Decoding of multiple wrist and hand movements using a transient EMG classifier

Working under the assumption that steady-state EMG signals are more prone to be affected by factors such as differing physiology and fatigue, we investigate the possibility of creating a classifier that acts on the transient EMG observed during muscle contraction. During evaluation we obtained performances comparable to state-of-the-art steady-state EMG controllers; illustrating the possibility of using the transient portion of EMG signals for classification.