Evolving Approaches in Epilepsy Management: Harnessing Internet of Things and Deep Learning

For efficient treatment and management of epilepsy, which is characterized by repeated, abrupt, and excessive electrical discharges in the brain, early detection and exact diagnosis are required. The use of the Internet of Things (IoT) and deep learning algorithms for identifying and monitoring epileptic seizures has increased dramatically in recent years. IoT devices, which collect data from various sources like video cameras, wearable sensors, and electroencephalogram (EEG) equipment, collaborate with deep learning algorithms to deliver real-time insights about a patient's status. This in-depth examination examines the most recent breakthroughs in IoT and deep learning technology for identifying and tracking epileptic episodes. The review delves into the field's existing issues and potential future directions. This review begins by discussing the intricacies of diagnosing and monitoring epilepsy and subsequently delving into IoT and deep learning techniques for seizure detection, classification, and prediction. Finally, we shed light on intriguing research avenues and discuss the barriers and prospects in this dynamic domain.