Adaptive EMG decomposition in dynamic conditions based on online learning metrics with tunable hyperparameters.

The findings demonstrate the feasibility of accurately decoding MN discharges in real-time during dynamic contractions from wearable systems mounted at the wrist and forearm. Moreover, the study proposes an experimental validation method for EMG decomposition in dynamic tasks.