Nairn, Brooke;
Tsakanikas, Vassilios;
Gordon, Becky;
Karapintzou, Evita;
Kaski, Diego;
Fotiadis, Dimitrios I;
Bamiou, Doris-Eva;
(2024)
Smart wearable technologies for balance rehabilitation in older adults for falls risk: a scoping review and comparative analysis (Preprint).
JMIR Rehabilitation and Assistive Technologies
10.2196/69589.
(In press).
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Abstract
Background: Falls among older adults are a significant public health concern, often leading to severe injuries, decreased quality of life, and substantial healthcare costs. Smart wearable technology systems for balance rehabilitation present a promising avenue for addressing the falls epidemic, capable of providing detailed objective movement data, engaging visuals, and real-time feedback. With the recent and rapid evolution of innovative technologies, including artificial intelligence (AI), augmented reality (AR)/virtual reality (VR), and motion tracking, there is a need to evaluate the market to identify the most effective and accessible smart balance systems currently available Objective: This review aims to evaluate the current landscape of smart wearable technology solutions for balance rehabilitation in older adults at risk of falls. Additionally, it aims to compare market available systems to TeleRehab DSS, a recently developed smart balance system Methods: A scoping review and SWOT analysis was completed, exploring the landscape of smart balance systems in older adults at risk of falls. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, electronic databases PUBMED, MEDLINE, and Cochrane were systematically searched for articles in English from July 1, 2014, to July 1, 2024. Grey literature searches of relevant institutions and webpages were also conducted. The database search and commercial systems were then compared against the TeleRehab DSS in a SWOT analysis Results: The scoping review yielded 17 systems that met the inclusion criteria; 10 investigational systems and 7 commercially available systems. Only one study reported the use of intelligent learning/AI. Eight studies reported the use of motion tracking, with two protocols not reporting its use. Of the studies incorporating motion tracking, three provided feedback as either visual or auditory. Nine of the 10 included studies incorporated either AR or VR, with one study using a computer interface. All but two studies reported the use of gamification, and seven studies incorporated balance exercises. Two studies reported remote delivery, with five being clinician-supervised and four providing a clinician report. The SWOT analysis of TeleRehab DSS against the 7 market-available smart balance systems revealed several unique advantages including personalized therapy with AI-DSS, AR for real-world interaction, enhanced clinician involvement, and comprehensive data analytics. Conclusions: Despite limitations such as cost, accessibility, and user training requirements. Conclusions: Despite limitations such as cost, accessibility, and user training requirements, TeleRehab DSS emerges as a significant innovation in smart balance systems. It offers a unique blend of AI personalization, AR, and real-time clinician monitoring for balance rehabilitation among middle-aged and older adults at risk of falls. These features position it as a next-generation solution that aligns closely with the evolving needs of patients and clinicians.
| Type: | Article |
|---|---|
| Title: | Smart wearable technologies for balance rehabilitation in older adults for falls risk: a scoping review and comparative analysis (Preprint) |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.2196/69589 |
| Publisher version: | https://doi.org/10.2196/69589 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > The Ear Institute |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10207618 |
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