Epilepsy is one of the most common neurological diseases, which has a cumulative lifetime incidence of 3%. Two to threefold increased morbidity and mortality rates are reported, especially if generalized tonic-clonic seizures (GTCS) occur. A wireless small and user-friendly detection system would be helpful in early identification of seizures. This could minimize the risk of seizure-related injuries and further allow complete seizure frequency documentation, especially in a non-clinical private setting. The aim of our study was to develop a design and to conduct an exploratory validation of an accelerometry (ACM)-based detection system for GTCS detection in real-time. Patients were recruited via the Epilepsy Monitoring Unit at the Department of Neurology, Medical University Innsbruck. In three out of 20 patients, four GTCS could be recorded. The ACM sensors recorded increased activities at the stated seizure time, which clearly differed from everyday movements. The temporary sensitivity (100%), specificity (≥88%) and the positive predictive value (≥75%) of the detection suggests a promising alarm/false alarm ratio. The validity of the detection device has to be evaluated with more data in order to be able to significantly confirm the positive results and to further develop a cut-off algorithm for automatic seizure detection.
Copyright © 2011 Elsevier B.V. All rights reserved.