智能可穿戴技术用于有跌倒风险的老年人平衡康复:范围回顾和比较分析。

Q2 Medicine
Brooke Nairn, Vassilios Tsakanikas, Becky Gordon, Efterpi Karapintzou, Diego Kaski, Dimitrios I Fotiadis, Doris-Eva Bamiou
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引用次数: 0

摘要

背景:老年人跌倒是一个重大的公共卫生问题,经常导致严重伤害、生活质量下降和大量医疗保健费用。用于平衡康复的智能可穿戴技术为解决跌倒流行病提供了一条有前途的途径,能够提供详细的客观运动数据,引人入胜的视觉效果和实时反馈。随着包括人工智能(AI)、增强现实(AR)或虚拟现实(VR)以及运动跟踪在内的创新技术的快速发展,有必要评估市场,以确定目前可用的最有效和最容易获得的智能平衡系统。目的:本研究旨在评估智能可穿戴技术系统用于有跌倒风险的老年人平衡康复的现状。此外,它旨在将市场上可用的系统与最近开发的智能平衡系统远程康复平衡临床和经济决策支持系统(TeleRehab DSS)进行比较。方法:进行范围审查和优势、劣势、机会和威胁(SWOT)分析,探索智能平衡系统在有跌倒风险的老年人中的应用前景。根据系统评价和荟萃分析扩展范围评价(PRISMA-ScR)指南的首选报告项目,系统检索了2014年7月1日至2024年7月1日的电子数据库PubMed、MEDLINE和Cochrane的英文文章。对相关机构和网页进行灰色文献检索。然后在SWOT分析中将数据库搜索和商业系统与TeleRehab DSS进行比较。结果:范围审查产生17个系统符合纳入标准;10个试验系统和7个商用系统。在10项研究中,只有1项报告使用了智能学习或人工智能,8项研究报告使用了运动跟踪,9项研究使用了虚拟现实。在结合运动跟踪的研究中,有3项提供了视觉或听觉反馈。除2项研究外,所有研究都报告了游戏化的使用,7项研究纳入了平衡练习。总共有2项研究报告了远程分娩,其中5项由临床医生监督,4项提供临床医生报告。TeleRehab DSS与7个市场上可用的智能平衡系统进行SWOT分析,发现了一些独特的优势,包括AI-DSS的个性化治疗、现实世界互动的AR、增强的临床医生参与和全面的数据分析。结论:这一范围综述的发现强调了智能平衡系统的快速发展,但在人工智能集成、远程可访问性和临床医生驱动的数据分析方面仍存在重大差距。尽管存在成本、可访问性和用户培训要求等方面的限制,TeleRehab DSS仍是一项重大创新,通过人工智能驱动的个性化、现实世界互动的增强现实和临床医生实时监测,解决了许多这些差距。这些功能使其成为下一代解决方案,与患者和临床医生不断变化的需求密切相关。本综述的结果为未来的研究提供了有价值的见解,支持了进一步验证研究和开发更智能、更容易获得的平衡康复技术的需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Wearable Technologies for Balance Rehabilitation in Older Adults at Risk of Falls: Scoping Review and Comparative Analysis.

Background: Falls among older adults are a significant public health concern, often leading to severe injuries, decreased quality of life, and substantial health care costs. Smart wearable technologies 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) or 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 study aims to evaluate the current landscape of smart wearable technology systems for balance rehabilitation in older adults at risk of falls. In addition, it aims to compare market-available systems to the telerehabilitation of balance clinical and economic decision support system (TeleRehab DSS), a recently developed smart balance system.

Methods: A scoping review and strengths, weaknesses, opportunities, and threats (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 (PRISMA-ScR) guidelines, electronic databases PubMed, MEDLINE, and Cochrane were systematically searched for articles in English from July 1, 2014, to July 1, 2024. Gray literature searches of relevant institutions and web pages 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. Out of 10 studies, only 1 reported the use of intelligent learning or AI, 8 studies reported the use of motion tracking, and 9 studies used virtual reality. Of the studies incorporating motion tracking, 3 provided feedback as either visual or auditory. All but 2 studies reported the use of gamification, and 7 studies incorporated balance exercises. In total, 2 studies reported remote delivery, with 5 being clinician-supervised and 4 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: The findings from this scoping review highlight the rapid evolution of smart balance systems, yet significant gaps remain in AI integration, remote accessibility, and clinician-driven data analytics. Despite limitations such as cost, accessibility, and user training requirements, TeleRehab DSS emerges as a significant innovation, addressing many of these gaps through AI-driven personalization, AR for real-world interaction, and real-time clinician monitoring. These features position it as a next-generation solution that aligns closely with the evolving needs of patients and clinicians. The results of this review provide valuable insights for future research, supporting the need for further validation studies and the development of more intelligent and accessible balance rehabilitation technologies.

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来源期刊
CiteScore
4.20
自引率
0.00%
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31
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