The Application of Artificial Intelligence in Digital Physical Activity and Falls Prevention Interventions for Older Adults.


Journal

Journal of aging and physical activity
ISSN: 1543-267X
Titre abrégé: J Aging Phys Act
Pays: United States
ID NLM: 9415639

Informations de publication

Date de publication:
01 10 2023
Historique:
received: 17 11 2022
revised: 02 01 2023
accepted: 01 02 2023
medline: 18 9 2023
pubmed: 21 4 2023
entrez: 20 04 2023
Statut: epublish

Résumé

This article discusses the practical applications of artificial intelligence in digital physical activity and falls prevention interventions for older adults. It notes the range of technologies that can be used to collect digital datasets on older adult health and how machine learning algorithms can be applied to these to improve our understanding of physical activity and falls. In particular, these advanced computational techniques could help personalize exercises, feedback, and notifications to older people, improve adherence to and reduce attrition from digital health interventions, and enhance monitoring by providing predictive analytics on the physiological and environmental conditions that contribute to physical activity and falls in aging populations.

Identifiants

pubmed: 37080545
doi: 10.1123/japa.2022-0376
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

887-889

Auteurs

David C Wong (DC)

Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester,United Kingdom.

Siobhan O'Connor (S)

Division of Nursing, Midwifery, and Social Work, The University of Manchester, Manchester,United Kingdom.

Emma Stanmore (E)

Division of Nursing, Midwifery, and Social Work, The University of Manchester, Manchester,United Kingdom.

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Classifications MeSH