Fractal analysis features for weak and single-channel upper-limb EMG signals

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.

► EMG signals may be weak (small movements or minor corresponding muscles). ► Classifying EMG at low-level is difficult, particularly in a single-channel system. ► Classification of low-level EMG signals with a single channel is investigated. ► DFA performs better in EMG classification than other commonly used features. ► DFA may be suitable for HCIs for patients, the elderly and amputees.