Title: Design of a hand gesture recognition system based on forearm surface electromyography feedback

Authors: Wei Zhuang; Yi Zhan; Yue Han; Jian Su; Chunming Gao; Dan Yang

Addresses: School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China ' School of Engineering and Technology, University of Washington Tacoma, Tacoma, WA 98402, USA ' School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, Liaoning 114051, China

Abstract: This paper presents a study of using surface electromyography (SEMG) for hand gesture recognitions. A SEMG acquisition system is discussed in this paper. The characteristics of SEMG are introduced and the transformation characteristics are analysed as well. Then the selected gestures and the location for the SEMG sensor are determined. The process of pattern recognition and the reason of selecting SVM classifier are presented in detail, and the kernel function selection of SVM is discussed. Three optimisation methods of parameters are compared using the cross-validation method. Finally, the parameters obtained by the genetic algorithm are used to test the model and the recognition performance.

Keywords: MYO; wearable technology; gesture recognition; support vector machine.

DOI: 10.1504/IJES.2020.108864

International Journal of Embedded Systems, 2020 Vol.13 No.2, pp.169 - 179

Received: 26 Feb 2019
Accepted: 29 Apr 2019

Published online: 11 May 2020 *

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