 |
| Research article summary (published 30 Aug 2002): |
Feature selection for the classification of movements from single movement-related potentials.
Full Abstract
Classification of movement-related potentials recorded from the scalp to their corresponding limb is a crucial task in brain-computer interfaces based on such potentials. Many features can be extracted from raw electroencephalographic signals to be used for classification, but the utilization of irrelevant or superfluous features is detrimental to the performance of classification algorithms. It is, therefore, necessary to select a small number of relevant features for the classification task. This paper demonstrates the use of two feature selection methods to choose a small number (10-20) of relevant features from a bank containing upward of 1000 features. One method is based on information theory and the other on the use of genetic algorithms. We show that the former is poorly suited for the aforementioned classification task and discuss the probable reasons for this. However, using a genetic algorithm on data recorded from five subjects we demonstrate that it is possible to differentiate between the movements of two limbs with a classification accuracy of 87% using as little as 10 features without subject training. With the addition of a simple coding scheme, this method can be applied to multiple limb classification and a 63% classification accuracy rate can be reached when attempting to distinguish between three limbs.
Learn Faster Today Improve your study skills
Author information
Author/s: Yom-Tov, Elad (E); Inbar, Gideon F (GF);
Affiliation: Technion-Israel Institute of Technology, Haifa 32000, Israel. elad(-atsign-)ieee.org
Journal and publication information
Publication Type: Clinical Trial; Comparative Study; Journal Article
Journal: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society (IEEE Trans Neural Syst Rehabil Eng), published in United States. (Language: eng)
Reference: 2002-Sep; vol 10 (issue 3) : pp 170-7
Dates: Created 2002/12/30; Completed 2003/04/23; Revised 2006/11/15;
PMID: 12503782, status: MEDLINE (last retrieval date: 11/6/2008)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
External Links for this article (including full text providers, if available):
Click Electronic Full-text Provider Links to see options for finding the electronic full text links to this article. Note there may be a subscription or fee required for access to the full text. See our FAQ for information on finding FREE full text articles.
This article may also be located in paper journal collections available in many libraries. Use the Journal and Publication Information above to find the full article.
MeSH headings (categories)
This article was linked to the MESH Headings shown below.
|
|
Related articles
This article has not been indexed for related articles as yet, however you can still use the live related article search links below.
See a large map of 100+ related articles.