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

Physio4D: An Interactive Mobile Technology for Guidance of Physical Therapy Exercises at Home
Physio4D:一种用于指导家庭物理治疗练习的交互式移动技术
批准号:
487116-2015
负责人:
Tang, Anthony
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31

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中文摘要
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英文摘要
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.
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CANet - Canadian Arrhythmia Network
  • 批准号:
    468630-2019
  • 项目类别:
    Networks of Centres of Excellence
  • 资助金额:
    $231.3万
  • 财政年份:
    2021
  • 负责人:
    Tang, Anthony
  • 依托单位:
Mixed-Reality Interfaces for Remote Collaboration
  • 批准号:
    RGPIN-2017-04883
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.95万
  • 财政年份:
    2021
  • 负责人:
    Tang, Anthony
  • 依托单位:
CANet - Canadian Arrhythmia Network
  • 批准号:
    468630-2019
  • 项目类别:
    Networks of Centres of Excellence
  • 资助金额:
    $183.95万
  • 财政年份:
    2020
  • 负责人:
    Tang, Anthony
  • 依托单位:
Mixed-Reality Interfaces for Remote Collaboration
  • 批准号:
    RGPIN-2017-04883
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.48万
  • 财政年份:
    2020
  • 负责人:
    Tang, Anthony
  • 依托单位:
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