Research on gesture definition and electrode placementin pattern recognition of hand gesture action SEMG

Authors:
Xu Zhang;Xiang Chen;Zhang-yan Zhao;You-qiang Tu;Ji-hai Yang;Vuokko Lantz;Kong-qiao Wang
Affiliations:
Department of Electronics Science & Technology, University of Science & Technology of China, Hefei, China;Department of Electronics Science & Technology, University of Science & Technology of China, Hefei, China;Department of Electronics Science & Technology, University of Science & Technology of China, Hefei, China;Department of Electronics Science & Technology, University of Science & Technology of China, Hefei, China;Department of Electronics Science & Technology, University of Science & Technology of China, Hefei, China;Nokia Research Center, Interaction CTC, Interacting in Smart Environments, Finland;Nokia Research Center, NOKIA China, Investment CO., LTD., Beijing
Venue:
ICMB'08 Proceedings of the 1st international conference on Medical biometrics
Year:
2008

Citing 2
Cited 1

Toward subtle intimate interfaces for mobile devices using an EMG controller

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Robust coding schemes for indexing and retrieval from large face databases

IEEE Transactions on Image Processing

Key-press gestures recognition and interaction based on SEMG signals

International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction

Quantified Score

Hi-index	0.00

Visualization

Abstract

The goal of this study is to explore the effects of electrode placement on the hand gesture pattern recognition performance. We have conducted experiments with surface EMG sensors using two detecting electrode channels. In total 25 different hand gestures and 10 different electrode positions for measuring muscle activities have been evaluated. Based on the experimental results, dependencies between surface EMG signal detection positions and hand gesture recognition performance have been analyzed and summarized as suggestions how to define hand gestures and select suitable electrode positions for a myoelectric control system. This work provides useful insight for the development of a medical rehabilitation system based on EMG technique.