A Tensor-Based Method for Completion of Missing Electromyography Data

This paper discusses the recovery of missing data in surface electromyography (sEMG) signals that arise during the acquisition process. Missing values in the EMG signals occur due to either the disconnection of electrodes, artifacts and muscle fatigue or the incapability of instruments to collect very low-amplitude signals. In many real-world EMG-related applications, algorithms need complete data to make accurate and correct predictions, or...