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Sensing Technology to Monitor Behavioral and Psychological Symptoms and to Assess Treatment Response in People With Dementia. A Systematic Review.
Husebo, Bettina S; Heintz, Hannah L; Berge, Line I; Owoyemi, Praise; Rahman, Aniqa T; Vahia, Ipsit V.
Afiliação
  • Husebo BS; Department of Global Public Health and Primary Care, Centre for Elderly and Nursing Home Medicine, University of Bergen, Bergen, Norway.
  • Heintz HL; Department of Nursing Home Medicine, Municipality of Bergen, Bergen, Norway.
  • Berge LI; Division of Geriatric Psychiatry, McLean Hospital, Belmont, MA, United States.
  • Owoyemi P; Department of Global Public Health and Primary Care, Centre for Elderly and Nursing Home Medicine, University of Bergen, Bergen, Norway.
  • Rahman AT; NKS Olaviken Gerontopsychiatric Hospital, Bergen, Norway.
  • Vahia IV; Division of Geriatric Psychiatry, McLean Hospital, Belmont, MA, United States.
Front Pharmacol ; 10: 1699, 2019.
Article em En | MEDLINE | ID: mdl-32116687
Background: The prevalence of dementia is expected to rapidly increase in the next decades, warranting innovative solutions improving diagnostics, monitoring and resource utilization to facilitate smart housing and living in the nursing home. This systematic review presents a synthesis of research on sensing technology to assess behavioral and psychological symptoms and to monitor treatment response in people with dementia. Methods: The literature search included medical peer-reviewed English language publications indexed in Embase, Medline, Cochrane library and Web of Sciences, published up to the 5th of April 2019. Keywords included MESH terms and phrases synonymous with "dementia", "sensor", "patient", "monitoring", "behavior", and "therapy". Studies applying both cross sectional and prospective designs, either as randomized controlled trials, cohort studies, and case-control studies were included. The study was registered in PROSPERO 3rd of May 2019. Results: A total of 1,337 potential publications were identified in the search, of which 34 were included in this review after the systematic exclusion process. Studies were classified according to the type of technology used, as (1) wearable sensors, (2) non-wearable motion sensor technologies, and (3) assistive technologies/smart home technologies. Half of the studies investigated how temporarily dense data on motion can be utilized as a proxy for behavior, indicating high validity of using motion data to monitor behavior such as sleep disturbances, agitation and wandering. Further, up to half of the studies represented proof of concept, acceptability and/or feasibility testing. Overall, the technology was regarded as non-intrusive and well accepted. Conclusions: Targeted clinical application of specific technologies is poised to revolutionize precision care in dementia as these technologies may be used both by patients and caregivers, and at a systems level to provide safe and effective care. To highlight awareness of legal regulations, data risk assessment, and patient and public involvement, we propose a necessary framework for sustainable ethical innovation in healthcare technology. The success of this field will depend on interdisciplinary cooperation and the advance in sustainable ethic innovation. Systematic Review Registration: PROSPERO, identifier CRD42019134313.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Diagnostic_studies / Observational_studies / Risk_factors_studies / Systematic_reviews Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Diagnostic_studies / Observational_studies / Risk_factors_studies / Systematic_reviews Idioma: En Ano de publicação: 2019 Tipo de documento: Article