Fürbass F, Ossenblok P, Hartmann M, Perko H, Skupch AM, Lindinger G, Elezi L, Pataraia E, Colon AJ, Baumgartner C, Kluge T. Prospective multi-center study of an automatic online seizure detection system for epilepsy monitoring units.
Clin Neurophysiol 2014;
126:1124-1131. [PMID:
25454341 DOI:
10.1016/j.clinph.2014.09.023]
[Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2014] [Revised: 09/17/2014] [Accepted: 09/24/2014] [Indexed: 10/24/2022]
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.
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