东南大学学报（英文版）2005，Vol.21Issue(3)：324-329,6.
基于分形维前臂动作表面肌电信号的分类
Classification of forearm action surface EMG signals based on fractal dimension
摘要
Abstract
Surface electromyogram (EMG) signals were identified by fractal dimension.Two patterns of surface EMG signals were acquired from 30 healthy volunteers' right forearm flexor respectively in the process of forearm supination (FS) and forearm pronation (FP).After the raw action surface EMG (ASEMG) signal was decomposed into several sub-signals with wavelet packet transform (WPT),five fractal dimensions were respectively calculated from the raw signal and four sub-signals by the method based on fuzzy self-similarity.The results show that calculated from the sub-signal in the band 0 to 125 Hz,the fractal dimensions of FS ASEMG signals and FP ASEMG signals distributed in two different regions,and its error rate based on Bayes decision was no more than 2.26%.Therefore,the fractal dimension is an appropriate feature by which an FS ASEMG signal is distinguished from an FP ASEMG signal.关键词
动作表面肌电信号/分形维/小波包变换/模糊自相似性/Bayes决策Key words
action surface electromyogram (ASEMG) signal/fractal dimension/wavelet packet transform (WPT)/fuzzy self-similarity/Bayes decision分类
医药卫生引用本文复制引用
胡晓,王志中,任小梅..基于分形维前臂动作表面肌电信号的分类[J].东南大学学报（英文版）,2005,21(3):324-329,6.基金项目
The National Natural Science Foundation of China (No.60171006),the National Basic Research Program of China (973 Program) (No.2005CB724303). （No.60171006）
