Nouredanesh, Mina, Godfrey, Alan, Howcroft, Jennifer, Lemaire, Edward and Tung, James (2021) Fall risk assessment in the wild: A critical examination of wearable sensor use in free-living conditions. Gait & Posture, 85. pp. 178-190. ISSN 0966-6362
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2020_Nouredanesh_G_P_.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (1MB) | Preview |
Abstract
Background
Despite advances in laboratory-based supervised fall risk assessment methods (FRAs), falls still remain a major public health problem. This can be due to the alteration of behavior in laboratory due to the awareness of being observed (i.e., Hawthorne effect), the multifactorial complex etiology of falls, and our limited understanding of human behaviour in natural environments, or in the’ wild’. To address these imitations, a growing body of literature has focused on free-living wearable-sensor-based FRAs. The objective of this narrative literature review is to discuss papers investigating natural data collected by wearable sensors for a duration of at least 24 h to identify fall-prone older adults.
Methods
Databases (Scopus, PubMed and Google Scholar) were searched for studies based on a rigorous search strategy.
Results
Twenty-four journal papers were selected, in which inertial sensors were the only wearable system employed for FRA in the wild. Gait was the most-investigated activity; but sitting, standing, lying, transitions and gait events, such as turns and missteps, were also explored. A multitude of free-living fall predictors (FLFPs), e.g., the quantity of daily steps, were extracted from activity bouts and events. FLFPs were further categorized into discrete domains (e.g., pace, complexity) defined by conceptual or data-driven models. Heterogeneity was found within the reviewed studies, which includes variance in: terminology (e.g., quantity vs macro), hyperparameters to define/estimate FLFPs, models and domains, and data processing approaches (e.g., the cut-off thresholds to define an ambulatory bout). These inconsistencies led to different results for similar FLFPs, limiting the ability to interpret and compare the evidence.
Conclusion
Free-living FRA is a promising avenue for fall prevention. Achieving a harmonized model is necessary to systematically address the inconsistencies in the field and identify FLFPs with the highest predictive values for falls to eventually address intervention programs and fall prevention.
Item Type: | Article |
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Additional Information: | Funding information: M Nouredanesh was funded by AGE-WELL NCE Inc. (Canada’s technology and aging network) Graduate Scholarship. A Godfrey holds a grant from the Royal Academy of Engineering: Frontiers of Engineering for Development (FoESF1819T621). The rest of co-authors were supported by National Sciences and Engineering Research Council of Canada (NSERC): E Lemaire (2014-129967) and J Tung (2015-05317). None of the funding sources had a role in the writing of this review. The authors would like to thank Shahrose Aratia for the assistance with literature search and data abstraction. |
Uncontrolled Keywords: | Falls in elderly, inertial measurement unit, wearable sensors, ambulatory fall risk assessment, free-living fall predictors |
Subjects: | B800 Medical Technology G900 Others in Mathematical and Computing Sciences H300 Mechanical Engineering |
Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
Depositing User: | Elena Carlaw |
Date Deposited: | 07 Apr 2020 09:27 |
Last Modified: | 31 Jul 2021 16:32 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/42712 |
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