Lin Shayne, Mann Jotvarinder, Mansfield Avril, Wang Rosalie H, Harris Jocelyn E, Taati Babak
Division of Engineering Science, University of Toronto, Toronto, Canada.
Toronto Rehabilitation Institute, University Health Network, Toronto, Canada.
J Rehabil Assist Technol Eng. 2019 Mar 18;6:2055668319831631. doi: 10.1177/2055668319831631. eCollection 2019 Jan-Dec.
Homework-based rehabilitation programs can help stroke survivors restore upper extremity function. However, compensatory motions can develop without therapist supervision, leading to sub-optimal recovery. We developed a visual feedback system using a live video feed or an avatar reflecting users' movements so users are aware of compensations. This pilot study aimed to evaluate validity (how well the avatar characterizes different types of compensations) and acceptability of the system.
Ten participants with chronic stroke performed upper-extremity exercises under three feedback conditions: none, video, and avatar. Validity was evaluated by comparing agreement on compensations annotated using video and avatar images. A usability survey was administered to participants after the experiment to obtain information on acceptability.
There was substantial agreement between video and avatar images for shoulder elevation and hip extension (Cohen's κ: 0.6-0.8) and almost perfect agreement for trunk rotation and flexion (κ: 0.80-1). Acceptability was low due to lack of corrective prompts and occasional noise with the avatar display. Most participants suggested that an automatic compensation detection feature with visual and auditory cuing would improve the system.
The avatar characterized four types of compensations well. Future work will involve increasing sensitivity for shoulder elevation and implementing a method to detect compensations.
基于家庭作业的康复计划有助于中风幸存者恢复上肢功能。然而,在没有治疗师监督的情况下可能会出现代偿动作,导致恢复效果欠佳。我们开发了一种视觉反馈系统,该系统使用实时视频或反映用户动作的虚拟形象,以便用户了解代偿情况。这项初步研究旨在评估该系统的有效性(虚拟形象对不同类型代偿的表征程度)和可接受性。
10名慢性中风患者在三种反馈条件下进行上肢锻炼:无反馈、视频反馈和虚拟形象反馈。通过比较使用视频和虚拟形象图像标注的代偿情况的一致性来评估有效性。实验结束后,对参与者进行可用性调查,以获取有关可接受性的信息。
视频和虚拟形象图像在肩部抬高和髋部伸展方面有实质性一致性(科恩kappa系数:0.6 - 0.8),在躯干旋转和屈曲方面几乎完全一致(kappa系数:0.80 - 1)。由于缺乏纠正提示以及虚拟形象显示偶尔出现噪声,可接受性较低。大多数参与者建议,具有视觉和听觉提示的自动代偿检测功能将改善该系统。
虚拟形象能很好地表征四种类型的代偿。未来的工作将包括提高对肩部抬高的敏感度以及实施一种检测代偿的方法。