Timely and adequate rehabilitation is critical in facilitating post-stroke recovery. However, the organization and delivery of rehabilitation are resource-demanding, and are only available to approximately 25% of stroke survivors in low-to-middle-income countries. Improving access to stroke rehabilitation services through innovative solutions is therefore urgently required. Tele-rehabilitation, which transits care to home- and community settings, has emerged as a promising solution. However, current approaches using video tutorial, teleconference, or other specialized devices face inherent shortfalls that limit their uptake. In this study, we proposed and validated the use of an open-source, markerless motion capture model with consumer-grade devices to overcome these challenges. Our solution enables reliable measurement of the end range of motion during upper limb exercises with near-perfect waveform similarity and intraclass correlation to that of the gold standard Kinect approach. Our multidisciplinary team developed an automated telerehabilitation framework incorporating the validated markerless technique to facilitate a seamless telerehabilitation process. It enables personalized rehabilitation plans with real-time feedback, and individual progress reports using objective quantitative and qualitative features to improve patient monitoring and management, and home-based rehabilitation service uptake and compliance. This study serves as a proof-of-concept in preparation for the future development of a detailed model of care, and feasibility, usability, and cost-effectiveness studies of an automated telerehabilitation platform and framework in improving the state of post-stroke rehabilitation and functional outcome.

翻译：及时且充分的康复治疗对于促进中风后恢复至关重要。然而，康复服务的组织与实施需要大量资源，在中低收入国家中仅约25%的中风幸存者能获得此类服务。因此，亟需通过创新解决方案改善中风康复服务的可及性。将护理转移至家庭和社区环境的远程康复已成为一种有前景的解决方案。然而，当前采用视频教程、远程会议或其他专用设备的方法存在固有缺陷，限制了其推广应用。本研究提出并验证了一种使用消费级设备的开源无标记动作捕捉模型，以克服上述挑战。该方案能够在上肢锻炼过程中可靠测量末端活动范围，其波形相似度和组内相关系数与金标准Kinect方法近乎完美。我们的多学科团队开发了一个自动化远程康复框架，整合了经过验证的无标记技术，以实现无缝康复流程。该框架支持个性化康复计划、实时反馈，并通过客观量化和定性特征生成个体进展报告，从而改善患者监测与管理，提升居家康复服务的接受度和依从性。本研究作为概念验证，为未来开发详细护理模式，以及评估自动化远程康复平台与框架在改善中风后康复状态与功能结局方面的可行性、可用性和成本效益奠定基础。