An automated, electronic assessment tool can accurately classify older adult postural stability
Journal article
Johnson, Liam, Fry, Adam, Dehbandi, Behdad, Rubin, Lawrence, Halem, Michael, Barachant, Alexandre, Smeragliuolo, Anna H. and Putrino, David. (2019). An automated, electronic assessment tool can accurately classify older adult postural stability. Journal of Biomechanics. 93, pp. 6-10. https://doi.org/10.1016/j.jbiomech.2019.06.001
Authors | Johnson, Liam, Fry, Adam, Dehbandi, Behdad, Rubin, Lawrence, Halem, Michael, Barachant, Alexandre, Smeragliuolo, Anna H. and Putrino, David |
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Abstract | Current methods of balance assessment in the clinical environment are often subjective, time-consuming and lack clinical relevance for non-ambulatory older adults. The objective of this study was to develop a novel method of balance assessment that utilizes data collected using the Microsoft Kinect 2 to create a Berg Balance Scale score, which is completely determined by statistical methods rather than by human evaluators. 74 older adults, both healthy and balance impaired, were recruited for this trial. All participants completed the Berg Balance Scale (BBS) which was scored independently by trained physical therapists. Participants then completed the items of the “Modified Berg Balance Scale” in front of the Microsoft Kinect camera. Kinematic data collected during this measurement was used to train a feed-forward neural network that was used to assign a Berg Balance Scale score. The neural network model estimated the clinician-assigned BBS score to within a median of 0.93 points for the participants in our sample population (range: 0.02–5.69). Using low-cost depth sensing camera technology and a clinical protocol that takes less than 5 min to complete in both ambulatory and non-ambulatory older adults, the method outlined in this manuscript can accurately predict a participant’s BBS score and thereby identify whether they are deemed a high fall risk or not. If implemented correctly, this could enable fall prevention services to be deployed in a timely fashion using low-cost, accessible technology, resulting in improved safety of older adults. |
Keywords | Postural instability; Older adults; Microsoft Kinect 2; Berg Balance Scale |
Year | 2019 |
Journal | Journal of Biomechanics |
Journal citation | 93, pp. 6-10 |
Publisher | Elsevier |
ISSN | 0021-9290 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.jbiomech.2019.06.001 |
Scopus EID | 2-s2.0-85067237738 |
Open access | Published as green open access |
Page range | 6-10 |
Research Group | Sports Performance, Recovery, Injury and New Technologies (SPRINT) Research Centre |
Author's accepted manuscript | License File Access Level Open |
Publisher's version | License All rights reserved File Access Level Controlled |
Output status | Published |
Publication dates | |
Online | 06 Jun 2019 |
Publication process dates | |
Accepted | 01 Jun 2019 |
Place of publication | United Kingdom |
https://acuresearchbank.acu.edu.au/item/89zqy/an-automated-electronic-assessment-tool-can-accurately-classify-older-adult-postural-stability
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Author's accepted manuscript
AM_Johnson_2019_An_automated_electronic_assessment_tool_can.pdf | |
License: CC BY-NC-ND | |
File access level: Open |
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