An application of the approach combining wavelet transform and energy entropy to remove electrocardiography interference in diaphragmatic electromyographic
Zhou, Q.; Yang, Z.; Fan, Z.; Li, X.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 30(1): 16-21
2013
ISSN/ISBN: 1001-5515 PMID: 23488131 Document Number: 665852
Diaphragmatic electromyographic (EMGdi) signal is a weak biological signal, which contains some significant physiological information of our body respiration system and is susceptible to strong electrocardiography (ECG) signal interference. Based on wavelet transform and theory of information entropy, a new wavelet energy entropy threshold algorithm to remove ECG interference is proposed in this paper. On the base of analysis of wavelet coefficients of each scale, the method sees the information of each scale as a single signal source, equalizes it byzones, and then divides the energy entropy into two categories (i. e., high energy entropy and low energy entropy) through the distribution characteristics of energy entropy of each zone to conduct absolute mean value threshold. In addition, the denoised signal is reconstructed by wavelet coefficients processed. The experimental results showed that the method removed the ECG signal in EMGdi effectively and reserved the available characteristics of EMGdi better.