Paper Info
Title
Basic Hand Gestures Classification Based on Surface Electromyography.
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.
Year
DOI
Venue
2016
10.1155/2016/6481282
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
Field
DocType
Volume
Structured support vector machine,Radial basis function kernel,Computer science,Artificial intelligence,Computer vision,Pattern recognition,Support vector machine,Cuckoo search,Relevance vector machine,Kernel method,Linear classifier,Machine learning,Kernel (statistics)
Journal
2016
ISSN
Citations 
PageRank 
1748-670X
0
0.34
References 
Authors
8
2
Name
Order
Citations
PageRank
Aleksander Palkowski121.05
Grzegorz Redlarski2133.34