Hasan, BAS and Gan, JQ (2009) Multi-objective particle swarm optimization for channel selection in brain-computer interfaces. In: Proceedings of the UK Workshop on Computational Intelligence (UKCI 2009), ? - ?, Nottingham.
|
Text
bashar_UKCI09.pdf Download (900kB) | Preview |
Abstract
This paper presents a novel application of a multi-objective particle swarm optimization (MOPSO) method to solve the problem of effective channel selection for Brain-Computer Interface (BCI) systems. The proposed method is tested on 6 subjects and compared to another search based method, Sequential Floating Forward Search (SFFS). The results demonstrate the effectiveness of MOPSO in selecting a fewer number of channels with insignificant sacrifice in accuracy, which is very important to build robust online BCI systems.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Published proceedings: _not provided_ |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
| Depositing User: | Users 161 not found. |
| Date Deposited: | 01 Jul 2013 13:05 |
| Last Modified: | 17 Aug 2017 18:07 |
| URI: | http://repository.essex.ac.uk/id/eprint/4148 |
Actions (login required)
 |
View Item |