Classification of Epileptic and Healthy Individual Eeg Signals Using Neural Networks

Aykat, SukruSenan, SibelEnsari, TolgaAykat, Şükrü2025-02-152025-02-1520209781728175652https://doi.org/10.1109/ubmk50275.2020.9219474https://hdl.handle.net/20.500.12514/6009AYKAT, Sukru/0000-0003-1738-3696Electroencephalogram (EEG) are signals used for the analysis of the electrical and functional activity of the brain. These signals are commonly used to detect epileptic seizures. The aim of this study is to classify healthy and epileptic individual EEG signals using artificial neural networks (ANN). For this purpose, the open data source of the University of Bonn was used. The success rates of the classification results obtained with the designed ANN model show the effectiveness of this ANN structure in the application under consideration.tr10.1109/ubmk50275.2020.9219474info:eu-repo/semantics/closedAccessEeg SignalArtificial Neural NetworksWavelet TransformClassification of Epileptic and Healthy Individual Eeg Signals Using Neural NetworksConference Object4751N/AN/AWOS:0006290555000092-s2.0-850957099220