Time Domain Analysis of EMG Signals using KNN and SVM Techniques

Abstract

The EMG signals that have been processed can mimic human movements. For this study, raw EMG data obtained when the hands are in repose (rest), in a clasp, and when the wrist is buckled and stretched were used to categorise four distinct forms of hand gestures using a MATLAB-based intelligent framework (open access data set). Statistical-time-domain features are applied to sort various hand gestures in this investigation. The K-Nearest-Neighbor (KNN) and Support-Vector-Machine (SVM) classifiers are used for classification and comparison. Furthermore, our method outperforms a state-of-the-art method on other data sets of hand gestures.