Accepted for/Published in: JMIR Rehabilitation and Assistive Technologies
Date Submitted: Dec 19, 2024
Open Peer Review Period: Jan 10, 2025 - Mar 7, 2025
Date Accepted: Apr 3, 2025
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Comparative evaluation of smart wearable technology solutions for balance rehabilitation in older adults at risk of falls: a scoping review and SWOT analysis
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.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.