Authors
Jackson Mittlesteadt, Sven Bambach, Alex Dawes, Evelynne Wentzel, Andrea Debs, Emre Sezgin, Dan Digby, Yungui Huang, Andrea Ganger, Shivani Bhatnagar, Lori Ehrenberg, Sunjay Nunley, Peter Glynn, Simon Lin, Steve Rust, Anup D Patel
Publication date
2020/11
Journal
Journal of Child Neurology
Volume
35
Issue
13
Pages
873-878
Publisher
SAGE Publications
Description
Currently, the tracking of seizures is highly subjective, dependent on qualitative information provided by the patient and family instead of quantifiable seizure data. Usage of a seizure detection device to potentially detect seizure events in a population of epilepsy patients has been previously done. Therefore, we chose the Fitbit Charge 2 smart watch to determine if it could detect seizure events in patients when compared to continuous electroencephalographic (EEG) monitoring for those admitted to an epilepsy monitoring unit. A total of 40 patients were enrolled in the study that met the criteria between 2015 and 2016. All seizure types were recorded. Twelve patients had a total of 53 epileptic seizures. The patient-aggregated receiver operating characteristic curve had an area under the curve of 0.58 [0.56, 0.60], indicating that the neural network models were generally able to detect seizure events at an above …
Total citations
20222023202452
Scholar articles
J Mittlesteadt, S Bambach, A Dawes, E Wentzel… - Journal of Child Neurology, 2020