A Deep Learning and Raspberry PI Investigation for Epilepsy Seizure Detection

A common neurological condition that affects over 65 million people globally is epilepsy. Most of the time, patients with this ailment do not respond to medicine or surgery. However, therapeutic intervention that anticipates a seizure before it happens can help avoid it. Research indicates that the preictal state—a state of abnormal brain activity—begins just prior to the actual seizure. It is still challenging to accurately and very sensitively forecast the preictal condition of a seizure, despite multiple experiments. The proposed work uses deep learning technology to develop an automated seizure prediction system. The EEG data is preprocessed and some pertinent characteristics are extracted before being classified using a deep learning system. Furthermore, a precise seizure detection system constructed around a Raspberry Pi is developed to anticipate the start of seizures.