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A method for detecting the starting point of qrs complex of multi-lead electrocardiographic signal

A technology of QRS complex and detection method, which is applied in diagnostic recording/measurement, medical science, diagnosis, etc. It can solve problems such as strong algorithm dependence, large calculation amount of wavelet transform method, irregular RR interval, etc., and achieve accurate detection High rate, simple algorithm, strong real-time detection effect

Active Publication Date: 2021-10-26
FUDAN UNIV
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AI Technical Summary

Problems solved by technology

[0003] The template matching method needs to make corresponding adjustments according to the differences of different individuals. The algorithm is highly dependent and susceptible to noise interference, and the detection results are often unsatisfactory.
When arrhythmia occurs, especially premature ventricular contractions, the amplitude of the R wave of the QRS complex changes greatly, and the RR interval is irregular, and the traditional differential threshold method cannot be accurately located
Although the method of artificial neural network has high adaptability and good detection effect, the realization of this method requires a large number of representative samples, which is difficult to realize in the actual application process.
The wavelet transform method has a large amount of calculation, complicated steps, and long time-consuming, and it is impossible to locate the start and end points

Method used

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  • A method for detecting the starting point of qrs complex of multi-lead electrocardiographic signal
  • A method for detecting the starting point of qrs complex of multi-lead electrocardiographic signal
  • A method for detecting the starting point of qrs complex of multi-lead electrocardiographic signal

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Embodiment 1

[0037] Embodiment 1: The method for detecting the starting point of the QRS complex of the present invention is applied to the sinus rhythm signal (the rhythm of different parts is consistent). In this embodiment, the body surface 12-lead electrocardiogram (that is, the number of leads n=12) with a sampling rate of 1000 Hz is used, and the workflow is as follows:

[0038] (1) Observe the body surface 12-lead electrocardiographic signal (digital signal) of the sinus rhythm that is collected synchronously, such as figure 2 (a) shown. The light gray horizontal line for each lead represents its zero potential line. It can be seen from the figure that the ECG signals of some leads have serious baseline drift, such as I, II, III, aVR, aVL, aVF, V2, V3, V4, V5, and V6.

[0039](2) Preprocessing the body surface 12-lead electrocardiographic signals in sinus rhythm in step (1). Firstly, the signal is decomposed into 10 layers by using the sym4 wavelet basis function. For the 1000Hz...

Embodiment 2

[0044] Embodiment 2: apply the detection method of QRS wave group starting point of the present invention to premature ventricular beat signal (before sinoatrial node impulse has not yet arrived at ventricle, any position in the ventricle or the ectopic rhythm point of the interventricular septum sends out electric impulse in advance , causing depolarization of the ventricles). In this embodiment, the body surface 12-lead electrocardiogram (that is, the number of leads n=12) with a sampling rate of 1000 Hz is used, and the workflow is as follows:

[0045] (1) Observe the body surface 12-lead electrocardiographic signal (digital signal) of polymorphic ventricular premature beats that is collected synchronously, such as image 3 (a) shown. The light gray horizontal line of each lead indicates its zero potential line. It can be seen from the figure that there are serious baseline drifts in the ECG signals of some leads, such as II, III, aVR, aVL, AVF, V1, V3, V4, V5 , V6.

[0...

Embodiment 3

[0051] Embodiment 3: The method for detecting the starting point of the QRS complex of the present invention is applied to the signal of atrial fibrillation (there are multiple rhythms, and the rhythms in different parts may be inconsistent). In this embodiment, the body surface 12-lead electrocardiogram (that is, the number of leads n=12) with a sampling rate of 1000 Hz is used, and the workflow is as follows:

[0052] (1) observe the body surface 12-lead electrocardiographic signal (digital signal) of atrial fibrillation collected synchronously, such as Figure 4 (a) shown. The light gray horizontal line of each lead represents its zero potential line. It can be seen that the ECG signals of some leads have serious baseline drift, such as I, II, aVR, aVL, V3, V5, and V6.

[0053] (2) Preprocessing the 12-lead electrocardiographic signal of atrial fibrillation in step (1). Firstly, the signal is decomposed into 10 layers by using the sym4 wavelet basis function. For the 1000...

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Abstract

The invention relates to a method for detecting the starting point of the QRS wave group of multi-lead electrocardiographic signals. Use ECG acquisition technology to collect multi-lead ECG signals; preprocess the multi-lead ECG signals to obtain signals after removing baseline drift and high-frequency noise; normalize the signals to obtain normalized multi-lead ECG signals Connect ECG signals; calculate the root mean square RMS of the normalized multi-lead ECG signals and the detection function DEF, and calculate the threshold by learning the values ​​of RMS and DEF for several seconds before, and view the DEF peak points that meet the threshold conditions is the starting point of the QRS complex. The method of the invention has the advantages of high detection accuracy, simple algorithm, real-time operation and the like. The method of the invention is suitable for long-range or short-range electrocardiographic signals, can be used for analyzing sinus rhythm signals or arrhythmia signals, and has certain application value in electrophysiological mechanism research and clinical medicine. The method of the invention can be extended to the excitation analysis and related quantification research of intracardiac electrical signals.

Description

technical field [0001] The invention relates to a method for detecting the starting point of the QRS wave group of multi-lead electrocardiographic signals. Background technique [0002] In the ECG cycle signal, the QRS wave group has the largest amplitude and the most obvious characteristics. Therefore, in the existing ECG signal feature point detection algorithm, there are many detection methods related to the QRS wave group. The common methods are: template matching method, difference Threshold method, artificial neural network method and wavelet transform method. [0003] The template matching method needs to make corresponding adjustments according to the differences of different individuals. The algorithm is highly dependent and susceptible to noise interference, and the detection results are often unsatisfactory. When arrhythmia occurs, especially premature ventricular contractions, the amplitude of the R wave of the QRS complex changes greatly, and the RR interval is...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/318A61B5/366A61B5/00A61B5/353A61B5/355A61B5/358
CPCA61B5/7203A61B5/7235A61B5/316A61B5/366
Inventor 杨翠微何凯悦陈家曦丁小曼
Owner FUDAN UNIV
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