Literature DB >> 33652175

Toward Remote Assessment of Physical Frailty Using Sensor-based Sit-to-stand Test.

Catherine Park1, Amir Sharafkhaneh2, Mon S Bryant2, Christina Nguyen2, Ilse Torres2, Bijan Najafi3.   

Abstract

BACKGROUND: Traditional physical frailty (PF) screening tools are resource intensive and unsuitable for remote assessment. In this study, we used five times sit-to-stand test (5×STS) with wearable sensors to determine PF and three key frailty phenotypes (slowness, weakness, and exhaustion) objectively.
MATERIALS AND METHODS: Older adults (n = 102, age: 76.54 ± 7.72 y, 72% women) performed 5×STS while wearing sensors attached to the trunk and bilateral thigh and shank. Duration of 5×STS was recorded using a stopwatch. Seventeen sensor-derived variables were analyzed to determine the ability of 5×STS to distinguish PF, slowness, weakness, and exhaustion. Binary logistic regression was used, and its area under curve was calculated.
RESULTS: A strong correlation was observed between sensor-based and manually-recorded 5xSTS durations (r = 0.93, P < 0.0001). Sensor-derived variables indicators of slowness (5×STS duration, hip angular velocity range, and knee angular velocity range), weakness (hip power range and knee power range), and exhaustion (coefficient of variation (CV) of hip angular velocity range, CV of vertical velocity range, and CV of vertical power range) were different between the robust group and prefrail/frail group (P < 0.05) with medium to large effect sizes (Cohen's d = 0.50-1.09). The results suggested that sensor-derived variables enable identifying PF, slowness, weakness, and exhaustion with an area under curve of 0.861, 0.865, 0.720, and 0.723, respectively.
CONCLUSIONS: Our study suggests that sensor-based 5×STS can provide digital biomarkers of PF, slowness, weakness, and exhaustion. The simplicity, ease of administration in front of a camera, and safety of 5xSTS may facilitate a remote assessment of PF, slowness, weakness, and exhaustion via telemedicine.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Digital biomarker; Digital health; Physical frailty; Remote patient monitoring; Sit-to-stand test; Wearable

Mesh:

Year:  2021        PMID: 33652175      PMCID: PMC9113630          DOI: 10.1016/j.jss.2021.01.023

Source DB:  PubMed          Journal:  J Surg Res        ISSN: 0022-4804            Impact factor:   2.417


  37 in total

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6.  Frailty as a predictor of surgical outcomes in older patients.

Authors:  Martin A Makary; Dorry L Segev; Peter J Pronovost; Dora Syin; Karen Bandeen-Roche; Purvi Patel; Ryan Takenaga; Lara Devgan; Christine G Holzmueller; Jing Tian; Linda P Fried
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Authors: 
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Review 8.  Frailty and post-operative outcomes in older surgical patients: a systematic review.

Authors:  Hui-Shan Lin; J N Watts; N M Peel; R E Hubbard
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9.  How clinical practitioners assess frailty in their daily practice: an international survey.

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Authors:  Stephen M Cornish; Dean M Cordingley; Keely A Shaw; Scott C Forbes; Taylor Leonhardt; Ainsley Bristol; Darren G Candow; Philip D Chilibeck
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5.  Digital Biomarker Representing Frailty Phenotypes: The Use of Machine Learning and Sensor-Based Sit-to-Stand Test.

Authors:  Catherine Park; Ramkinker Mishra; Amir Sharafkhaneh; Mon S Bryant; Christina Nguyen; Ilse Torres; Aanand D Naik; Bijan Najafi
Journal:  Sensors (Basel)       Date:  2021-05-08       Impact factor: 3.576

  5 in total

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