Automatic seizure detection system with low complex PSD using TMS320C6713 DSP Online publication date: Thu, 25-Jun-2015
by N. Balasaraswathy; R. Rajavel
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 18, No. 2, 2015
Abstract: Epilepsy is one of the most common neurological disorders characterised by a sudden and recurrent malfunction of the brain, a 'seizure'. An electroencephalogram (EEG) has been an especially valuable clinical tool for the evaluation and treatment of epilepsy. This paper proposes an automatic and feasible real-time seizure detection system for epileptic patients. The seizure detection system use Power Spectral Density (PSD) of EEG sub-bands as features. A low complex PSD estimate, with 30% reduction in computation time compared to traditional Welch PSD estimate is used in this work. Mahalanobis Distance Based Classifier (MDBC) is used in the classification stage to classify between seizures and non-seizures. The EEG dataset used in this work is obtained from Department of Epileptology, University of Bonn, Germany. The proposed automatic seizure detection system is implemented in TI's TMS320C6713 DSP processor and obtained the classification accuracy of higher than 95%.
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