Digital semiology and time-evolution pattern of bio-signals in focal onset motor seizures.

Epilepsy M-health Remote monitoring technology (RMT) Users Wearables

Journal

Seizure
ISSN: 1532-2688
Titre abrégé: Seizure
Pays: England
ID NLM: 9306979

Informations de publication

Date de publication:
Apr 2021
Historique:
received: 11 01 2021
revised: 11 03 2021
accepted: 14 03 2021
pubmed: 28 3 2021
medline: 13 7 2021
entrez: 27 3 2021
Statut: ppublish

Résumé

Focal seizures constitute the most common seizure type and are associated with poor control. One of the major difficulties in detecting focal onset with wearable devices seizures is related to their phenomenological complexity. We aimed at capturing focal onset seizures with motor manifestations with a multimodal wearable device to identify the digital semiology and the evolution pattern of ictal manifestations. Participants were asked to wear a multimodal wearable device (IMEC) aimed at seizure detection while admitted to an epilepsy monitoring unit. Seizures were labelled by a neurologist and start and offset time were noted. The signals captured by the device during the seizure window were plotted and a visual inspection was performed for focal motor seizures with impaired awareness and for focal motor aware seizures. Fifty-three seizures from twelve patients with focal seizures with motor manifestations recorded with the device were visually inspected. Overall, a common pattern presented across focal motor seizures with impaired awareness and it was characterized by early cardiac manifestations followed by motor phenomena and final EDA response. Motor seizures with retained awareness appeared to be characterized by brief motor events not associated with major autonomic manifestations Conclusion: an overall common digital phenotype and time-evolution pattern was demonstrated for focal motor seizures with impaired awareness. The identification of the evolution pattern could more precisely inform the development of highly preforming algorithms opening the possibility to a more precise, and potentially customizable way to optimize focal seizure detection.

Identifiants

pubmed: 33773333
pii: S1059-1311(21)00089-3
doi: 10.1016/j.seizure.2021.03.013
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

114-120

Informations de copyright

Copyright © 2021. Published by Elsevier Ltd.

Auteurs

Elisa Bruno (E)

Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK. Electronic address: elisa.bruno@kcl.ac.uk.

Andrea Biondi (A)

Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.

Mark P Richardson (MP)

Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.

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