Title :
Multi-objective evolutionary methods for channel selection in Brain-Computer Interfaces: Some preliminary experimental results
Author :
Hasan, Bashar Awwad Shiekh ; Gan, John Q. ; Zhang, Qingfu
Author_Institution :
Sch. of Comput. Sci. & Electron. Eng., Univ. of Eessex, Colchester, UK
Abstract :
This paper presents a comparative study among three evolutionary and search based methods to solve the problem of channel selection for Brain-Computer Interface (BCI) systems. Multi-Objective Particle Swarm Optimization (MOPSO) method is compared to Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) and single objective Sequential Floating Forward Search (SFFS) method. The methods are tested on the first data set for BCI-Competition IV. The results show the usefulness of the multi-objective evolutionary methods in achieving accuracy results similar to the extensive search method with fewer channels and less computational time.
Keywords :
brain-computer interfaces; evolutionary computation; particle swarm optimisation; brain-computer interfaces; channel selection; multiobjective evolutionary methods; multiobjective particle swarm optimization; sequential floating forward search; Accuracy; Electroencephalography; Feature extraction; Optimization; Particle swarm optimization; Search problems;
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
DOI :
10.1109/CEC.2010.5586411
