Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic

Detalhes bibliográficos
Autor(a) principal: Brinkmann, Benjamin H.
Data de Publicação: 2021
Outros Autores: Karoly, Philippa J., Nurse, Ewan S., Dumanis, Sonya B., Nasseri, Mona, Viana, Pedro, Schulze-Bonhage, Andreas, Freestone, Dean R., Worrell, Greg, Richardson, Mark P., Cook, Mark J.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10451/49523
Resumo: Copyright © 2021 Brinkmann, Karoly, Nurse, Dumanis, Nasseri, Viana, Schulze-Bonhage, Freestone, Worrell, Richardson and Cook. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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spelling Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinicEpilepsyMachine learningMultidian cyclesSeizure detectionSeizure forecastingWearable devicesCopyright © 2021 Brinkmann, Karoly, Nurse, Dumanis, Nasseri, Viana, Schulze-Bonhage, Freestone, Worrell, Richardson and Cook. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.It is a major challenge in clinical epilepsy to diagnose and treat a disease characterized by infrequent seizures based on patient or caregiver reports and limited duration clinical testing. The poor reliability of self-reported seizure diaries for many people with epilepsy is well-established, but these records remain necessary in clinical care and therapeutic studies. A number of wearable devices have emerged, which may be capable of detecting seizures, recording seizure data, and alerting caregivers. Developments in non-invasive wearable sensors to measure accelerometry, photoplethysmography (PPG), electrodermal activity (EDA), electromyography (EMG), and other signals outside of the traditional clinical environment may be able to identify seizure-related changes. Non-invasive scalp electroencephalography (EEG) and minimally invasive subscalp EEG may allow direct measurement of seizure activity. However, significant network and computational infrastructure is needed for continuous, secure transmission of data. The large volume of data acquired by these devices necessitates computer-assisted review and detection to reduce the burden on human reviewers. Furthermore, user acceptability of such devices must be a paramount consideration to ensure adherence with long-term device use. Such devices can identify tonic-clonic seizures, but identification of other seizure semiologies with non-EEG wearables is an ongoing challenge. Identification of electrographic seizures with subscalp EEG systems has recently been demonstrated over long (>6 month) durations, and this shows promise for accurate, objective seizure records. While the ability to detect and forecast seizures from ambulatory intracranial EEG is established, invasive devices may not be acceptable for many individuals with epilepsy. Recent studies show promising results for probabilistic forecasts of seizure risk from long-term wearable devices and electronic diaries of self-reported seizures. There may also be predictive value in individuals' symptoms, mood, and cognitive performance. However, seizure forecasting requires perpetual use of a device for monitoring, increasing the importance of the system's acceptability to users. Furthermore, long-term studies with concurrent EEG confirmation are lacking currently. This review describes the current evidence and challenges in the use of minimally and non-invasive devices for long-term epilepsy monitoring, the essential components in remote monitoring systems, and explores the feasibility to detect and forecast impending seizures via long-term use of these systems.FrontiersRepositório da Universidade de LisboaBrinkmann, Benjamin H.Karoly, Philippa J.Nurse, Ewan S.Dumanis, Sonya B.Nasseri, MonaViana, PedroSchulze-Bonhage, AndreasFreestone, Dean R.Worrell, GregRichardson, Mark P.Cook, Mark J.2021-09-15T16:45:51Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/49523engFront Neurol. 2021 Jul 13;12:69040410.3389/fneur.2021.6904041664-2295info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-08T16:53:22Zoai:repositorio.ul.pt:10451/49523Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:01:09.065132Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
title Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
spellingShingle Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
Brinkmann, Benjamin H.
Epilepsy
Machine learning
Multidian cycles
Seizure detection
Seizure forecasting
Wearable devices
title_short Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
title_full Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
title_fullStr Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
title_full_unstemmed Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
title_sort Seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic
author Brinkmann, Benjamin H.
author_facet Brinkmann, Benjamin H.
Karoly, Philippa J.
Nurse, Ewan S.
Dumanis, Sonya B.
Nasseri, Mona
Viana, Pedro
Schulze-Bonhage, Andreas
Freestone, Dean R.
Worrell, Greg
Richardson, Mark P.
Cook, Mark J.
author_role author
author2 Karoly, Philippa J.
Nurse, Ewan S.
Dumanis, Sonya B.
Nasseri, Mona
Viana, Pedro
Schulze-Bonhage, Andreas
Freestone, Dean R.
Worrell, Greg
Richardson, Mark P.
Cook, Mark J.
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Brinkmann, Benjamin H.
Karoly, Philippa J.
Nurse, Ewan S.
Dumanis, Sonya B.
Nasseri, Mona
Viana, Pedro
Schulze-Bonhage, Andreas
Freestone, Dean R.
Worrell, Greg
Richardson, Mark P.
Cook, Mark J.
dc.subject.por.fl_str_mv Epilepsy
Machine learning
Multidian cycles
Seizure detection
Seizure forecasting
Wearable devices
topic Epilepsy
Machine learning
Multidian cycles
Seizure detection
Seizure forecasting
Wearable devices
description Copyright © 2021 Brinkmann, Karoly, Nurse, Dumanis, Nasseri, Viana, Schulze-Bonhage, Freestone, Worrell, Richardson and Cook. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
publishDate 2021
dc.date.none.fl_str_mv 2021-09-15T16:45:51Z
2021
2021-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10451/49523
url http://hdl.handle.net/10451/49523
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Front Neurol. 2021 Jul 13;12:690404
10.3389/fneur.2021.690404
1664-2295
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Frontiers
publisher.none.fl_str_mv Frontiers
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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