A Review on EEG based Epileptic Seizures Detection using Deep Learning Techniques
Srikanth Cherukuvada, R. Kayalvizhi
Abstract
Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG) modalities have been used in several screening procedures to diagnose epileptic seizures with a high-level accuracy. over the last two decades; significant contributions have been made to automate the procedure of EEG tests to diagnose epilepsy and seizures detection. Because manual seizure detection will take more time for a doctor as well as for technician to put their efforts into recognizing the type of seizure within less time. Deep Learning (DL) helps in automatic feature extraction and classification techniques. In the Medical field, adopting these approaches has resulted in the introduction of these approaches has led to a significant breakthrough in substantial advancements including the identification of epileptic seizures. This paper presents a comprehensive summary of each section in depth and methods used to diagnose epilepsy from a variety of methods. In addition, they are highlighted because they are best suited for applied medicine, hardware execution, and cloud-based tasks. This paper provides a review of novel seizure detection applications and previous studies. The research concludes with some fresh concepts for seizure detection utilizing DL techniques which are becoming increasingly popular.