Using the Robust High Density-surface Electromyography Features for Real-Time Hand Gestures Classification

Using High-Density surface Electromyography (HD-sEMG) signals for gesture classification has augmented the spatial information of muscle activity by increasing the density and convergence of the electrodes. In this paper, spatial features are extracted from HD-sEMG data. These features generated by combining HOG features of HD-sEMG map and intensity features calculated from the average of segmented HD-sEMG map which is denoted as (AIH) features....