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Performance of digital technologies in assessing fall risks among older adults with cognitive impairment: a systematic review.
Koh, Vanessa; Xuan, Lai Wei; Zhe, Tan Kai; Singh, Navrag; B Matchar, David; Chan, Angelique.
Afiliación
  • Koh V; Programme in Health Services and Systems Research (HSSR), Duke-NUS Medical School, Singapore, Singapore. vanessa.kjw@u.duke.nus.edu.
  • Xuan LW; Centre for Ageing Research and Education (CARE), Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore. vanessa.kjw@u.duke.nus.edu.
  • Zhe TK; Programme in Health Services and Systems Research (HSSR), Duke-NUS Medical School, Singapore, Singapore.
  • Singh N; Future Health Technologies Programme, Singapore-ETH Centre, Singapore, Singapore.
  • B Matchar D; Future Health Technologies Programme, Singapore-ETH Centre, Singapore, Singapore.
  • Chan A; Laboratory for Movement Biomechanics, Institute for Biomechanics, ETH Zurich, Zurich, Switzerland.
Geroscience ; 46(3): 2951-2975, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38436792
ABSTRACT
Older adults with cognitive impairment (CI) are twice as likely to fall compared to the general older adult population. Traditional fall risk assessments may not be suitable for older adults with CI due to their reliance on attention and recall. Hence, there is an interest in using objective technology-based fall risk assessment tools to assess falls within this population. This systematic review aims to evaluate the features and performance of technology-based fall risk assessment tools for older adults with CI. A systematic search was conducted across several databases such as PubMed and IEEE Xplore, resulting in the inclusion of 22 studies. Most studies focused on participants with dementia. The technologies included sensors, mobile applications, motion capture, and virtual reality. Fall risk assessments were conducted in the community, laboratory, and institutional settings; with studies incorporating continuous monitoring of older adults in everyday environments. Studies used a combination of technology-based inputs of gait parameters, socio-demographic indicators, and clinical assessments. However, many missed the opportunity to include cognitive performance inputs as predictors to fall risk. The findings of this review support the use of technology-based fall risk assessment tools for older adults with CI. Further advancements incorporating cognitive measures and additional longitudinal studies are needed to improve the effectiveness and clinical applications of these assessment tools. Additional work is also required to compare the performance of existing methods for fall risk assessment, technology-based fall risk assessments, and the combination of these approaches.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Geroscience Año: 2024 Tipo del documento: Article País de afiliación: Singapur

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Geroscience Año: 2024 Tipo del documento: Article País de afiliación: Singapur