EEG CLASSIFICATION FOR EPILEPSY BASED ON WAVELET PACKET DECOMPOSITION AND RANDOM FOREST
EEG (electroencephalogram) can detect epileptic seizures by neurophysiologists in clinical practice with visually scan long recordings. Epilepsy seizure is a condition of brain disorder with chronic noncommunicable that affects people of all ages. The challenge of study is how to develop a method fo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Universitas Indonesia
2018-02-01
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| Series: | Jurnal Ilmu Komputer dan Informasi |
| Subjects: | |
| Online Access: | http://jiki.cs.ui.ac.id/index.php/jiki/article/view/549 |
| _version_ | 1818022915288858624 |
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| author | Yuna Sugianela Qonita Luthfia Sutino Darlis Herumurti |
| author_facet | Yuna Sugianela Qonita Luthfia Sutino Darlis Herumurti |
| author_sort | Yuna Sugianela |
| collection | DOAJ |
| description | EEG (electroencephalogram) can detect epileptic seizures by neurophysiologists in clinical practice with visually scan long recordings. Epilepsy seizure is a condition of brain disorder with chronic noncommunicable that affects people of all ages. The challenge of study is how to develop a method for signal processing that extract the subtle information of EEG and use it for automating the detection of epileptic with high accuration, so we can use it for monitoring and treatment the epileptic patient. In this study we developed a method to classify the EEG signal based on Wavelet Packet Decomposition that decompose the EEG signal and Random Forest for seizure detetion. The result of study shows that Random Forest classification has the best performance than KNN, ANN, and SVM. The best combination of statisctical features is standard deviation, maximum and minimum value, and bandpower. WPD is has best decomposition in 5th level. |
| first_indexed | 2024-12-10T03:36:00Z |
| format | Article |
| id | doaj.art-6de59e7e86604bbdb719ba2aa2613b3c |
| institution | Directory Open Access Journal |
| issn | 2088-7051 2502-9274 |
| language | English |
| last_indexed | 2024-12-10T03:36:00Z |
| publishDate | 2018-02-01 |
| publisher | Universitas Indonesia |
| record_format | Article |
| series | Jurnal Ilmu Komputer dan Informasi |
| spelling | doaj.art-6de59e7e86604bbdb719ba2aa2613b3c2022-12-22T02:03:41ZengUniversitas IndonesiaJurnal Ilmu Komputer dan Informasi2088-70512502-92742018-02-01111273310.21609/jiki.v11i1.549239EEG CLASSIFICATION FOR EPILEPSY BASED ON WAVELET PACKET DECOMPOSITION AND RANDOM FORESTYuna Sugianela0Qonita Luthfia SutinoDarlis HerumurtiSepuluh Nopember Institute of TechnologyEEG (electroencephalogram) can detect epileptic seizures by neurophysiologists in clinical practice with visually scan long recordings. Epilepsy seizure is a condition of brain disorder with chronic noncommunicable that affects people of all ages. The challenge of study is how to develop a method for signal processing that extract the subtle information of EEG and use it for automating the detection of epileptic with high accuration, so we can use it for monitoring and treatment the epileptic patient. In this study we developed a method to classify the EEG signal based on Wavelet Packet Decomposition that decompose the EEG signal and Random Forest for seizure detetion. The result of study shows that Random Forest classification has the best performance than KNN, ANN, and SVM. The best combination of statisctical features is standard deviation, maximum and minimum value, and bandpower. WPD is has best decomposition in 5th level.http://jiki.cs.ui.ac.id/index.php/jiki/article/view/549EEG, epilepsy, seizure, wavelet, random forest |
| spellingShingle | Yuna Sugianela Qonita Luthfia Sutino Darlis Herumurti EEG CLASSIFICATION FOR EPILEPSY BASED ON WAVELET PACKET DECOMPOSITION AND RANDOM FOREST Jurnal Ilmu Komputer dan Informasi EEG, epilepsy, seizure, wavelet, random forest |
| title | EEG CLASSIFICATION FOR EPILEPSY BASED ON WAVELET PACKET DECOMPOSITION AND RANDOM FOREST |
| title_full | EEG CLASSIFICATION FOR EPILEPSY BASED ON WAVELET PACKET DECOMPOSITION AND RANDOM FOREST |
| title_fullStr | EEG CLASSIFICATION FOR EPILEPSY BASED ON WAVELET PACKET DECOMPOSITION AND RANDOM FOREST |
| title_full_unstemmed | EEG CLASSIFICATION FOR EPILEPSY BASED ON WAVELET PACKET DECOMPOSITION AND RANDOM FOREST |
| title_short | EEG CLASSIFICATION FOR EPILEPSY BASED ON WAVELET PACKET DECOMPOSITION AND RANDOM FOREST |
| title_sort | eeg classification for epilepsy based on wavelet packet decomposition and random forest |
| topic | EEG, epilepsy, seizure, wavelet, random forest |
| url | http://jiki.cs.ui.ac.id/index.php/jiki/article/view/549 |
| work_keys_str_mv | AT yunasugianela eegclassificationforepilepsybasedonwaveletpacketdecompositionandrandomforest AT qonitaluthfiasutino eegclassificationforepilepsybasedonwaveletpacketdecompositionandrandomforest AT darlisherumurti eegclassificationforepilepsybasedonwaveletpacketdecompositionandrandomforest |