Basic Hand Gestures Classification Based on Surface Electromyography
Joint Authors
Palkowski, Aleksander
Redlarski, Grzegorz
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-05-19
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Palkowski, Aleksander& Redlarski, Grzegorz. 2016. Basic Hand Gestures Classification Based on Surface Electromyography. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1100170
Modern Language Association (MLA)
Palkowski, Aleksander& Redlarski, Grzegorz. Basic Hand Gestures Classification Based on Surface Electromyography. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1100170
American Medical Association (AMA)
Palkowski, Aleksander& Redlarski, Grzegorz. Basic Hand Gestures Classification Based on Surface Electromyography. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1100170
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1100170
