Singular Values as a Detector of Epileptic Seizures in EEG Signals

• Main Authors: Shahid, Arslan, Kamel , Nidal, Malik, Aamir Saeed
• Format: Conference or Workshop Item
• Published: 2014
• Subjects: Q Science (General); T Technology (General)
• Online Access: http://eprints.utp.edu.my/11418/1/Singular%20values%20as%20a%20detector%20of%20epileptic%20seizures%20in%20EEG%20signals%20-%20Paper.pdf; http://eprints.utp.edu.my/11418/
• Institution: Universiti Teknologi Petronas

This paper introduces a new method based on the Singular Values of EEG signals for the detection of epileptic seizures. Singular Value Decomposition was performed on an EEG signal in epochs of 8 seconds and Singular Values were extracted from each epoch. These singular values were fed into Support Vector Machine (SVM) for a binary classification between epileptic seizure and non- seizure events. Singular Values of EEG signals proved to be a very good feature for the detection of epileptic seizures and gave a classification accuracy of 90%, and an average sensitivity and specificity of 91% and 89%, respectively.