Paper Info
Title
SVM Evaluation for Brain Computer Interface Systems
Abstract
A Support Vector Machine (SVM) classification method for data acquired by EEG registration for brain/computer interface systems is here proposed. The aim of this work is to evaluate the SVM performances in the recognition of a human mental task, among others. Such methodology could be very useful in important applications for disabled people. A prerequisite has been the developing of a system capable to recognize and classify the following four tasks: thinking to move the right hand, thinking to move the left hand, performing a simple mathematical operation, and thinking to a nursery rhyme. The data set exploited in the training and testing phases has been acquired by means of 61 EEG electrodes and consists of several time series. These time data sets were then transformed into the frequency domain, in order to obtain the power frequency spectrum. In such a way, for every electrode, 128 frequency channels were obtained. Finally, the SVM algorithm was used and evaluated to get the proposed classification.
Year
Venue
Keywords
2010
BIOSIGNALS 2010: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING
Support Vector Machine,Classification,Brain computer interface
Field
DocType
Citations 
Computer science,Brain–computer interface,Rhyme,Artificial intelligence,Electroencephalography,Frequency domain,Computer vision,Operation,Pattern recognition,Support vector machine,Communication channel,Machine learning,Interface (computing)
Conference
0
PageRank 
References 
Authors
0.34
0
9
Name
Order
Citations
PageRank
M. Salerno172.76
G. Costantini211813.88
Daniele Casali3878.21
Giancarlo Orengo443.81
Pietro Cavallo511.09
Giovanni Saggio64116.27
Luigi Bianchi7233.01
Lucia Rita Quitadamo8285.14
Maria Grazia Marciani9344.80