Electroencephalogram time series classification: Applications in epilepsy

Electroencephalogram time series classification: Applications in epilepsy

0.00 Avg rating0 Votes
Article ID: iaor20072437
Country: Netherlands
Volume: 148
Issue: 1
Start Page Number: 227
End Page Number: 250
Publication Date: Nov 2006
Journal: Annals of Operations Research
Authors: , ,
Abstract:

Epilepsy is among the most common brain disorders. Approximately 25–30% of epilepsy patients remain unresponsive to anti-epileptic drug treatment, which is the standard therapy for epilepsy. In this study, we apply optimization-based data mining techniques to classify the brain's normal and epilepsy activity using intracranial electroencephalogram (EEG), which is a tool for evaluating the physiological state of the brain. A statistical cross validation and support vector machines were implemented to classify the brain's normal and abnormal activities. The results of this study indicate that it may be possible to design and develop efficient seizure warning algorithms for diagnostic and therapeutic purposes.

Reviews

Required fields are marked *. Your email address will not be published.