Automatic epileptic seizure onset detection using matching pursuit: a case study

Thomas L Sorensen, Ulrich L Olsen, Isa Conradsen, Jonas Duun-Henriksen, Troels W Kjaer, Carsten Eckhart Thomsen, Helge B D Sorensen

7 Citationer (Scopus)


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 extractor for detection of epileptic seizures.
TidsskriftI E E E Engineering in Medicine and Biology Society. Conference Proceedings
Sider (fra-til)3277-80
Antal sider4
StatusUdgivet - 1 jan. 2010


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