Khorshidtalab, A. and Salami, Momoh Jimoh Emiyoka (2011) EEG signal classification for real-time brain-computer interface applications: a review. In: ICOM 2011, 17-19 May, 2011, Kuala Lumpur, Malaysia.
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Abstract
Brain-computer interface (BCI) is linking the brain activity to computer, which allows a person to control devices directly with his brain waves and without any use of his muscles. Recent advances in real-time signal processing have made BCI a feasible alternative for controlling robot and for communication as well. Controlling devices using BCI is a crucial aid for people suffering from severe disabilities and more than that, BCIs can replace human to control robots working in dangerous or uncongenial situations. Effective BCIs demand for accurate and real-time EEG signals processing. This paper is to review the current state of research and to compare the performance of different algorithms for real-time classification of BCIbased electroencephalogram signals.
Item Type: | Conference or Workshop Item (Full Paper) |
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Additional Information: | 2470/1820 |
Uncontrolled Keywords: | Brain Computer Interface, EEG, realtime signal processing |
Subjects: | T Technology > T Technology (General) > T175 Industrial research. Research and development |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Engineering > Department of Mechatronics Engineering |
Depositing User: | Prof Momoh-Jimoh Salami |
Date Deposited: | 09 Sep 2011 19:52 |
Last Modified: | 28 Feb 2012 10:48 |
URI: | http://irep.iium.edu.my/id/eprint/1820 |
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