TY - JOUR
T1 - Improving nocturnal event monitoring in people with intellectual disability in community using an artificial intelligence camera
AU - Lennard, Sarah
AU - Newman, Rachel
AU - McLean, Brendan
AU - Jory, Caryn
AU - Cox, David
AU - Young, Charlotte
AU - Corson, Eve
AU - Shankar, Rohit
N1 - Publisher Copyright:
© 2023 The Author(s)
PY - 2023/4/25
Y1 - 2023/4/25
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Developmental disabilities
KW - Risk mitigation
KW - Seizure deduction technology
KW - SUDEP
UR - http://www.scopus.com/inward/record.url?scp=85153594831&partnerID=8YFLogxK
UR - https://pearl.plymouth.ac.uk/context/pms-research/article/2071/viewcontent/pagination_EBR_100603.pdf
U2 - 10.1016/j.ebr.2023.100603
DO - 10.1016/j.ebr.2023.100603
M3 - Article
AN - SCOPUS:85153594831
SN - 2213-3232
VL - 22
JO - Epilepsy and Behavior Reports
JF - Epilepsy and Behavior Reports
M1 - 100603
ER -