Fractal analysis features for weak and single-channel upper-limb EMG signals
- 作者：Angkoon Phinyomark ; angkoon.p@hotmail.com ; Pornchai Phukpattaranont ; Chusak Limsakul
- 关键词：Electromyography signal ; Human&ndash ; computer interface ; Multifunction myoelectric control system ; Detrended fluctuation analysis ; Low-level movements ; Robustness ; Surface electrodes
- 刊名：Expert Systems with Applications
- 出版年：2012
- 期刊代码：62_09574174
- 类别：et
- 出版时间：15 September, 2012
- 卷：39
- 期：12
- 页码：11156-11163
- 文件大小：788 K
摘要
Electromyography (EMG) signals are the electrical manifestations of muscle contractions. EMG signals may be weak or at a low level when there is only a small movement in the major corresponding muscle group or when there is a strong movement in the minor corresponding muscle group. Moreover, in a single-channel EMG classification identifying the signals may be difficult. However, weak and single-channel EMG control systems offer a very convenient way of controlling human-computer interfaces (HCIs). Identifying upper-limb movements using a single-channel surface EMG also has a number of rehabilitation and HCI applications. The fractal analysis method, known as detrended fluctuation analysis (DFA), has been suggested for the identification of low-level muscle activations. This study found that DFA performs better in the classification of EMG signals from bifunctional movements of low-level and equal power as compared to other successful and commonly used features based on magnitude and other fractal techniques.