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Mental task classification against the idle state: A preliminary investigation

Dyson, M and Sepulveda, F and Gan, JQ (2008) Mental task classification against the idle state: A preliminary investigation. In: UNSPECIFIED, ? - ?.

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Abstract

The motivation for this study was to obtain candidate electrode sites for use in online self-paced brain-computer interfaces and preliminary classification results for comparison to online tests. Six mental tasks were tested for classification against an idle state. Data representing the idle state was collected in association with active mental task data during each recording session. Features were extracted in two representations, band power and reflection coefficients. A sequential forward floating search algorithm was used to obtain prevailing electrode-feature pairs for each subject-task combination under two conditions: maximising classification accuracy and maximising mean trial accuracy. Methods used to select electrode-feature combinations are found to lead to differing electrode sites in a number of task-feature combinations. An across task prevalence towards electrodes positioned in the left frontal hemisphere is observed when maximising classification accuracy. © 2008 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > R Medicine (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 14 Dec 2012 10:13
Last Modified: 23 Jan 2019 00:15
URI: http://repository.essex.ac.uk/id/eprint/4158

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