Research on the detection algorithm of electrocardiogram characteristic wave based on energy segmentation and stationary wavelet transform.
10.7507/1001-5515.202002038
- Author:
Jinzhen LIU
1
;
Lifei SUN
1
;
Hui XIONG
1
;
Meiling LIANG
2
Author Information
1. School of Electrical Engineering and Automation, TianGong University, Tianjin 300387, P.R.China.
2. Beijing Zhaoyi Innovation Technology Co., Ltd, Beijing 100088, P.R.China.
- Publication Type:Journal Article
- Keywords:
QRS detection;
energy segmentation;
exercise electrocardiogram;
stationary wavelet transform
- MeSH:
Algorithms;
Arrhythmias, Cardiac;
Electrocardiography;
Heart Rate;
Humans;
Signal Processing, Computer-Assisted;
Wavelet Analysis
- From:
Journal of Biomedical Engineering
2021;38(6):1181-1192
- CountryChina
- Language:Chinese
-
Abstract:
The detection of electrocardiogram (ECG) characteristic wave is the basis of cardiovascular disease analysis and heart rate variability analysis. In order to solve the problems of low detection accuracy and poor real-time performance of ECG signal in the state of motion, this paper proposes a detection algorithm based on segmentation energy and stationary wavelet transform (SWT). Firstly, the energy of ECG signal is calculated by segmenting, and the energy candidate peak is obtained after moving average to detect QRS complex. Secondly, the QRS amplitude is set to zero and the fifth component of SWT is used to locate P wave and T wave. The experimental results show that compared with other algorithms, the algorithm in this paper has high accuracy in detecting QRS complex in different motion states. It only takes 0.22 s to detect QSR complex of a 30-minute ECG record, and the real-time performance is improved obviously. On the basis of QRS complex detection, the accuracy of P wave and T wave detection is higher than 95%. The results show that this method can improve the efficiency of ECG signal detection, and provide a new method for real-time ECG signal classification and cardiovascular disease diagnosis.
