[0044] The first data point of the QRS_Sample data is shifted to the position where the vertical axis is zero. The other data points of the QRS_Sample data are shifted in the same direction and by the same magnitude as the first data point.

[0045] Next, number the QRS_Sample data points according to their positions and record the position of the first data point;

[0046] If the product of the current data point and the next data point is greater than zero, record the position of the next data point. If the product of the current data point and the next data point is zero, also record the position of the next data point. The first data point is not counted.

[0047] Then, record the position of the last data point.

[0048] Furthermore, a screening operation is performed on the recorded data point positions. The positions of the recorded data points are compared one to the next. If the distance is equal to 1, the previous data point position is removed, and only the next data point is kept.

[0049] Step 4: Divide the QRS wave data into two segments based on the recorded data point positions, and divide the QRS_Sample data into N segments based on the recorded data point positions, where N equals the number of intervals.

[0050] Step 5: Take the absolute value of the segmented QRS wave data and then take the maximum value. Determine the current QRS wave pattern based on the threshold.

[0051] Specifically, based on the N segments of data obtained;

[0052] 1) If the data segment is the first segment, take the maximum value after calculating the absolute value of the data in the first segment and record it as max_value_first. Take the flag returned after calculating the extreme value of the data in the first segment and record it as peak_flag_value_first. Take the maximum value of the data in the first segment directly and record it as max_symbol_first.

[0053] The value is Q or R if max_value_first is greater than or equal to 0.5mV, and q or r if max_value_first is less than 0.5mV.

[0054] If peak_flag_value_first is False, proceed to the next data segment.

[0055] If max_symbol_first is greater than zero, it is R or r; if it is less than zero, it is Q or q.

[0056] Then the morphology type is recorded.

[0057] 2) If the segment is an intermediate data segment, take the absolute value of the data in the segment and record the maximum value as max_value_middle, or directly calculate the maximum value of the data in the segment and record it as max_symbol_middle. Use Rr_flag_middle to indicate whether the type record contains R or r, and use Ss_flag_middle to indicate whether the type record contains S or s.

[0058] If max_value_middle is greater than or equal to 0.5mV, it is either S or R; if max_value_middle is less than 0.5mV, it is either s or r.

[0059] If max_symbol_middle is greater than zero, it is R or r; if it is less than zero, it is S or s.

[0060] If Rr_flag_middle is True, use R' instead of R and r' instead of r;

[0061] If Ss_flag_middle is True, use S' instead of S, and s' instead of s;

[0062] Then the morphology type is recorded.

[0063] 3) If this is the last data segment, record the flag returned after finding the extreme value of the last segment as `peak_flag_value_last`, record the maximum value after taking the absolute value of the data in this segment as `max_value_last`, and record the maximum value directly as `max_symbol_last`. Use `Rr_flag_last` to indicate whether the type record contains R or r, and `Ss_flag_last` to indicate whether the type record contains S or s. Use `last_one_value` to represent the magnitude of the absolute value of the last data point in the last segment.

[0064] If peak_flag_value_first is equal to False, or last_one_value is greater than max_value_last*0.4, return the last record of the type.

[0065] If max_value_last is greater than or equal to 0.5mV, it is either S or R; if max_value_last is less than 0.5mV, it is either s or r.

[0066] If max_symbol_last is greater than zero, it is R or r; if it is less than zero, it is S or s.

[0067] If Rr_flag_last is True, use R' instead of R and r' instead of r;

[0068] If Ss_flag_last is True, use S' instead of S, and s' instead of s;

[0069] Then the morphology type is recorded.

[0070] Finally, return the last morphology type record.

[0071] Example 2

[0072] One embodiment of this disclosure provides a QRS wave morphology detection system based on the location of the electrocardiogram QRS wave, including:

[0073] The data acquisition module is used to acquire the ECG data to be tested and to preprocess the ECG data;

[0074] The morphology detection module is used to identify the start and end points of the QRS wave in the electrocardiogram data and to extract the QRS segments corresponding to all the identified start and end points of the QRS wave.

