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dc.contributor.authorLennard, S
dc.contributor.authorNewman, R
dc.contributor.authorMcLean, B
dc.contributor.authorJory, C
dc.contributor.authorCox, D
dc.contributor.authorYoung, C
dc.contributor.authorCorson, E
dc.contributor.authorShankar, R
dc.date.accessioned2023-07-31T14:02:08Z
dc.date.available2023-07-31T14:02:08Z
dc.date.issued2023-04-25
dc.identifier.issn2589-9864
dc.identifier.issn2589-9864
dc.identifier.other100603
dc.identifier.urihttps://pearl.plymouth.ac.uk/handle/10026.1/21098
dc.description.abstract

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.

dc.format.extent100603-100603
dc.format.mediumElectronic-eCollection
dc.languageen
dc.publisherElsevier BV
dc.subjectArtificial intelligence
dc.subjectDevelopmental disabilities
dc.subjectSUDEP
dc.subjectRisk mitigation
dc.subjectSeizure deduction technology
dc.titleImproving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera
dc.typejournal-article
dc.typeArticle
plymouth.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/37152695
plymouth.volume22
plymouth.publisher-urlhttp://dx.doi.org/10.1016/j.ebr.2023.100603
plymouth.publication-statusPublished
plymouth.journalEpilepsy & Behavior Reports
dc.identifier.doi10.1016/j.ebr.2023.100603
plymouth.organisational-group|Plymouth
plymouth.organisational-group|Plymouth|Faculty of Health
plymouth.organisational-group|Plymouth|Users by role
dc.publisher.placeUnited States
dcterms.dateAccepted2023-04-19
dc.date.updated2023-07-31T14:02:08Z
dc.rights.embargodate2023-8-1
dc.identifier.eissn2589-9864
dc.rights.embargoperiodforever
rioxxterms.versionofrecord10.1016/j.ebr.2023.100603


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