Title
A fuzzy genetic algorithm for optimal spatial filter selection for P300-based brain computer interfaces
Date Issued
12 October 2018
Access level
metadata only access
Resource Type
conference paper
Author(s)
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
A fuzzy genetic algorithm to optimize spatial filter selection can improve the performance of P300-based brain computer interfaces (BCI); genetic algorithm searches an optimal configuration supported by a fuzzy inference system, it would reduce the error calculated during a 4 fold crossvalidation. The performance is measured through the accuracy and the bit rate, 4 methods based on fuzzy logic and Bayesian linear discriminant analysis are considered for the performance comparison. This proposed method has obtained significant results for healthy persons and post stroke patients, accuracies above 90% and bit rates greater than 8 bits/min for the most of cases evaluated in a P300-based BCI using the Hoffman approach.
Volume
2018-July
Language
English
OCDE Knowledge area
Biotecnología relacionada con la salud
Scopus EID
2-s2.0-85060490116
Source
IEEE International Conference on Fuzzy Systems
Resource of which it is part
IEEE International Conference on Fuzzy Systems
ISSN of the container
10987584
ISBN of the container
978-150906020-7
Sponsor(s)
This work was supported by the Programa Nacional de Innovación para la Competitividad y Productividad, Perú, under the grant 146-PNICP-PIAP-2015.
Sources of information:
Directorio de Producción Científica
Scopus