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Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm

Sulaiman, Suriani and Ahmed Yahya, Saba and Mohd Shukor, Nur Sakinah and Ismail , Amelia Ritahani and Zaahirah, Qazi and Yaacob, Hamwira Sakti and Abdul Rahman, Abdul Wahab and Dzulkifli, Mariam Adawiah (2015) Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm. In: Computational intelligence in information systems: proceedings of the Fourth INNS Symposia Series on Computational Intelligence in Information Systems (INNS-CIIS 2014). Advances in Intelligent Systems and Computing (331). Switzerland, Springer International Publishing, pp. 51-60. ISBN 978-3-319-13152-8

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Abstract

We present a preliminary study on the use of a Brain Computer Interface(BCI) device to investigate the feasibility of recognizing patterns of natural language morphemes from EEG signals. This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.

Item Type: Book Chapter
Additional Information: 4615/40882
Uncontrolled Keywords: Clustering,·Artificial Bee Colony algorithm, EEG signals, Natural language morphemes, Morphological priming tasks, BCI.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: Sr. Suriani Sulaiman
Date Deposited: 11 Feb 2016 12:46
Last Modified: 17 Jul 2016 14:41
URI: http://irep.iium.edu.my/id/eprint/49579

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