Key-press gestures recognition and interaction based on SEMG signals

Authors:
Juan Cheng;Xiang Chen;Zhiyuan Lu;Kongqiao Wang;Minfen Shen
Affiliations:
University of Science & Technology of China, China;University of Science & Technology of China, China;University of Science & Technology of China, China;Nokia Research Center, NOKIA (CHINA) Investment CO. LTD., Beijing, China;Shantou University, China
Venue:
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Year:
2010

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Abstract

This article conducted research on the pattern recognition of keypress finger gestures based on surface electromyographic (SEMG) signals and the feasibility of key -press gestures for interaction application. Two sort of recognition experiments were designed firstly to explore the feasibility and repeatability of the SEMG -based classification of 1 6 key-press finger gestures relating to right hand and 4 control gestures, and the key -press gestures were defined referring to the standard PC key board. Based on the experimental results, 10 quite well recognized key -press gestures were selected as numeric input keys of a simulated phone, and the 4 control gestures were mapped to 4 control keys. Then two types of use tests, namely volume setting and SMS sending were conducted to survey the gesture-base interaction performance and user's attitude to this technique, and the test results showed that users could accept this novel input strategy with fresh experience.