Epileptic seizure detection in EEGs signals using a fast weighted horizontal visibility algorithm

Zhu, Guohun and Li, Yan and Wen, Peng (Paul) (2014) Epileptic seizure detection in EEGs signals using a fast weighted horizontal visibility algorithm. Computer Methods and Programs in Biomedicine, 115 (2). pp. 64-75. ISSN 0169-2607


This paper proposes a fast weighted horizontal visibility graph constructing algorithm (FWHVA) to identify seizure from EEG signals. The performance of the FWHVA is evaluated by comparing with Fast Fourier Transform (FFT) and sample entropy (SampEn) method. Two noise-robustness graph features based on the FWHVA, mean degree and mean strength, are investigated using two chaos signals and five groups of EEG signals. Experimental results show that feature extraction using the FWHVA is faster than that of SampEn and FFT. And mean strength feature associated with ictal EEG is significant higher than that of healthy and inter-ictal EEGs. In addition, an 100% classification accuracy for identifying seizure from healthy shows that the features based on the FWHVA are more promising than the frequency features based on FFT and entropy indices based on SampEn for time series classification.

Statistics for USQ ePrint 25346
Statistics for this ePrint Item
Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2014 Elsevier Ireland Ltd. Permanent restricted access to published version due to publisher copyright policy.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 21 Apr 2015 04:00
Last Modified: 04 Jul 2016 05:14
Uncontrolled Keywords: epilepsy; computational complexity; weighted horizontal visibility graph; mean degree; mean strength
Fields of Research : 09 Engineering > 0903 Biomedical Engineering > 090399 Biomedical Engineering not elsewhere classified
01 Mathematical Sciences > 0102 Applied Mathematics > 010202 Biological Mathematics
08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080201 Analysis of Algorithms and Complexity
Socio-Economic Objective: C Society > 92 Health > 9202 Health and Support Services > 920203 Diagnostic Methods
Identification Number or DOI: 10.1016/j.cmpb.2014.04.001
URI: http://eprints.usq.edu.au/id/eprint/25346

Actions (login required)

View Item Archive Repository Staff Only