Title of article
Basic Hand Gestures Classification Based on Surface Electromyography
Author/Authors
Palkowski, Aleksander Department of Mechatronics and High Voltage Engineering - Gdansk University of Technology - Ulica G. Narutowicza - Gdansk, Poland , Redlarski, Grzegorz Department of Mechatronics and High Voltage Engineering - Gdansk University of Technology - Ulica G. Narutowicza - Gdansk, Poland
Pages
7
From page
1
To page
7
Abstract
This paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis.
The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are
conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector
Machine classifiers with various kernel functions. The average classification rate of 98.12% has been achieved for the proposed
method.
Keywords
Basic Hand , Electromyography , Classification
Journal title
Computational and Mathematical Methods in Medicine
Serial Year
2016
Full Text URL
Record number
2607128
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