Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit

Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit

Background: Using machine learning to combine wrist accelerometer (ACM) and electrodermal activity (EDA) has been shown effective to detect primarily and secondarily generalized tonic-clonic seizures, here termed as convulsive seizures (CS). A prospective study was conducted for the FDA clearance of...

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Bibliographic Details
Main Authors: Francesco Onorati, Giulia Regalia, Chiara Caborni, W. Curt LaFrance, Andrew S. Blum, Jonathan Bidwell, Paola De Liso, Rima El Atrache, Tobias Loddenkemper, Fatemeh Mohammadpour-Touserkani, Rani A. Sarkis, Daniel Friedman, Jay Jeschke, Rosalind Picard
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-08-01
Series:Frontiers in Neurology
Subjects:
epilepsy
seizure detection
wearable sensors
machine learning
clinical validation
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2021.724904/full

Internet

https://www.frontiersin.org/articles/10.3389/fneur.2021.724904/full

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