Authors:
Ignacio Rodriguez Carreño
1
and
Marko Vuskovic
2
Affiliations:
1
Public University of Navarre, Spain
;
2
San Diego State University, United States
Keyword(s):
Pattern recognition, EMG, feature extraction, wavelets, moments, support vector machines.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
A new feature extraction method based on five moments applied to three wavelet transform sequences has been proposed and used in classification of prehensile surface EMG patterns. The new method has essentially extended the Englehart's discrete wavelet transform and wavelet packet transform by introducing more efficient feature reduction method that also offered better generalization. The approaches were empirically evaluated on the same set of signals recorded from two real subjects, and by using the same classifier, which was the Vapnik's support vector machine.