Epileptic seizure detection using EEG
Date of Issue2017
School of Computer Science and Engineering
Seizures occur at unpredictable times and is usually without warnings. Seizures can be dangerous and potentially life-threatening if left without assistance and treatments. This poses a challenge for medical personnel as immediate assistance is required should a patient suffers from a seizure. This project aims to develop an algorithm to allow detection of epileptic seizures of a patient through the use of electroencephalogram (EEG) signal. This algorithm will determine if the input EEG data is epileptic or not. This algorithm consists of two processes: feature extraction and classification. For this purpose, power spectral density is used to extract features of the EEG signals. Classification is done by using a Support Vector Machine (SVM). With a working algorithm in detection of seizure, future implementation of such detection methods could be used in real-life situations where an alarm could be triggered to notify the medical personnel of a seizure of patient so that immediate response could be activated.
DRNTU::Engineering::Computer science and engineering
Final Year Project (FYP)
Nanyang Technological University