Effect of Surface Electrode Orientation on Independent Component Analysis for Feature Extraction of Surface Motor Unit Action Potential

Recently, application of Independent Component Analysis (ICA) has been reported for effective decomposition of surface electromyogram (SEMG) signals into a train of surface motor unit action potentials (SMUAPs) of a single motor unit (MU). Results of ICA were not always sufficient as the feature extraction of SWAP at first dorsal interosseous muscle (FDI). The purpose of this study is to propose an effective method for feature extraction of SMUAP by simulation study of focusing on the effects of electrode orientation. SEMG signals were created with the model and application of ICA was applied to the signals. The present study showed that the useful and actual method of ICA application was to repeat measurement of SEMG signals with varying the electrode orientation, and then to select the better signals for the feature extraction by executing ICA algorithm.