Ettefagh Alireza, Roshan Fekr Atena
KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.
Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
J Rehabil Assist Technol Eng. 2024 Jun 4;11:20556683241259256. doi: 10.1177/20556683241259256. eCollection 2024 Jan-Dec.
Tele-rehabilitation is a healthcare practice that leverages technology to provide rehabilitation services remotely to individuals in their own homes or other locations. With advancements in remote monitoring and Artificial Intelligence, automatic tele-rehabilitation systems that can measure joint angles, recognize exercises, and provide feedback based on movement analysis are being developed. Such platforms can offer valuable information to clinicians for improved care planning. However, with various methods and sensors being used, understanding their pros, cons, and performance is important. This paper reviews and compares the performance of recent vision-based, wearable, and pressure-sensing technologies used in lower limb tele-rehabilitation systems over the past 10 years (from 2014 to 2023). We selected studies that were published in English and focused on joint angle estimation, activity recognition, and exercise assessment. Vision-based approaches were the most common, accounting for 42% of studies. Wearable technology followed at approximately 37%, and pressure-sensing technology appeared in 21% of studies. Identified gaps include a lack of uniformity in reported performance metrics and evaluation methods, a need for cross-subject validation, inadequate testing with patients and older adults, restricted sets of exercises evaluated, and a scarcity of comprehensive datasets on lower limb exercises, especially those involving movements while lying down.
远程康复是一种利用技术为在家中或其他地点的个人提供远程康复服务的医疗保健实践。随着远程监测和人工智能的进步,能够测量关节角度、识别运动并基于运动分析提供反馈的自动远程康复系统正在开发中。这样的平台可以为临床医生提供有价值的信息,以改进护理计划。然而,由于使用了各种方法和传感器,了解它们的优缺点和性能很重要。本文回顾并比较了过去10年(2014年至2023年)在下肢远程康复系统中使用的基于视觉、可穿戴和压力传感的最新技术的性能。我们选择了以英文发表的、专注于关节角度估计、活动识别和运动评估的研究。基于视觉的方法最为常见,占研究的42%。可穿戴技术约占37%,压力传感技术出现在21%的研究中。发现的差距包括报告的性能指标和评估方法缺乏一致性、需要进行跨受试者验证、对患者和老年人的测试不足、评估的运动集有限,以及下肢运动的综合数据集稀缺,尤其是那些涉及躺下时运动的数据集。