Research on finger key-press gesture recognition based on surface electromyographic signals / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 352-370, 2011.
Article
in Chinese
| WPRIM
| ID: wpr-306560
ABSTRACT
This article reported researches on the pattern recognition of finger key-press gestures based on surface electromyographic (SEMG) signals. All the gestures were defined referring to the PC standard keyboard, and totally 16 sorts of key-press gestures relating to the right hand were defined. The SEMG signals were collected from the forearm of the subjects by 4 sensors. And two kinds of pattern recognition experiments were designed and implemented for exploring the feasibility and repeatability of the key-press gesture recognition based on SEMG signals. The results from 6 subjects showed, by using the same-day templates, that the average classification rates of 16 defined key-press gestures reached above 75.8%. Moreover, when the training samples added up to 5 days, the recognition accuracies approached those obtained with the same-day templates. The experimental results confirm the feasibility and repeatability of SEMG-based key-press gestures classification, which is meaningful for the implementation of myoelectric control-based virtual keyboard interaction.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Physiology
/
Algorithms
/
Signal Processing, Computer-Assisted
/
Pattern Recognition, Automated
/
Muscle, Skeletal
/
Electromyography
/
Fingers
/
Gestures
/
Methods
/
Movement
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2011
Type:
Article
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