Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9190315 | Epilepsy & Behavior | 2005 | 11 Pages |
Abstract
Seizure detection results based on the visual analysis of three-dimensional (3D) accelerometry (ACM) and video/EEG recordings are reported for 18 patients with severe epilepsy. They were monitored for 36 hours during which 897 seizures were detected. This was seven times higher than the number of seizures reported by nurses during the registration period. The results in this article demonstrate that 3D ACM is a valuable sensing method for seizure detection in this population. Four hundred twenty-eight (48%) seizures were detected by ACM. With 3D ACM alone it was possible to detect all the seizures in 10 of the 18 patients. Three-dimensional ACM also was complementary to EEG in our population. ACM patterns during seizures were stereotypical in 95% of the motor seizures. These characteristic patterns are a starting point for automated seizure detection.
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Authors
Tamara M.E. Nijsen, Johan B.A.M. Arends, Paul A.M. Griep, Pierre J.M. Cluitmans,