A testing system for a real-time gesture classification using surface EMG. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Akhmadeev, Konstantin; Rampone, Elena; Yu, Tianyi; Aoustin, Yannick; Carpentier, Eric Le
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 11498
• Page End: 11503
• Publication Date: 2017-07
• Subjects: Electromyography -- EMG -- myoelectric control -- classification -- support vector machine; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.1602
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: 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™ armband by Thalmic Labs Inc.™, 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.