An automatic alarm system for detecting epileptic
seizure onsets could be of great assistance to patients and
medical staff. A novel approach is proposed using the Matching Pursuit algorithm as a feature extractor combined with the Support Vector Machine (SVM) as a classifier for this purpose. The combination of Matching Pursuit and SVM for automatic seizure detection has never been tested before, making this a pilot study. Data from red different patients with 6 to 49 seizures are used to test our model. Three patients are recorded with scalp electroencephalography (sEEG) and three with intracranial electroencephalography (iEEG). A sensitivity of 78-100% and a detection latency of 5-18s has been achieved, while holding the false detection at 0.16-5.31/h. Our results
show the potential of Matching Pursuit as a feature xtractor for detection of epileptic seizures.
|Conference||32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society|
|Period||31/08/2010 → 04/09/2010|
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