Feasibility of a continuous, multi-sensor remote health monitoring approach in persons living with neurodegenerative disease.

Adherence Cerebrovascular disease Neurodegenerative disease Remote monitoring User acceptance Wearable sensors

Journal

Journal of neurology
ISSN: 1432-1459
Titre abrégé: J Neurol
Pays: Germany
ID NLM: 0423161

Informations de publication

Date de publication:
May 2022
Historique:
received: 10 07 2021
accepted: 28 09 2021
revised: 27 09 2021
pubmed: 28 10 2021
medline: 23 4 2022
entrez: 27 10 2021
Statut: ppublish

Résumé

Remote health monitoring with wearable sensor technology may positively impact patient self-management and clinical care. In individuals with complex health conditions, multi-sensor wear may yield meaningful information about health-related behaviors. Despite available technology, feasibility of device-wearing in daily life has received little attention in persons with physical or cognitive limitations. This mixed methods study assessed the feasibility of continuous, multi-sensor wear in persons with cerebrovascular (CVD) or neurodegenerative disease (NDD). Thirty-nine participants with CVD, Alzheimer's disease/amnestic mild cognitive impairment, frontotemporal dementia, Parkinson's disease, or amyotrophic lateral sclerosis (median age 68 (45-83) years, 36% female) wore five devices (bilateral ankles and wrists, chest) continuously for a 7-day period. Adherence to device wearing was quantified by examining volume and pattern of device removal (non-wear). A thematic analysis of semi-structured de-brief interviews with participants and study partners was used to examine user acceptance. Adherence to multi-sensor wear, defined as a minimum of three devices worn concurrently, was high (median 98.2% of the study period). Non-wear rates were low across all sensor locations (median 17-22 min/day), with significant differences between some locations (p = 0.006). Multi-sensor non-wear was higher for daytime versus nighttime wear (p < 0.001) and there was a small but significant increase in non-wear over the collection period (p = 0.04). Feedback from de-brief interviews suggested that multi-sensor wear was generally well accepted by both participants and study partners. A continuous, multi-sensor remote health monitoring approach is feasible in a cohort of persons with CVD or NDD.

Sections du résumé

BACKGROUND BACKGROUND
Remote health monitoring with wearable sensor technology may positively impact patient self-management and clinical care. In individuals with complex health conditions, multi-sensor wear may yield meaningful information about health-related behaviors. Despite available technology, feasibility of device-wearing in daily life has received little attention in persons with physical or cognitive limitations. This mixed methods study assessed the feasibility of continuous, multi-sensor wear in persons with cerebrovascular (CVD) or neurodegenerative disease (NDD).
METHODS METHODS
Thirty-nine participants with CVD, Alzheimer's disease/amnestic mild cognitive impairment, frontotemporal dementia, Parkinson's disease, or amyotrophic lateral sclerosis (median age 68 (45-83) years, 36% female) wore five devices (bilateral ankles and wrists, chest) continuously for a 7-day period. Adherence to device wearing was quantified by examining volume and pattern of device removal (non-wear). A thematic analysis of semi-structured de-brief interviews with participants and study partners was used to examine user acceptance.
RESULTS RESULTS
Adherence to multi-sensor wear, defined as a minimum of three devices worn concurrently, was high (median 98.2% of the study period). Non-wear rates were low across all sensor locations (median 17-22 min/day), with significant differences between some locations (p = 0.006). Multi-sensor non-wear was higher for daytime versus nighttime wear (p < 0.001) and there was a small but significant increase in non-wear over the collection period (p = 0.04). Feedback from de-brief interviews suggested that multi-sensor wear was generally well accepted by both participants and study partners.
CONCLUSION CONCLUSIONS
A continuous, multi-sensor remote health monitoring approach is feasible in a cohort of persons with CVD or NDD.

Identifiants

pubmed: 34705114
doi: 10.1007/s00415-021-10831-z
pii: 10.1007/s00415-021-10831-z
pmc: PMC8548705
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2673-2686

Informations de copyright

© 2021. Crown.

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Auteurs

F Elizabeth Godkin (FE)

Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.

Erin Turner (E)

Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.

Youness Demnati (Y)

Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.

Adam Vert (A)

Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.

Angela Roberts (A)

School of Communication Sciences and Disorders, Elborn College, Western University, London, ON, Canada.
Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA.

Richard H Swartz (RH)

Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.

Paula M McLaughlin (PM)

Nova Scotia Health Authority, Halifax, NS, Canada.

Kyle S Weber (KS)

Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.

Vanessa Thai (V)

Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.

Kit B Beyer (KB)

Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.

Benjamin Cornish (B)

Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.

Agessandro Abrahao (A)

Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.

Sandra E Black (SE)

Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.

Mario Masellis (M)

Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.

Lorne Zinman (L)

Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.

Derek Beaton (D)

Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.

Malcolm A Binns (MA)

Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.
Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.

Vivian Chau (V)

Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.

Donna Kwan (D)

Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.

Andrew Lim (A)

Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.
Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.

Douglas P Munoz (DP)

Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.

Stephen C Strother (SC)

Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.
Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.

Kelly M Sunderland (KM)

Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.

Brian Tan (B)

Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.

William E McIlroy (WE)

Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada.

Karen Van Ooteghem (K)

Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, ON, Canada. kvanooteghem@uwaterloo.ca.

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