Physio4D: An Interactive Mobile Technology for Guidance of Physical Therapy Exercises at Home

超过2万名注册物理治疗师在加拿大工作。他们的目标是提供安全、高质量和 以病人为中心的服务，帮助病人在受伤或手术后恢复身体功能。它的速度是 患者的康复通常取决于后续的治疗和家庭锻炼。考虑到理疗 通常需要一周一次的探视，在白天伴随着家庭伸展/锻炼，执行 正确的练习是恢复过程中最重要的部分。在目前的系统中，物理治疗师提供 拿着讲义概述练习和图纸的患者可能会对更复杂的伸展感到困惑。 即使物理治疗师会演示练习，但从演示到第一次演示的时间通常会滞后 家庭治疗的时间可能比病人的记忆力还长。Physio4D为这个问题提供了一种移动解决方案 使用一组3D动作捕捉练习和实时提示反馈。 运动捕捉技术在肌肉骨骼疾病的诊断中显示出较高的准确性。然而， 运动捕捉目前还不能负担得起，也不能充分移动到患者使用。Physio4D解决了这个问题 使用运动捕捉工作室中记录的3D动画的存储库并由 经验丰富的理疗师。这些3D动画练习可以从多个角度查看，其中 普通手持设备的摄像头可以用来实时扫描患者的身体并提供 屏幕上的纠正指导。AnimationLeader的问题是他们没有足够的库 动作捕捉的理疗动作。此外，目前还不清楚如何绘制患者的行动图 (由移动MO-CAP系统捕获)到动作捕获的“正确”动作。这是 我们将在这项工作中通过应用我们先前对如何设计和 开发此问题的实时可视化解决方案。

More than 20,000 registered physiotherapists work in Canada. Their goal is to provide safe, high quality, and client-centered service to patients by restoring their physical function after injury or surgery. The rate at which patients heal is usually dependent on following up treatment with home exercises. Given that physiotherapy normally requires a once-a-week visit accompanied by home stretches/exercises during the day, performing the exercises correctly is the largest part of the recovery process. In the current system, physiotherapists provide patients with a handout outlining the exercise and the drawings can be confusing for more complex stretches. Even though the physiotherapist will demonstrate the exercise, quite often the lag in time from demo to first at home session can be longer than the patient's memory. Physio4D provides a mobile solution for this problem using a set of 3D motion captured exercises and real-time suggestive feedback. Motion capture technique has shown a higher accuracy in the diagnosis of musculoskeletal disorders. However, motion capture is currently not affordable nor sufficiently mobile to be used by patients. Physio4D solves this problem by using a repository of 3D animations recorded in a motion capture studio and authorized by an experienced physiotherapist. These 3D animated exercises can be viewed from multiple angles, where the cameras of common handheld devices can be used to scan the body of the patients in real-time and provide on-screen corrective guidance. The problem AnimationLeader has is that they do not have an adequate library of motion-captured physiotherapy movements. Furthermore, it is unclear how to map patients' movements (captured by the mobile mo-cap systems) to that of the motion-captured "correct" movements. This is the problem we will address in this work by applying some of our prior understanding of how to design and develop real-time visualizations for this problem.