Single-lead ECG signal PQRST wave joint precise recognition algorithm

Abstract

The invention discloses a single-lead ECG signal PQRST wave joint precise recognition algorithm, wherein the algorithm includes the steps: when inputting a single-lead signal, preprocessing the signalwith a wavelet analysis method, filtering out a noise signal and adjusting the baseline drift of the ECG signal; according to the preprocessed signal, calculating to obtain an R wave peak position ofthe ECG signal by a difference method; according to the R wave peak position and an RR interval, intelligently locating each heartbeat period, and segmenting the ECG signal according to the heartbeatperiod; for the segmented ECG signal, calculating and determining Q wave and S wave positions by a self-adaptive method; and for the segmented ECG signal, recognizing and determining the P wave and Twave peak positions by a convolution method. The PQRST wave recognition method includes recognition of the PQRST wave peaks, the intervals between the waves and the wave-wave interval between different ECG signal segments. The algorithm realizes the recognition of various waves and interval features of the single-lead ECG signal, and provides reliable features for application of the ECG signal classification algorithm by the machine learning method.

Description

Technical field [0001] The present invention relates to the technical field of bioinformatics, and relates to a single-lead ECG signal PQRST wave joint recognition algorithm based on wavelet decomposition and feature point recognition, in particular to the denoising and de-noising of ECG signals during the real-time body wearing process of ECG terminals Baseline drift and real-time PQRST wave feature recognition method. Background technique [0002] The clinical application of ECG signals has a history of more than 100 years, and it is still one of the most important auxiliary examinations in clinical medicine. It is not only used for the diagnosis of cardiovascular diseases, but also an indispensable means for observing changes in the condition of various clinical departments. The electrocardiogram is the "gold standard" for the diagnosis of arrhythmia, and it is non-invasive, economical, convenient, fast, and reproducible, and has advantages that other examination equipment ca...

AI Technical Summary

Problems solved by technology

[0005] In view of the above problems, the present invention provides a single-lead electrocardiographic signal PQRST wave joint accurate recognition algorithm based on wavelet decomposition and feature point recognition, which is used to solve the problems in the prior art that are greatly affected by high-frequency noise and baseline drift, and the detection is accurate A series of problems such as low rate and large amount of calculation

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