Title :
Improving myoelectric signal classification using wavelet packets and principal components analysis
Author :
Englehart, K. ; Hudgins, B. ; Park, P.A. ; Stevenson, M.
Author_Institution :
Dept. of Electr. & Comput. Eng., New Brunswick Univ., Fredericton, NB, Canada
Abstract :
An accurate and computationally efficient means of classifying surface myoelectric signals has been the subject of considerable research effort in recent years. This work demonstrates how this may be achieved, using a wavelet packet based feature set in conjunction with principal components analysis
Keywords :
electromyography; medical signal processing; principal component analysis; signal classification; time-frequency analysis; wavelet transforms; EMG; computationally efficient; dimensionality reduction; feature set; linear discriminant analysis; multilayer perceptron; myoelectric signal classification; pattern recognition; principal components analysis; short-time FT; time-frequency method; transient bursts; wavelet packets; Biomedical computing; Fourier transforms; Linear discriminant analysis; Pattern classification; Principal component analysis; Signal analysis; Steady-state; Testing; Wavelet analysis; Wavelet packets;
Conference_Titel :
[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-5674-8
DOI :
10.1109/IEMBS.1999.802647
