F Fürbass1, P Ossenblok2, M Hartmann3, H Perko3, A M Skupch3, G Lindinger4, L Elezi5, E Pataraia4, A J Colon6, C Baumgartner5, T Kluge3. 1. Department Safety & Security, AIT Austrian Institute of Technology GmbH, Vienna, Austria. Electronic address: franz.fuerbass@ait.ac.at. 2. Clinical Physics, Academic Center of Epileptology, Heeze & Maastricht UMC+, The Netherlands. 3. Department Safety & Security, AIT Austrian Institute of Technology GmbH, Vienna, Austria. 4. Department of Clinical Neurology, Medical University of Vienna, Vienna, Austria. 5. General Hospital Hietzing with Neurological Center Rosenhuegel, 2nd Neurological Department, Vienna, Austria. 6. Department of Clinical Neurophysiology, Academic Center of Epileptology, Heeze & Maastricht UMC+, PO Box 61, 5590 AB Heeze, The Netherlands.
Abstract
OBJECTIVE: A method for automatic detection of epileptic seizures in long-term scalp-EEG recordings called EpiScan will be presented. EpiScan is used as alarm device to notify medical staff of epilepsy monitoring units (EMUs) in case of a seizure. METHODS: A prospective multi-center study was performed in three EMUs including 205 patients. A comparison between EpiScan and the Persyst seizure detector on the prospective data will be presented. In addition, the detection results of EpiScan on retrospective EEG data of 310 patients and the public available CHB-MIT dataset will be shown. RESULTS: A detection sensitivity of 81% was reached for unequivocal electrographic seizures with false alarm rate of only 7 per day. No statistical significant differences in the detection sensitivities could be found between the centers. The comparison to the Persyst seizure detector showed a lower false alarm rate of EpiScan but the difference was not of statistical significance. CONCLUSIONS: The automatic seizure detection method EpiScan showed high sensitivity and low false alarm rate in a prospective multi-center study on a large number of patients. SIGNIFICANCE: The application as seizure alarm device in EMUs becomes feasible and will raise the efficiency of video-EEG monitoring and the safety levels of patients.
OBJECTIVE: A method for automatic detection of epilepticseizures in long-term scalp-EEG recordings called EpiScan will be presented. EpiScan is used as alarm device to notify medical staff of epilepsy monitoring units (EMUs) in case of a seizure. METHODS: A prospective multi-center study was performed in three EMUs including 205 patients. A comparison between EpiScan and the Persyst seizure detector on the prospective data will be presented. In addition, the detection results of EpiScan on retrospective EEG data of 310 patients and the public available CHB-MIT dataset will be shown. RESULTS: A detection sensitivity of 81% was reached for unequivocal electrographic seizures with false alarm rate of only 7 per day. No statistical significant differences in the detection sensitivities could be found between the centers. The comparison to the Persyst seizure detector showed a lower false alarm rate of EpiScan but the difference was not of statistical significance. CONCLUSIONS: The automatic seizure detection method EpiScan showed high sensitivity and low false alarm rate in a prospective multi-center study on a large number of patients. SIGNIFICANCE: The application as seizure alarm device in EMUs becomes feasible and will raise the efficiency of video-EEG monitoring and the safety levels of patients.
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