心室纤颤和心动过速的小波非广度熵分析

Tsallis multiresolution entropy analysis of ventricular fibrillation and ventricular tachycardia

为了对心动过速和心室纤颤进行准确而可靠的识别,提出了基于小波的多分辨率分析和熵相结合的分析方法.利用传统的Shannon熵信号分析方法获得的室颤和室速的识别率分别为96.4%和98.2%,而用非广度框架进行分析时获得的室颤和室速的识别率分别为100%和98.2%.表明作为检测室颤与室速的一个判据,Tsallis多分辨率熵(MRET)比Shannon多分辨率熵(MRE)具有更强的识别能力.该方法是一种稳定的、有效的特征提取方法,为其他非平稳生理信号的分析提供了新的手段.

A study of ventricular fibrillation and ventricular tachycardia was undertaken using wavelet-based muhiresolution analysis. We adapted the analysis to a nonextensive （Tsallis） scenario on the basis of conventional Shannon entropy analysis of signals. It is shown that, as a criteria for detecting between VF and VT, Tsallis＇ muhiresolution entropy （MRET） provides better discrimination power than the Shannon＇ s muhiresolution entropy （MRE） and this approach has great potentials in analyzing other nonstationary physiological signals.