Title :
Epileptic seizure detection using the singular values of EEG signals
Author :
Shahid, A. ; Kamel, N. ; Malik, A.S. ; Jatoi, M.A.
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. Teknol. PETRONAS, Tronoh, Malaysia
Abstract :
A new technique based on Singular Value Decomposition (SVD) for the detection of epileptic seizures is proposed. The SVD is applied sequentially on a sliding window of one second width of EEG data and the r singular values are obtained and used to indicate sudden changes in the signals. EEG recordings of 4-paediatric patients with 20 seizures are used to validate the proposed algorithm and the preliminary results indicates good level of sensitivity by the singular values to the changes in the EEG signals due to epileptic seizure. This sensitivity can be used to develop more reliable seizure detector than the existing techniques.
Keywords :
electroencephalography; medical disorders; medical signal detection; medical signal processing; paediatrics; singular value decomposition; EEG signals; SVD; epileptic seizure detection; paediatric patients; r singular values; singular value decomposition; sliding window; Delays; Electroencephalography; Epilepsy; Matrix decomposition; Neurophysiology; Singular value decomposition; Vectors; Electroencephalography (EEG); Epileptic Seizures; Singular Value Decomposition (SVD);
Conference_Titel :
Complex Medical Engineering (CME), 2013 ICME International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2970-5
DOI :
10.1109/ICCME.2013.6548330