Universiti Teknologi Malaysia Institutional Repository

Feature extraction of EEG signals and classification using FCM

Mohd. Aris, Siti Armiza and Taib, Mohd. Nasir and Lias, Sahrim and Sulaiman, Norizam (2011) Feature extraction of EEG signals and classification using FCM. In: UKSim 13th International Conference on Modelling and Simulation, UKSim 2011, 30 March 2011 - 1 April 2011, Cambridge, UK.

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Official URL: http://dx.doi.org/10.1109/UKSIM.2011.20


EEG data were collected between two conditions, relax wakefulness (close-eyes) and non-relax (IQ test). Data segmentation and linear regression model is used to extract the EEG features and to obtain the slope and the mean relative power from 43 participants. All of the data were then normalized and classified using Fuzzy C-Means (FCM) clustering. Results shown that there are different of activities exist in the EEG which proved that the feature extraction using linear regression model manage to discern between two different brain behaviors.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:EEG, FCM, linear regression technique
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Razak School of Engineering and Advanced Technology
ID Code:29700
Deposited By: Yanti Mohd Shah
Deposited On:21 Mar 2013 08:44
Last Modified:31 Jan 2022 08:41

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