Citation

Patel M, Pavic A, Goodwin VA. Gait Posture 2019; 76: 110-121.

Affiliation

PenARC, University of Exeter Medical School, University of Exeter, UK.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.gaitpost.2019.10.039

PMID

31756666

Abstract

BACKGROUND: Wearable inertial sensors have grown in popularity as a means of objectively assessing fall risk. This review aimed to identify gait and posture differences among older adult fallers and non-fallers which can be measured with the use of wearable inertial sensors. In addition to describing the number of sensors used to obtain measures, the concurrent anatomical locations, how these measures compare to current forms of clinical fall risk assessment tests and the setting of tests.

METHODS: Following the development of a rigorous search strategy, MEDLINE, Web of Science, Cochrane, EMBASE, PEDro, and CINAHL were systematically searched for studies involving the use of wearable inertial sensors, to determine gait and postural based differences among fallers or those at high fall risk compared with non-fallers and low fall risk adults aged 60 years and older.

RESULTS: Thirty five papers met the inclusion criteria. One hundred and forty nine gait and posture characteristic differences were identified using wearable inertial sensors. There were sensor derived measures which significantly and strongly correlated with traditional clinical tests. The use of a single wearable inertial sensor located at the lower posterior trunk, was most the most effective location and enough to ascertain multiple pertinent fall risk factors.

CONCLUSION: This review identified the capabilities of identifying fall risk factors among older adults with the use of wearable inertial sensors. The lightweight portable nature makes inertial sensors an effective tool to be implemented into clinical fall risk assessment and continuous unsupervised home monitoring, in addition to, outdoor testing.

Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

Language: en

Keywords

Fall risk; Gait; Older adults; Posture; Wearable inertial sensor