PREDICTION MODEL DESIGN AND DEVELOPMENT FOR SEIZURE DETECTION
Research Scholar Maharishi University of Information Technology Lucknow Email:
Prof. Chitranjan Gaur
Professor Maharishi University of information Technology Lucknow
Because of advancements in computing and processing capacity, EEG signal analysis has become more reliable and accurate in recent years. It has progressed into an important diagnostic tool for neurological problems, with applications in both the medical and physiological fields. The overlapping manifestations of normal and aberrant signals make epileptic seizure diagnosis and prediction challenging even for the most seasoned neurologist. Consequently, it would be ideal to have a fully automated Computer Aided Diagnostic (CAD) system that can use EEG signals to categorise the severity of epileptic seizures. This motivates the current study’s objective of developing a computerised prediction model for interpreting EEG data and making a diagnosis of epilepsy. This chapter presents a computer-aided design (CAD) system that may identify abnormalities in the brain before and during the start of seizures.
Keywords: Prediction Model, Seizure Activity etc