EEG-based attention recognition

Li, X. and Hu, B. and Dong, Q. and Campbell, W.M. and Moore, P. and Peng, H. (2011) EEG-based attention recognition. In: 2011 6th International Conference on Pervasive Computing and Applications, ICPCA 2011, 26 October 2011 through 28 October 2011, Port Elizabeth; South Africa.

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Abstract

Attention recognition (AR) is an essential component in many applications, however the focus of current research into AR is on face detection, eye center localization and eye center tracking techniques. This paper describes a research project conducted to investigate the use of electroencephalography (EEG) signals to extend the current approaches and enrich AR. EEG processing and classification algorithms are applied to EEG data to identify a group of features that can be used to effectively implement AR. The experimental results reported in this paper are encouraging with correct classification rates achieved being: 51.9% where attention is divided into 5 classes and 63.9% where attention id divided into 3 classes. The distribution of the training tuples and testing tuples is discussed along with their impact on the reported results. The paper concludes with an overview of outstanding issues and consideration of projected future research. © 2011 IEEE.

Item Type:	Conference or Workshop Item (Paper)
Identification Number:	10.1109/ICPCA.2011.6106504
Dates:	Date Event 2011 Published
Uncontrolled Keywords:	Attention Recognition, Classification Algrithm, EEG, Attention Recognition, Classification rates, EEG processing and classifications, Essential component, Tracking techniques, Electrophysiology, Face recognition, Research, Ubiquitous computing, Electroencephalography
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions:	Faculty of Computing, Engineering and the Built Environment Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User:	Hussen Farooq
Date Deposited:	20 Jul 2016 09:46
Last Modified:	22 Mar 2023 12:02
URI:	https://www.open-access.bcu.ac.uk/id/eprint/2051

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