DocumentCode
1508627
Title
An enhanced feature extraction algorithm for EMG pattern classification
Author
Lee, Seok-pil ; Kim, Jung-Sub ; Park, Sang-Hui
Author_Institution
Dept. of Electr. Eng., Yonsei Univ., Seoul, South Korea
Volume
4
Issue
4
fYear
1996
fDate
12/1/1996 12:00:00 AM
Firstpage
439
Lastpage
443
Abstract
The authors present an enhanced feature extraction algorithm which combines block and adaptive processing to identify motion command for the control of a prosthetic arm. The algorithm is capable of precise and stable feature extraction. A sample application with the block processing stationary model parameters is provided to evaluate the feasibility of the adaptive cepstrum vector extracted by the proposed algorithm for electromyographic (EMG) pattern classification
Keywords
adaptive signal processing; algorithm theory; artificial limbs; electromyography; feature extraction; medical signal processing; EMG pattern classification; adaptive cepstrum vector; block processing; electromyographic pattern classification; enhanced feature extraction algorithm; motion command identification; precise stable feature extraction; prosthetic arm control; Cepstrum; Circuits; Displays; Electromyography; Feature extraction; Microcontrollers; Packaging; Pattern classification; Signal processing; Signal processing algorithms;
fLanguage
English
Journal_Title
Rehabilitation Engineering, IEEE Transactions on
Publisher
ieee
ISSN
1063-6528
Type
jour
DOI
10.1109/86.547948
Filename
547948
Link To Document