[0075] The QRS band is shifted and the QRS wave data position is recorded and numbered sequentially. Then, the QRS wave data is segmented according to the recorded position data points and the two preceding and following position data points. The absolute value of the segmented QRS wave data is calculated and the maximum value is taken. The current QRS wave morphology is determined based on the threshold.

[0076] The system in Embodiment 2 specifically executes the method steps described in any one of Embodiment 1.

[0077] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0078] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0079] While the specific embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this disclosure. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this disclosure are still within the scope of protection of this disclosure.

Claims

1. A method for detecting QRS wave morphology based on the location of the QRS wave in an electrocardiogram, characterized in that, include: Acquire the ECG data to be tested and preprocess the ECG data; The start and end points of the QRS waves in the electrocardiogram data are identified, and the QRS segments corresponding to all the identified start and end points are extracted. The QRS band is shifted and the QRS wave data position is recorded and numbered sequentially. Then, the QRS wave data is segmented according to the recorded position data points, and the absolute value of the segmented QRS wave data is calculated and the maximum value is taken. The current QRS wave morphology is determined according to the threshold. The process of recording and sequentially numbering the QRS band translation operation includes: acquiring one QRS band data, translating the first data point of the QRS band data to a position where the vertical axis is zero, and performing the same translation operation on the other data points of the other QRS band data according to the direction and magnitude of the translation of the first data point. The QRS band data are numbered according to their positions. The position of the first data point is recorded. If the product of the current data point and the next data point is greater than or equal to zero, the position of the next data point is recorded, except for the first data point. The position of the last data point is recorded. The recorded data point positions are screened by comparing the positions of the data points one after the other. If the distance is equal to 1, the previous data point position is removed and only the next data point is kept.

2. The QRS wave morphology detection method based on ECG QRS wave location as described in claim 1, characterized in that, The preprocessing includes filtering the ECG data to eliminate high-frequency interference and removing baseline drift from the filtered ECG data.

3. The QRS wave morphology detection method based on ECG QRS wave location as described in claim 1, characterized in that, The start and end points of the QRS complex in the electrocardiogram data are identified, including using the Pan-Tompkins algorithm to identify the start and end points of the QRS complex, extracting the corresponding QRS segments on the signal based on all identified start and end points, and saving the signals.

4. The QRS wave morphology detection method based on ECG QRS wave location as described in claim 1, characterized in that, The QRS wave data is divided into two segments based on the recorded data point positions. If the data segment is the first segment, the maximum value of the absolute value of the data in the first segment is recorded as max_value_first. The flag returned after finding the extreme value of the data in the first segment is recorded as peak_flag_value_first. The maximum value of the data in the first segment is directly recorded as max_symbol_first. If max_value_first is greater than or equal to the set threshold, it is Q or R; if max_value_first is less than the set threshold, it is q or r. If peak_flag_value_first is False, proceed to the next data segment.

5. The QRS wave morphology detection method based on ECG QRS wave location as described in claim 4, characterized in that, If the data segment is an intermediate segment, take the maximum value after calculating the absolute value of the data in the segment and record it as max_value_middle. Take the maximum value directly and record it as max_symbol_middle. Use Rr_flag_middle to indicate whether the type record contains R or r, and use Ss_flag_middle to indicate whether the type record contains S or s.

6. The QRS wave morphology detection method based on ECG QRS wave location as described in claim 5, characterized in that, If max_value_middle is greater than or equal to the set threshold, it is either S or R; if max_value_middle is less than the set threshold, it is either s or r. If max_symbol_middle is greater than zero, it is R or r; if it is less than zero, it is S or s.

7. A QRS wave morphology detection system based on ECG QRS wave location, employing the QRS wave morphology detection method based on ECG QRS wave location as described in any one of claims 1-6, characterized in that, include: The data acquisition module is used to acquire the ECG data to be tested and to preprocess the ECG data; The morphology detection module is used to identify the start and end points of the QRS wave in the electrocardiogram data and to extract the QRS segments corresponding to all the identified start and end points of the QRS wave. The QRS band is shifted and the QRS wave data position is recorded and numbered sequentially. Then, the QRS wave data is segmented according to the recorded position data points and the two preceding and following position data points. The absolute value of the segmented QRS wave data is calculated and the maximum value is taken. The current QRS wave morphology is determined based on the threshold.

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