Combination of Coarse-Grained Procedure and Fractal Dimension for Epileptic EEG Classification
Epilepsy, cured by some offered treatments such as medication, surgery, and dietary plan, is a neurological brain disorder due to disturbed nerve cell activity characterized by repeated seizures. Electroencephalographic (EEG) signal processing detects and classifies these seizures as one of the ab...
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| Format: | EJournal Article |
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IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.,
2021-10-31.
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| LEADER | 02374 am a22003133u 4500 | ||
|---|---|---|---|
| 001 | IJCSS_69845 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Rahmawati, Dien |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Rizal, Achmad |e author |
| 700 | 1 | 0 | |a Silalahi, Desri Kristina |e author |
| 245 | 0 | 0 | |a Combination of Coarse-Grained Procedure and Fractal Dimension for Epileptic EEG Classification |
| 260 | |b IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia., |c 2021-10-31. | ||
| 500 | |a https://jurnal.ugm.ac.id/ijccs/article/view/69845 | ||
| 520 | |a Epilepsy, cured by some offered treatments such as medication, surgery, and dietary plan, is a neurological brain disorder due to disturbed nerve cell activity characterized by repeated seizures. Electroencephalographic (EEG) signal processing detects and classifies these seizures as one of the abnormality types in the brain within temporal and spectral content. The proposed method in this paper employed a combination of two feature extractions, namely coarse-grained and fractal dimension, a challenge to obtain a highly accurate procedure to evaluate and predict the epileptic EEG signal of normal, interictal, and seizure classes. The result of classification accuracy using variance fractal dimension (VFD) and quadratic support machine vector (SVM) with a number scale of 10 is 99% as the highest one, excellent performance of the predictive model in terms of the error rate. In addition, a higher scale number does not determine a higher accuracy in this study. | ||
| 540 | |a Copyright (c) 2021 IJCCS (Indonesian Journal of Computing and Cybernetics Systems) | ||
| 540 | |a http://creativecommons.org/licenses/by-sa/4.0 | ||
| 546 | |a eng | ||
| 690 | |a Computer Science; Machine Learning | ||
| 690 | |a epilepsy; EEG classification; coarse-grained; fractal dimension; support vector machine | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 15, No 4 (2021): October; 427-438 | |
| 786 | 0 | |n 2460-7258 | |
| 786 | 0 | |n 1978-1520 | |
| 787 | 0 | |n https://jurnal.ugm.ac.id/ijccs/article/view/69845/32412 | |
| 856 | 4 | 1 | |u https://jurnal.ugm.ac.id/ijccs/article/view/69845 |z Get Fulltext |
| 856 | 4 | 1 | |u https://jurnal.ugm.ac.id/ijccs/article/view/69845/32412 |z Get Fulltext |