Seizure Prediction and Classification Using Affective Technology

Abstract

Epilepsy is a neurological issue that is described by abrupt and irregular seizures. As indicated by the World Health Organisation (WHO), roughly 1% of the total populace are epileptic patients. The abrupt nature of epileptic seizures constitutes a major disabling aspect of the ailment due to the impediments in patients' daily activities. Therefore, a method that can speculate the event of seizures could essentially improve the wellbeing of epileptic patients. Hence, the point of this paper is to build up a model that can anticipate seizures and furthermore characterize them, using a GSR sensor, temperature sensor, and also a pulse rate sensor.