학술논문
SVM classification of locomotion modes using surface electromyography for applications in rehabilitation robotics
Document Type
Conference
Author
Source
19th International Symposium in Robot and Human Interactive Communication RO-MAN, 2010 IEEE. :165-170 Sep, 2010
Subject
Language
ISSN
1944-9445
1944-9437
1944-9437
Abstract
The next generation of tools for rehabilitation robotics requires advanced human-robot interfaces able to activate the device as soon as patient's motion intention is raised. This paper investigated the suitability of Support Vector Machine (SVM) classifiers for identification of locomotion intentions from surface electromyography (sEMG) data. A phase-dependent approach, based on foot contact and foot push off events, was employed in order to contextualize muscle activation signals. Good accuracy is demonstrated on experimental data from three healthy subjects. Classification has also been tested for different subsets of EMG features and muscles, aiming to identify a minimal setup required for the control of an EMG-based exoskeleton for rehabilitation purposes.