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Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera

There is higher prevalence of epilepsy and SUDEP in people with intellectual disability (PwID) compared to general population. Accurate seizure recording particularly at night can be challenging in PwID. Neuro Event Labs seizure monitoring (Nelli) uses high-quality video based artificial intelligenc...

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Detalles Bibliográficos
Autores principales: Lennard, Sarah, Newman, Rachel, McLean, Brendan, Jory, Caryn, Cox, David, Young, Charlotte, Corson, Eve, Shankar, Rohit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160340/
https://www.ncbi.nlm.nih.gov/pubmed/37152695
http://dx.doi.org/10.1016/j.ebr.2023.100603
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author Lennard, Sarah
Newman, Rachel
McLean, Brendan
Jory, Caryn
Cox, David
Young, Charlotte
Corson, Eve
Shankar, Rohit
author_facet Lennard, Sarah
Newman, Rachel
McLean, Brendan
Jory, Caryn
Cox, David
Young, Charlotte
Corson, Eve
Shankar, Rohit
author_sort Lennard, Sarah
collection PubMed
description There is higher prevalence of epilepsy and SUDEP in people with intellectual disability (PwID) compared to general population. Accurate seizure recording particularly at night can be challenging in PwID. Neuro Event Labs seizure monitoring (Nelli) uses high-quality video based artificial intelligence to detect and record possible nocturnal seizures. This study looks to evaluate the clinical utility and acceptability of Nelli in PwID and epilepsy. Family/carers of PwID and drug resistant epilepsy with suspicions of nocturnal seizures who had not tolerated routine or ambulatory EEGs were invited to evaluate Nelli. Relevant demographics and clinical characteristics were collected. Nelli’s impact, it’s facilitators, barriers and feedback quality was captured from patient and professional stakeholders. Quantitative and thematic analysis was undertaken. Fifteen PwID and epilepsy and four health professionals were involved. Nelli recorded 707 possible seizure events across the study cohort of which 247 were not heard or recognised by carers. Carers recorded 165 episodes of ‘restless’ or “seizure behaviour” which the Nelli did not deem to be seizures. There was 93% acceptability. Thematic analysis revealed three broad themes of device acceptability, result implementation and possible seizure recognition ability. Nelli allowed for improved communication and care planning in a hitherto difficult to investigate population.
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spelling pubmed-101603402023-05-06 Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera Lennard, Sarah Newman, Rachel McLean, Brendan Jory, Caryn Cox, David Young, Charlotte Corson, Eve Shankar, Rohit Epilepsy Behav Rep Article There is higher prevalence of epilepsy and SUDEP in people with intellectual disability (PwID) compared to general population. Accurate seizure recording particularly at night can be challenging in PwID. Neuro Event Labs seizure monitoring (Nelli) uses high-quality video based artificial intelligence to detect and record possible nocturnal seizures. This study looks to evaluate the clinical utility and acceptability of Nelli in PwID and epilepsy. Family/carers of PwID and drug resistant epilepsy with suspicions of nocturnal seizures who had not tolerated routine or ambulatory EEGs were invited to evaluate Nelli. Relevant demographics and clinical characteristics were collected. Nelli’s impact, it’s facilitators, barriers and feedback quality was captured from patient and professional stakeholders. Quantitative and thematic analysis was undertaken. Fifteen PwID and epilepsy and four health professionals were involved. Nelli recorded 707 possible seizure events across the study cohort of which 247 were not heard or recognised by carers. Carers recorded 165 episodes of ‘restless’ or “seizure behaviour” which the Nelli did not deem to be seizures. There was 93% acceptability. Thematic analysis revealed three broad themes of device acceptability, result implementation and possible seizure recognition ability. Nelli allowed for improved communication and care planning in a hitherto difficult to investigate population. Elsevier 2023-04-23 /pmc/articles/PMC10160340/ /pubmed/37152695 http://dx.doi.org/10.1016/j.ebr.2023.100603 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lennard, Sarah
Newman, Rachel
McLean, Brendan
Jory, Caryn
Cox, David
Young, Charlotte
Corson, Eve
Shankar, Rohit
Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera
title Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera
title_full Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera
title_fullStr Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera
title_full_unstemmed Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera
title_short Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera
title_sort improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160340/
https://www.ncbi.nlm.nih.gov/pubmed/37152695
http://dx.doi.org/10.1016/j.ebr.2023.100603
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