QRS wave group detection based on B-Spline wavelet and adaptive threshold
An effective algorithm for detecting QRS wave group was presented. The ECG signal is de-composed with the equivalent filter of a biorthogonal spline wavelet by Mallat pyramid decomposition. The signal singularitys Lipschitz exponentwas used to analyze the relationship between the signal singularity (peak R) and the zero-crossing point of the modulus maximum pair of its wavelet transform,the Biorthogonal spline wavelet can detect Singular point well ,Aiming at the defects of different approaches, we choose 2-orderB -Spline wavelet as mother wavelet which filter has a small quantity of coefficient and combines the self-apaptation threshold method to improve the detection rate, the results by using the MIT-BIH Arrhythmia database improves this approach could detect the ECG signals with high noise and base-line drift ,the detection rate reach more than 99.79％.The detection speed is better than many other detection approaches and has good real time effect
lipschitz exponent wavelet QRS adaptive
Qing Chen Jicheng Liu Guoliang Li
Department of Electronic Engineering.Chengdu University of Information Technology
国际会议
长春
英文
272-275
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）