Publication Type : Book Chapter
Publisher : Artificial Intelligence Techniques for Advanced Computing Applications
Source : Artificial Intelligence Techniques for Advanced Computing Applications, Springer Singapore, Singapore (2021)
Url : https://link.springer.com/chapter/10.1007/978-981-15-5329-5_10
ISBN : 9789811553295
Campus : Bengaluru
School : School of Engineering
Department : Electronics and Communication
Year : 2021
Abstract : Epilepsy is one among the most common brain disorders where research is still going on to find the best solution towards its treatment. The phenomenon of occurrence of recurrent seizures is known as epilepsy. This condition is unpredictable, and the patient can suffer at any moment of time. This may lead to permanent nervous system breakdown or death. Several researchers have focused on predicting seizure activity from electrocardiogram (ECG) signals and electroencephalogram (EEG). This paper focuses on the different methods and models used to predict seizure from EEG signals to lessen the burden on patients because of the unpredictable nature of seizures. Furthermore, it also gives insights about deep learning approaches used to predict epilepsy using the EEG signals.
Cite this Research Publication : S. Bulusu, Prasad, R. Sai Surya, Telluri, P., and Dr. N. Neelima, “Methods for Epileptic Seizure Prediction Using EEG Signals: A Survey”, in Artificial Intelligence Techniques for Advanced Computing Applications, J. D. Hemanth, Vadivu, G., Sangeetha, M., and Balas, V. Emilia, Eds. Singapore: Springer Singapore, 2021.