Finger Motion Decoding Using EMG Signals Corresponding Various Arm Postures
Experimental Neurobiology
;
: 54-61, 2010.
Article
in English
| WPRIM
| ID: wpr-27763
ABSTRACT
We provide a novel method to infer finger flexing motions using a four-channel surface electromyogram (EMG). Surface EMG signals can be recorded from the human body non-invasively and easily. Surface EMG signals in this study were obtained from four channel electrodes placed around the forearm. The motions consist of the flexion of five single fingers (thumb, index finger, middle finger, ring finger, and little finger) and three multi-finger motions. The maximum likelihood estimation was used to infer the finger motions. Experimental results have shown that this method can successfully infer the finger flexing motions. The average accuracy was as high as 97.75%. In addition, we examined the influence of inference accuracies with the various arm postures.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Arm
/
Posture
/
Human Body
/
Electrodes
/
Fingers
/
Forearm
Language:
English
Journal:
Experimental Neurobiology
Year:
2010
Type:
Article
Similar
MEDLINE
...
LILACS
LIS