PFI-TT: Virtual Physical Therapy Using Mobile Devices and Artificial Intelligence

PFI-TT：使用移动设备和人工智能的虚拟物理治疗

• 批准号: 2044759
• 负责人: Sujit Dey
• 金额: $ 25万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2044759&HistoricalAwards=false
• 关键词: PFI; TT; Virtual; Physical; Therapy

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project includes providing access to physical therapy to large sections of society who cannot access clinic-based physical therapy for economic, geographic or health mobility reasons. The new system will focus initially on patients with stroke and various orthopedic conditions. By providing accurate, automated movement guidance to patients at home, the project aims to provide more timely, personalized physical therapy. Caregivers will have the ability to track the compliance and effectiveness of physical therapy. More effective patient engagement may lead to better health outcomes. Physical therapy clinics will be enabled to expand and scale up their businesses to reach a much larger customer base with innovative hybrid business models combining in-person, remote, and virtual therapy sessions. This type of system can enable other healthcare training applications and more meaningful video visits. The broader impacts of this project also include offering training in market-driven research, technology development, commercialization and entrepreneurship to the project team as well as broadening participation of women and underrepresented minority entrepreneurs in the commercialization effort. Thus, successful development and deployment of the virtual physical therapy system will have broad societal, commercial and educational benefits. The project creates a virtual physical therapy system by combining innovations in machine vision, artificial intelligence and mobile video technologies to ensure deep physical therapy expertise can be made available anywhere, with high accuracy, and in a personalized and timely fashion. For many medical conditions, ensuring proper exercise techniques throughout rehabilitation is very important, and constitutes a significant portion of a treatment session. Exercise quality performed by patients at home can vary. Some exercises can be harmful if performed incorrectly, causing painful setbacks. The team seeks to develop an advanced prototype of a virtual physical therapy system which can be used by patients anywhere with just a mobile device - either for live sessions with a remote therapist or for sessions with a machine-learning-based avatar which emulates a therapist with important real-time guidance. Successful implementation of the integrated solution will involve motion tracking and force estimation algorithms using mobile device cameras and machine learning algorithms for patient performance evaluation, with understanding of contextual and human factors that may guide judgment of physical therapists. The avatar and guidance rendering algorithms will minimize both human reaction and network latency in ways that can be most effective for patient training.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该创新-技术转化伙伴关系（PFI-TT）项目的更广泛影响/商业潜力包括为社会上因经济、地理或健康流动性原因无法获得诊所物理治疗的大部分人提供物理治疗。新系统最初将专注于中风和各种骨科疾病的患者。通过在家中为患者提供准确、自动化的运动指导，该项目旨在提供更及时、个性化的物理治疗。 护理人员将有能力跟踪物理治疗的依从性和有效性。 更有效的患者参与可能会带来更好的健康结果。物理治疗诊所将能够扩展和扩大其业务，通过结合面对面，远程和虚拟治疗会话的创新混合业务模式来覆盖更大的客户群。这种类型的系统可以实现其他医疗保健培训应用和更有意义的视频访问。该项目的更广泛影响还包括向项目小组提供市场驱动研究、技术开发、商业化和创业方面的培训，以及扩大妇女和代表性不足的少数民族企业家参与商业化工作。因此，虚拟物理治疗系统的成功开发和部署将具有广泛的社会、商业和教育效益。该项目通过结合机器视觉、人工智能和移动的视频技术的创新创建了一个虚拟物理治疗系统，以确保可以在任何地方以高准确性、个性化和及时的方式提供深入的物理治疗专业知识。对于许多医疗条件，在整个康复过程中确保适当的运动技术是非常重要的，并且构成了治疗过程的重要部分。 患者在家中进行的运动质量可能会有所不同。 有些练习如果做得不正确是有害的，会导致痛苦的挫折。该团队旨在开发一种先进的虚拟物理治疗系统原型，患者只需使用移动终端即可在任何地方使用-无论是与远程治疗师进行现场会话，还是与基于机器学习的化身进行会话，该化身模拟具有重要实时指导的治疗师。集成解决方案的成功实施将涉及使用移动终端摄像头的运动跟踪和力估计算法以及用于患者性能评估的机器学习算法，并了解可能指导物理治疗师判断的背景和人为因素。 化身和指导渲染算法将最大限度地减少人类反应和网络延迟的方式，可以最有效地为病人的培训。这个奖项反映了NSF的法定使命，并已被认为是值得的支持，通过评估使用基金会的智力价值和更广泛的影响审查标准。