Multiple Hand Gesture Recognition based on Surface EMG Signal
For realizing a multi-DOF myoelectric control system with a minimal number of sensors, research work on the recognition of twenty-four hand gestures based on two-channel surface EMG signal measured from human forearm muscles has been carried out. Third-order AR model coefficients, Mean Absolute Value and Mean Absolute Value ratio of the sEMG signal segments were used as features and the recognition of gestures was performed with a Linear Bayesian Classifier. Our experimental results show that the proposed two sensors setup and the sEMG signal processing and recognition methods are well suited for distinguishing hand gestures consisting of various wrist motions and single finger extension.
action SEMG signal gesture pattern recognition myoelectric control
Xiang Chen Xu Zhang Zhang-Yan Zhao Ji-Hai Yang Vuokko Lantz Kong-Qiao Wang
Electronic Science & Technology Dept.University of Science & Technology of China, Hefei, China Interaction CTC, Interacting in Smart Environments Nokia Research Center, Helsinki, Finland Visual Interaction Systems Nokia Research Center, SRC Beijing, China
国际会议
武汉
英文
516-519
2007-07-06（万方平台首次上网日期，不代表论文的发表时间）