Implementation of genetic algorithms to feature selection for the use of brain-computer interface

Marcin Kołodziej , Andrzej Majkowski , Remigiusz Rak

Abstract

The main goal of the article is to apply genetic algorithms to feature selection for the use of brain-computer interface (BCI). FFT coefficients of EEG signal were used as features. The best features for a BCI system depends on the person who uses the system as well as on the mental state of the person. Therefore, it is very important to apply efficient methods of feature selection. The genetic algorithm proposed by authors enables to choose the most representative features and electrodes.

Author Marcin Kołodziej (FoEE / ITEEMIS)
Marcin Kołodziej,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
, Andrzej Majkowski (FoEE / ITEEMIS)
Andrzej Majkowski,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
, Remigiusz Rak (FoEE / ITEEMIS)
Remigiusz Rak,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
Journal seriesPrzegląd Elektrotechniczny, ISSN 0033-2097, (A 15 pkt)
Issue year2011
Vol87
Pages71-73
Publication size in sheets0.3
ASJC Classification2208 Electrical and Electronic Engineering
Languageen angielski
Score (nominal)15
Score sourcejournalList
Publication indicators Scopus Citations = 7; WoS Citations = 3; GS Citations = 8.0; Scopus SNIP (Source Normalised Impact per Paper): 2011 = 0.531; WoS Impact Factor: 2011 = 0.244 (2)
Citation count*8 (2020-01-25)
Cite
Share Share

Get link to the record


* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
Back
Confirmation
Are you sure?