Citation
Deivasigamani, Subbramania Pattar and Chinnaiyan, Senthilpari and Wong, Hin Yong and Rajesh, P. K. and Narmadha, G. (2021) Epileptic EEG signal classifications based on DT-CWT and SVM classifier. Journal of Engineering Research. ISSN 2307-1877 Full text not available from this repository.
Official URL: https://doi.org/10.36909/jer.10523
Abstract
Contamination in human cerebrum causes the mind issue which is as Epilepsy. The contaminated territory in the cerebrum area creates the unpredictable example signals as focal signs and the other sound locales in the mind produce the standard example signals as non-focal sign. Henceforth, the discovery of focal signs from the non-focal signs is a significant for epileptic medical procedure in epilepsy patients. This paper proposes a straightforward and proficient technique for EEG signals orders utilizing SVM classifier. The exhibition of the proposed EEG signals characterization framework is assessed as far as Sensitivity, Specificity, and Accuracy.
Item Type: | Article |
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Uncontrolled Keywords: | Epilepsy, Focal, SVM, Neural networks, Epileptogenic area |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television |
Divisions: | Faculty of Engineering (FOE) |
Depositing User: | Ms Nurul Iqtiani Ahmad |
Date Deposited: | 05 Jul 2022 04:06 |
Last Modified: | 05 Jul 2022 04:06 |
URII: | http://shdl.mmu.edu.my/id/eprint/10105 |
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