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Improved screening ...
Improved screening of fall risk using free-living based accelerometer data
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- Kelly, D. (författare)
- Ulster University, Northern Ireland, United Kingdom
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- Condell, J. (författare)
- Ulster University, Northern Ireland, United Kingdom
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- Gillespie, J. (författare)
- Ulster University, Northern Ireland, United Kingdom
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- Munoz Esquivel, K. (författare)
- Ulster University, Northern Ireland, United Kingdom
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- Barton, J. (författare)
- Tyndall National Institute, University College Cork, Ireland
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- Tedesco, S. (författare)
- Tyndall National Institute, University College Cork, Ireland
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- Nordström, Anna (författare)
- Umeå universitet,Avdelningen för hållbar hälsa,Idrottshögskolan vid Umeå universitet,Geriatrik
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- Larsson, Markus Åkerlund (författare)
- Umeå universitet,Avdelningen för hållbar hälsa
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- Alamäki, A. (författare)
- Karelia University of Applied Sciences, Finland
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(creator_code:org_t)
- Elsevier BV, 2022
- 2022
- Engelska.
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Ingår i: Journal of Biomedical Informatics. - : Elsevier BV. - 1532-0464 .- 1532-0480. ; 131
- Relaterad länk:
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Falls are one of the most costly population health issues. Screening of older adults for fall risks can allow for earlier interventions and ultimately lead to better outcomes and reduced public health spending. This work proposes a solution to limitations in existing fall screening techniques by utilizing a hip-based accelerometer worn in free-living conditions. The work proposes techniques to extract fall risk features from periods of free-living ambulatory activity. Analysis of the proposed techniques is conducted and compared with existing screening methods using Functional Tests and Lab-based Gait Analysis. 1705 Older Adults from Umea (Sweden) were assessed. Data consisted of 1 Week of hip worn accelerometer data, gait measurements and performance metrics for 3 functional tests. Retrospective and Prospective fall data were also recorded based on the incidence of falls occurring 12 months before and after the study commencing respectively. Machine learning based experiments show accelerometer based measures perform best when predicting falls. Prospective falls had a sensitivity and specificity of 0.61 and 0.66 respectively while retrospective falls had a sensitivity and specificity of 0.61 and 0.68 respectively.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Hälsovetenskap -- Sjukgymnastik (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Health Sciences -- Physiotherapy (hsv//eng)
Nyckelord
- Accelerometer
- Fall risk
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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