Karya
Judul/Title Comparison of empirical mode decomposition and coarse-grained procedure for detecting pre-ictal and ictal condition in electroencephalography signal
Penulis/Author INUNG WIJAYANTO (1); Dr. Ir. Rudy Hartanto, M.T., IPM. (2); Prof. Ir. Hanung Adi Nugroho, S.T., M.Eng., Ph.D., IPM., SMIEEE. (3)
Tanggal/Date 2020
Kata Kunci/Keyword
Abstrak/Abstract This study evaluates the use of multiscale signal analysis to detect and predict seizures by finding the ictal and pre-ictal condition in electroencephalography (EEG) recordings. There are three processing stages in this study. The first is to decompose EEG signals by using empirical mode decomposition (EMD) and a coarse-grained (CG) procedure to obtain signal information in multiple scales. The second is extracting the features by calculating the fractal dimension of the decomposed signals. Eventually, k-NN, Random Forest, and support vector machine (SVM) classifiers are used to classify ictal and pre-ictal conditions. We evaluate the system using a public dataset from Bonn University. The combination of EMD with five IMFs, FD, and SVM is used for seizure detection (normal vs. ictal) and the three-class problem (normal vs. pre-ictal vs. ictal). The accuracy for seizure detection is 100%. For the three-class problem, we achieved a highest accuracy of 99.7%, and sensitivity and specificity of 99.7% and 99.9%, respectively. The combination of CG, FD, and SVM is proposed to predict a seizure (normal vs. pre-ictal) and achieves a maximum classification accuracy from 99.3% to 100%. These results indicate that the use of EMD with five IMFs is suitable for detecting seizures, while CG is suitable for predicting seizures in EEG signals.
Rumpun Ilmu Teknik Elektro
Bahasa Asli/Original Language English
Level Internasional
Status
Dokumen Karya
No Judul Tipe Dokumen Aksi
1Comparison of empirical mode decomposition and coarse-grained procedure for detecting pre-ictal and ictal condition in electroencephalography signal.pdf[PAK] Full Dokumen
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406 Bukti Korespondensi IMU_Comparison of Empirical Mode_compressed.pdf[PAK] Bukti Korespondensi Penulis
512 Suket Publikasi PAK_Comparison of empirical mode.pdfDokumen Pendukung Karya Ilmiah (Hibah, Publikasi, Penelitian, Pengabdian)