원문정보
초록
영어
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.
목차
1. Introduction
2. The Dection Principle Of Wavelet Transform For Singular Points
3. The Selection Of Waveletbase
4. Mallat Algorithm
5. The QRS Charactrtstic Waveform Extraction Based On B-Spline Wavelet
5.1. Relationship between Lipschitz exponent and modulus maxima
5.2. Relationship between R wave peaks and the crossing zero point of modulus maxima couple
5.3. QRS wave detection algorithm flow
6. Conclusions
Acknowledgements
References