The quadratic biorthogonal B-spline wavelet transform algorithm achieves a 99.89% accuracy rate in detecting QRS waves, effectively identifying occasional negative and irregular R waves.
Supports wavelet-based QRS detection in controlled datasets; leaves open prospective validation in diverse clinical populations.
In order to solve the problems of occasional occurrence algorithm of negative R waves and misdetection and false detection of irregular R waves, compensates for the misdetection and false detection of R waves is introduced to detect QRS waves using quadratic biorthogonal B-spline wavelet transform, the correspondence relationship between signal singular points and zero-crossing points is analyzed by Mallat algorithm from the perspectives of modulus maxima of signals on different scales and Lipschitz exponent, QRS waves are obtained. Finally, this paper employed Matlab to extract the QRS characteristic waveforms of ECG signals from MIT-BIH arrhythmia database. The results show that the detection accuracy rate for QRS waves is up to 99.89% with higher robustness for several common interferences with ECG signals.
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Shang et al. (2014) studied this question.
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