Multiclass epileptic seizure detection from Electroencephalogram (EEG) signals is difficult because seizure-related patterns are nonstationary, patient-dependent, and distributed across redundant EEG channels. This study develops a detection framework that combines Coefficient of Variation (CV)-based channel selection,...
A. Eviyanti, Ahmad Saikhu, Chastine Fatichah· Engineering, Technology &...· 0 citations
The results showed that the combination of FFT and SVM is effective for detecting epilepsy using EEG signals, indicating that the combination of FFT and SVM is effective for detecting epilepsy using EEG signals.
H. Hindarto, A. Eviyanti, A. Ahfas et al.· Jurnal Elektronika dan Telek...· 0 citations
Findings underscore the potential of higher-order statistical descriptors, particularly kurtosis, for EEG-based epileptic seizure detection under a controlled benchmark setting and underscore the potential of classical machine learning classifiers to distinguish normal and epileptic EEG signals.
H. Hindarto, Ade Eviyanti, A. Ahfas et al.· International journal of ele...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.