Biogeography based hybrid scheme for automatic detection of epileptic seizures from EEG signatures

Citation data:

Applied Soft Computing, ISSN: 1568-4946, Vol: 51, Page: 116-129

Publication Year:
2017
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DOI:
10.1016/j.asoc.2016.12.009
Author(s):
Rohtash Dhiman, J.S. Saini, null Priyanka
Publisher(s):
Elsevier BV
Tags:
Computer Science
article description
Biogeography Based Optimization (BBO) algorithm is one of the nature-inspired optimization methods, based on the study of geographical distribution of species on earth. The present research work is based upon decomposition of human electroencephalograms (EEG) signal by Wavelet Packet Transform, computation of a complete feature set using statistical and non-statistical properties followed by optimal selection of features by BBO; the optimality criterion being classification rate. The stopping criterion for BBO is set to 100% correct classification rate. The proposed algorithm is novel in terms of TWSVM computing the Habitat Suitability Index (HSI) values for BBO, perfect classification rate, low computation time, and feature selection mechanism. The proposed scheme outperforms several previous results reported in literature in that it gives a feature subset which gives 100% classification accuracy for different classification instances.

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