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Detecting Different Tasks Using EEG-Source-Temporal Features

Shams, Wafa Khazal and Abdul Rahman, Abdul Wahab and Qidwai, Uvais A. (2012) Detecting Different Tasks Using EEG-Source-Temporal Features. In: Proceedings of Neural Information Processing - 19th International Conference, ICONIP 2012, November 12-15, 2012, Doha, Qata.

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Abstract

This study proposes a new type of features extracted from Electroencephalography (EEG) signals to distinguish between different tasks. EEG signals are collected from six children aged between two to six years old during opened and closed eyes tasks. For each time-sample, Time Difference of Arrival (TDOA) is applied to EEG time series to compute the source-temporalfeatures that are assigned to x, y and z coordinates. The features are classified using neural network. The results show an accuracy of around 100% for eyes open task and around (83%-95%) for eyes closed tasks for the same subject. This study highlights the use of new types of features (source-temporal features), to characterize the brain functional behavior.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 6145/28931 © Springer-Verlag Berlin Heidelberg 2012 DOI: 10.1007/978-3-642-34478-7_47
Uncontrolled Keywords: EEG signals, Classification, TDOA approach, Source-Temporal features.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: Prof Abdul Wahab Abdul Rahman
Date Deposited: 15 Feb 2013 15:26
Last Modified: 15 Feb 2013 15:27
URI: http://irep.iium.edu.my/id/eprint/28931

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