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Time-domain features for sEMG signal classification: A brief survey
1 : Biomécanique et Bioingénierie
Université de Technologie de Compiègne, Centre National de la Recherche Scientifique
Surface electromyography (sEMG) signals have been widely used in various robotic and medical applications. Thus, Time domain features have been shown to be effective in extracting useful information from these signals for classification purposes. They are mainly based on amplitude, energy, and time statistics. Furthermore, they can be easily implemented in real-time systems and combined to conventional supervised learning algorithms. The proposed study depicts an presents an up-to-date literature review highlighting the significant time-domain features and their applications in the field.
