Open AccessA ROBUST QRS COMPLEX DETECTION METHOD BASED ON SHANNON ENERGY ENVELOPE AND HILBERT TRANSFORM
Author(s) -
Wansong Xu,
Fanyu Du
Publication year - 2022
Publication title -
journal of mechanics in medicine and biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.236
H-Index - 30
eISSN - 1793-6810
pISSN - 0219-5194
DOI - 10.1142/s0219519422400139
Subject(s) - hilbert transform , algorithm , envelope detector , computer science , envelope (radar) , qrs complex , robustness (evolution) , artificial intelligence , energy (signal processing) , pattern recognition (psychology) , interference (communication) , signal (programming language) , mathematics , computer vision , bandwidth (computing) , statistics , telecommunications , filter (signal processing) , medicine , amplifier , radar , biochemistry , chemistry , channel (broadcasting) , cardiology , gene , programming language
QRS complex detection plays an important role in electrocardiogram (ECG) automatic analysis. The accuracy and robustness of the detection algorithm greatly affect its practicability. However, the existing detection algorithms are greatly affected by ECG signal quality, and some detection algorithms cannot even work properly due to the poor signal quality. In this paper, a robust QRS complex detection algorithm is proposed based on Shannon energy envelope and Hilbert transform. The detection algorithm extracts the Shannon energy envelope of the preprocessed ECG signal, performs Hilbert transform on the envelope signal, then detects the suspected [Formula: see text]-peaks on the envelope by detecting the position of zero pass and screens the real [Formula: see text]-peaks by using a combination of ECG refractory period and backtracking mechanism. The proposed detection algorithm is validated using MIT-BIH Arrhythmia Database, and achieves the average detection accuracy of 99.69%, sensitivity of 99.81% and positive predictivity of 99.88%. Experimental results show that the proposed detection algorithm can still detect QRS complex correctly under complex interference, and the performance of the algorithm is hardly affected.