A survey on the automated computer-aided diagnosis of epilepsy seizure

Epilepsy, a life-threatening neurological disorder, necessitates early diagnosis and treatment to mitigate its risks. Neurologists detect epileptic seizures based on manual analysis of electroencephalography (EEG) signals. However, this manual approach is time-consuming, prone to errors due to human fatigue, and challenging for interpreting nonlinear, non-stationary data. This paper presents a comprehensive review of state-of-the-art automated computer-aided diagnosis techniques for early epilepsy seizure detection, focusing on advancements made to overcome the limitations. By synthesising existing research, this survey aims to pinpoint the current state of the field, shed light on its strengths and weaknesses, and identify promising directions for future research.