Performance of digital technologies in assessing fall risks among older adults with cognitive impairment: a systematic review.
| dc.contributor.author | Koh, Vanessa | |
| dc.contributor.author | Xuan, Lai Wei | |
| dc.contributor.author | Zhe, Tan Kai | |
| dc.contributor.author | Singh, Navrag | |
| dc.contributor.author | B Matchar, David | |
| dc.contributor.author | Chan, Angelique | |
| dc.date.accessioned | 2024-03-25T08:13:25Z | |
| dc.date.available | 2024-03-25T08:13:25Z | |
| dc.date.issued | 2024-03 | |
| dc.description.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. | |
| dc.identifier | 10.1007/s11357-024-01098-z | |
| dc.identifier.issn | 2509-2715 | |
| dc.identifier.issn | 2509-2723 | |
| dc.identifier.uri | ||
| dc.language | eng | |
| dc.publisher | Springer Science and Business Media LLC | |
| dc.relation.ispartof | GeroScience | |
| dc.relation.isversionof | 10.1007/s11357-024-01098-z | |
| dc.rights.uri | ||
| dc.subject | Cognitive impairment | |
| dc.subject | Digital technologies | |
| dc.subject | Fall prediction | |
| dc.subject | Falls risk assessment | |
| dc.subject | Older adults | |
| dc.title | Performance of digital technologies in assessing fall risks among older adults with cognitive impairment: a systematic review. | |
| dc.type | Journal article | |
| pubs.organisational-group | Duke | |
| pubs.organisational-group | School of Medicine | |
| pubs.organisational-group | Clinical Science Departments | |
| pubs.organisational-group | Medicine | |
| pubs.organisational-group | Pathology | |
| pubs.organisational-group | Medicine, General Internal Medicine | |
| pubs.organisational-group | University Initiatives & Academic Support Units | |
| pubs.organisational-group | University Institutes and Centers | |
| pubs.organisational-group | Duke Global Health Institute | |
| pubs.publication-status | Published |
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