People nowadays face numerous types of stress in their fast-paced everyday lives, and the majority of the world's population suffers from various neurological disorders. Epilepsy affects approximately 65 million people worldwide and is associated with increased rates of bodily injuries and mortality when not optimally treated. Also educational institutions include some of the students who are likely to have epilepsy, and for fear of exposing them to epileptic seizures in front of their colleagues, we identify and detect the symptoms to anticipate the seizure before it occurs.
Because of the high incidence and harm caused by seizure control failure, it is important to understand the characteristics of epilepsy in order to give an appropriate response for each patient. As a result, epilepsy prediction and early diagnosis are required to give timely preventative measures that allow patients to be free of the detrimental repercussions of epileptic seizures.
Manual analysis of EEG brain signals for epilepsy detection is a time-consuming and difficult procedure that places a tremendous strain on neurologists. As a result, several automatic approaches based on Artificial Intelligence have been developed to aid neurologists in epilepsy detection. The use of artificial intelligence in the diagnosis of epilepsy and predicts epileptic seizures provides an asset to the medical college students and the less experienced doctors in interpreting the EEG and reduces the diagnostics time.
The current study aims to summarize the most recent updates on epilepsy definitions, kinds, diagnosis, seizure and artificial intelligence role in its detection.