Paper Info
Title
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.
Year
DOI
Venue
2010
10.1145/1891903.1891950
ICMI-MLMI
Keywords
Field
DocType
electromyographic,human computer interaction,key-press finger gesture,virtual keyboard
Computer science,Gesture,sort,Gesture recognition,Speech recognition,Phone,Human–computer interaction,Virtual keyboard,Volume setting
Conference
Citations 
PageRank 
References 
2
0.36
10
Authors
5
Name
Order
Citations
PageRank
Juan Cheng16211.53
Xiang Chen213930.34
Zhiyuan Lu3311.88
Kongqiao Wang463443.95
M. Shen54512.04