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Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic
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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8315760/ https://www.ncbi.nlm.nih.gov/pubmed/34326807 http://dx.doi.org/10.3389/fneur.2021.690404 |
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author | Brinkmann, Benjamin H. Karoly, Philippa J. Nurse, Ewan S. Dumanis, Sonya B. Nasseri, Mona Viana, Pedro F. Schulze-Bonhage, Andreas Freestone, Dean R. Worrell, Greg Richardson, Mark P. Cook, Mark J. |
author_facet | Brinkmann, Benjamin H. Karoly, Philippa J. Nurse, Ewan S. Dumanis, Sonya B. Nasseri, Mona Viana, Pedro F. Schulze-Bonhage, Andreas Freestone, Dean R. Worrell, Greg Richardson, Mark P. Cook, Mark J. |
author_sort | Brinkmann, Benjamin H. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8315760 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83157602021-07-28 Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic Brinkmann, Benjamin H. Karoly, Philippa J. Nurse, Ewan S. Dumanis, Sonya B. Nasseri, Mona Viana, Pedro F. Schulze-Bonhage, Andreas Freestone, Dean R. Worrell, Greg Richardson, Mark P. Cook, Mark J. Front Neurol Neurology 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. Frontiers Media S.A. 2021-07-13 /pmc/articles/PMC8315760/ /pubmed/34326807 http://dx.doi.org/10.3389/fneur.2021.690404 Text en Copyright © 2021 Brinkmann, Karoly, Nurse, Dumanis, Nasseri, Viana, Schulze-Bonhage, Freestone, Worrell, Richardson and Cook. https://creativecommons.org/licenses/by/4.0/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. |
spellingShingle | Neurology Brinkmann, Benjamin H. Karoly, Philippa J. Nurse, Ewan S. Dumanis, Sonya B. Nasseri, Mona Viana, Pedro F. Schulze-Bonhage, Andreas Freestone, Dean R. Worrell, Greg Richardson, Mark P. Cook, Mark J. Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic |
title | 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_short | Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic |
title_sort | seizure diaries and forecasting with wearables: epilepsy monitoring outside the clinic |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8315760/ https://www.ncbi.nlm.nih.gov/pubmed/34326807 http://dx.doi.org/10.3389/fneur.2021.690404 |
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