Key-press gestures recognition and interaction based on SEMG signals

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.