[A method of QRS complexes detection based on complex wavelet decomposing].
The extraction and identification of ECG (electrocardiogram) signal characteristic parameters are the basic steps toward ECG analysis and diagnosis. The fast and precise detection of QRS complexes is very important in ECG signal analysis, for it is the precondition of the correlative parameters calculation and diagnosis. In our work, firstly, we used the modulus value of complex wavelet decomposition to detect QRS complexes from ECG signal. As the shape and amplitude of ECG signal varies from person to person, we utilized the self-learning algorithm for adjusting the threshold to adapt the changes. The correct detection rate of QRS complexes is up to 99.81% based on MIT-BIH ECG data. Finally, we used the similar methods to detect the P and T waves, after QRS complexes detection.
Chen
Wenli
W
College of Mathematics and Software Science, Sichuan Normnal University, Chengdu 610068, China.
Mo
Zhiwen
Z
D000465:Algorithms; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D012815:Signal Processing, Computer-Assisted