TY - JOUR PY - 2019// TI - An automated, electronic assessment tool can accurately classify older adult postural stability JO - Journal of biomechanics A1 - Johnson, Liam A1 - Fry, Adam A1 - Dehbandi, Behdad A1 - Rubin, Lawrence A1 - Halem, Michael A1 - Barachant, Alexandre A1 - Smeragliuolo, Anna H. A1 - Putrino, David SP - 6 EP - 10 VL - 93 IS - N2 - 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.

Copyright © 2019 Elsevier Ltd. All rights reserved.

Language: en

LA - en SN - 0021-9290 UR - http://dx.doi.org/10.1016/j.jbiomech.2019.06.001 ID - ref1 ER -