Hand gesture recognition and virtual game control based on 3D accelerometer and EMG sensors

Authors:
Xu Zhang;Xiang Chen;Wen-hui Wang;Ji-hai Yang;Vuokko Lantz;Kong-qiao Wang
Affiliations:
University of Science and Technology of China, Hefei, China;University of Science and Technology of China, Hefei, China;University of Science and Technology of China, Hefei, China;University of Science and Technology of China, Hefei, China;Nokia Research Center, Helsinki, Finland;NOKIA (CHINA) Investment CO. LTD., Beijing, China
Venue:
Proceedings of the 14th international conference on Intelligent user interfaces
Year:
2009

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Abstract

This paper describes a novel hand gesture recognition system that utilizes both multi-channel surface electromyogram (EMG) sensors and 3D accelerometer (ACC) to realize user-friendly interaction between human and computers. Signal segments of meaningful gestures are determined from the continuous EMG signal inputs. Multi-stream Hidden Markov Models consisting of EMG and ACC streams are utilized as decision fusion method to recognize hand gestures. This paper also presents a virtual Rubik's Cube game that is controlled by the hand gestures and is used for evaluating the performance of our hand gesture recognition system. For a set of 18 kinds of gestures, each trained with 10 repetitions, the average recognition accuracy was about 91.7% in real application. The proposed method facilitates intelligent and natural control based on gesture interaction.