Analysing epileptic EEGs with a visibility graph algorithm

Zhu, Guohun and Li, Yan and Wen, Peng (Paul) (2012) Analysing epileptic EEGs with a visibility graph algorithm. In: 5th International Conference on Biomedical Engineering and Informatics (BMEI 2012), 16-18 Oct 2012, Chongqing, China.

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Abstract

This paper analyzes the human epileptic lectroencephalogram (EEG) based on a visibility graph algorithm. A single-channel EEG is mapped into a visibility graph (VG). Then its mean degree and degree distribution on the VG are extracted. It is shown that the mean degree on a VG from an epileptic subject is larger than that on a healthy subject based on the VG. The number of nodes having five degree on a VG from a healthy subject is significantly different from the number of nodes having the same degree on the VG from an epileptic subject. The mean degree and the number of nodes with five and eight degrees are used to discriminate the healthy EEGs, seizure EEGs and inter-ictal EEGs. Experimental results demonstrate that the visibility graph algorithm has a high classification accuracy to identify these three types of EEGs.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2012 IEEE. Permanent restricted access to published version due to publisher copyright policy.
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 09 Apr 2013 23:49
Last Modified: 20 Feb 2015 05:49
Uncontrolled Keywords: seizure; visibility graph; degree distribution; EEG; nonlinear discriminant analysis
Fields of Research : 09 Engineering > 0903 Biomedical Engineering > 090399 Biomedical Engineering not elsewhere classified
08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080201 Analysis of Algorithms and Complexity
01 Mathematical Sciences > 0101 Pure Mathematics > 010104 Combinatorics and Discrete Mathematics (excl. Physical Combinatorics)
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970101 Expanding Knowledge in the Mathematical Sciences
Identification Number or DOI: 10.1109/BMEI.2012.6513212
URI: http://eprints.usq.edu.au/id/eprint/22243

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