Artificial Intelligence in Extended Reality and Digital Rehabilitation Technologies for Fall Prevention in Older Adults: A Rapid Review of the Evidence.

IF 2 4区 医学 Q3 CLINICAL NEUROLOGY
Muhammad Haris, Barbara Augusta Martins, Bowen Cai, Bonnie Dueck, Brittany Elliott, Jesse Gibbons, Mina Park, Mê-Linh Lê, Ke Peng, Zahra Moussavi, Hamdoni Pangandaman, Mirella Veras
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Abstract

BackgroundFall-related injuries in older adults remain a major health concern, contributing to functional dependence and healthcare losses. Traditional prevention programs, while effective, remain underutilized due to poor adherence and participation. Extended reality (XR) technologies, combined with artificial intelligence (AI), are emerging as promising solutions to mitigate fall-related outcomes.ObjectiveTo evaluate existing literature on extended (XR) and virtual reality (VR) based interventions and the role of AI in improving balance, mobility and fall outcomes among older adults.MethodologyA rapid review was conducted using Cochrane Rapid Review methods and conducted in Ovid MEDLINE, Scopus, and IEEE Xplore. Studies meeting eligibility criteria were screened and extracted using Covidence. Data on study design, participant characteristics, intervention components, outcome measures, and key findings were extracted and synthesized, narratively with attention to AI use within XR interventions.ResultsAfter dual screening, four studies met the inclusion criteria. XR and VR interventions showed improvements in mobility, movement quality and muscular strength. Two studies used AI primarily for movement classification and postural control analysis. One exergame study without AI showed mixed results. Participant engagement was generally high, with low dropout rates. Most full-text exclusions were due to absence of AI methods, highlighting the limited AI-specific evidence base. No study measured fall incidence directly.ConclusionThis rapid review highlights the effectiveness of XR interventions in enhancing mobility and participant adherence. However, evidence is limited as the available publications remain preliminary and do not demonstrate fall reduction and the added benefits of AI. Larger, well-designed studies are needed to establish the clinical value of these technologies.

人工智能在扩展现实和数字康复技术预防老年人跌倒:证据的快速回顾。
背景:老年人跌倒相关损伤仍然是一个主要的健康问题,导致功能依赖和医疗保健损失。传统的预防方案虽然有效,但由于依从性和参与性差,仍未得到充分利用。扩展现实(XR)技术与人工智能(AI)相结合,正在成为减轻跌倒相关后果的有希望的解决方案。目的评价基于扩展(XR)和虚拟现实(VR)的干预措施的现有文献,以及人工智能在改善老年人平衡、活动和跌倒结局中的作用。方法采用Cochrane快速综述方法,在Ovid MEDLINE、Scopus和IEEE explore中进行快速综述。使用covid对符合资格标准的研究进行筛选和提取。提取和综合了研究设计、参与者特征、干预成分、结果测量和关键发现的数据,并对人工智能在XR干预中的使用进行了叙述。结果经双重筛选,4项研究符合纳入标准。XR和VR干预显示出活动能力、运动质量和肌肉力量的改善。两项研究主要使用人工智能进行运动分类和姿势控制分析。一项没有人工智能的游戏研究结果好坏参半。参与者的参与度普遍较高,辍学率较低。大多数全文排除是由于缺乏人工智能方法,突出了有限的人工智能特定证据基础。没有研究直接测量跌倒发生率。结论:这项快速回顾强调了XR干预在增强活动能力和参与者依从性方面的有效性。然而,证据有限,因为现有的出版物仍然是初步的,并没有证明人工智能可以减少跌倒和带来额外的好处。需要更大规模、设计良好的研究来确定这些技术的临床价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
NeuroRehabilitation
NeuroRehabilitation CLINICAL NEUROLOGY-REHABILITATION
CiteScore
3.20
自引率
0.00%
发文量
178
审稿时长
6-12 weeks
期刊介绍: NeuroRehabilitation, an international, interdisciplinary, peer-reviewed journal, publishes manuscripts focused on scientifically based, practical information relevant to all aspects of neurologic rehabilitation. We publish unsolicited papers detailing original work/research that covers the full life span and range of neurological disabilities including stroke, spinal cord injury, traumatic brain injury, neuromuscular disease and other neurological disorders. We also publish thematically organized issues that focus on specific clinical disorders, types of therapy and age groups. Proposals for thematic issues and suggestions for issue editors are welcomed.
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