A testing system for a real-time gesture classification using surface EMG

This study addresses the development of a testing system for pattern-recognition based strategies of myoelectric control. This text describes the structure and components of the proposed system, as well as a process of its testing. The latter included an acquisition of an accompanying EMG, using Myo (TM) armband by Thalmic Labs Inc.(TM), for six different gestures (classes) from seven subjects, as well as its processing, feature extraction, training the classifier and further real-time validation. The results show that system provides acceptable classification rates. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.