Collaborative Research: RAPID: Understanding and Facilitating Remote Triage and Rehabilitation During Pandemics via Visual Based Patient Physiologic Sensing

合作研究:RAPID:通过基于视觉的患者生理感知理解和促进大流行期间的远程分诊和康复

基本信息

  • 批准号:
    2030430
  • 负责人:
  • 金额:
    $ 6.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-06-01 至 2022-05-31
  • 项目状态:
    已结题

项目摘要

This RAPID project plans to investigate visual-based physiological sensing technologies to facilitate remote triage and rehabilitation during pandemics, by using low-cost consumer-grade cameras to track such physiological conditions as respiration rate, heart rate, and blood oxygen saturation levels from videos. The physiological data can be visualized and archived, and shared by users with medical practitioners to understand and support remote triage and rehabilitation.The proposed research can enhance the interaction between medical providers and patients, and help address a projected surge in telehealth needs due to COVID-19. The PI team plans to conduct the first-of-a-kind data collection, by incorporating the novel contact-free video sensing into a biomedical cohort study that is being rolled out by a public-health collaboration team. This cross-disciplinary opportunity of multimodal data collection will offer insights on the relationship of multiple biosensing modalities, and the data collected would facilitate the research on early detection of COVID-19 and related diseases. The visual-based physiological sensing will also help enhance the remote interaction between rehabilitation therapists and patients during pandemics.The intellectual merit of this effort lies in advancing promising engineering techniques of video-based contact-free physiological monitoring to support the rising needs of remote triage and rehabilitation during pandemics. The research findings and techniques developed address an important missing component in telehealth, which simultaneously achieves social-distancing, avoids hospital overcrowding, and prioritizes personal protective equipment in response to pandemics. By collaborating with another cohort study, an unprecedented multitude of data collected by the joint effort will provide key insights toward understanding and managing COVID-19 diseases and remote triage for future outbreaks. The timeliness of this opportunity cannot be met by any regular NSF programs other than the RAPID.The project’s broader impact lies in two aspects. The multidisciplinary effort will provide important new knowledge and insights toward understanding and developing technology capabilities for remote triage and rehabilitation, which will contribute to the early detection, spread control, and effective management and prevention of future epidemics. The techniques developed through the project to support tele-rehabilitation will have a strong potential to improve the adverse conditions and quality of life of the affected citizens.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.
RAPID项目计划研究基于视觉的生理传感技术,通过使用低成本的消费级相机跟踪视频中的呼吸率、心率和血氧饱和度等生理状况,促进流行病期间的远程分诊和康复。生理数据可以可视化和存档,并由用户与医生共享,以了解和支持远程分诊和康复。拟议的研究可以加强医疗提供者和患者之间的互动,并有助于解决因COVID-19而导致的预计远程医疗需求激增的问题。PI团队计划通过将这种新型的无接触视频传感技术整合到一项生物医学队列研究中,进行首次数据收集,该研究正在由一个公共卫生合作团队推出。这一跨学科的多模式数据收集机会将为多种生物传感模式之间的关系提供见解,所收集的数据将促进COVID-19及相关疾病的早期发现研究。基于视觉的生理感应也将有助于在大流行期间加强康复治疗师和患者之间的远程互动。这一努力的智力价值在于推进有前途的基于视频的无接触生理监测工程技术,以支持大流行期间日益增长的远程分诊和康复需求。开发的研究成果和技术解决了远程保健中缺失的一个重要组成部分,它同时实现了社交距离,避免了医院过度拥挤,并优先考虑个人防护装备以应对大流行病。通过与另一项队列研究合作,通过共同努力收集的前所未有的大量数据将为了解和管理COVID-19疾病以及为未来疫情进行远程分诊提供关键见解。这个机会的及时性是除了RAPID之外任何常规NSF项目都无法满足的。该项目更广泛的影响体现在两个方面。多学科的努力将为理解和发展远程分诊和康复的技术能力提供重要的新知识和见解,这将有助于早期发现、传播控制以及有效管理和预防未来的流行病。通过该项目开发的支持远程康复的技术将有很大潜力改善受影响公民的不利条件和生活质量。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Adaptive Multi-Trace Carving for Robust Frequency Tracking in Forensic Applications
A Multi-Channel Ratio-of-Ratios Method for Noncontact Hand Video Based SpO$_2$ Monitoring Using Smartphone Cameras
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Chau-Wai Wong其他文献

TikTok engagement traces over time and health risky behaviors: Combining data linkage and computational methods
  • DOI:
    10.1016/j.tele.2025.102305
  • 发表时间:
    2025-09-01
  • 期刊:
  • 影响因子:
    8.300
  • 作者:
    Xinyan Zhao;Chau-Wai Wong
  • 通讯作者:
    Chau-Wai Wong

Chau-Wai Wong的其他文献

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{{ truncateString('Chau-Wai Wong', 18)}}的其他基金

Collaborative Research: Facilitating Supply Chain Trust via Micro-Surface Sensing and Vision-Enabled Authentication
合作研究:通过微表面传感和视觉认证促进供应链信任
  • 批准号:
    2227499
  • 财政年份:
    2022
  • 资助金额:
    $ 6.5万
  • 项目类别:
    Standard Grant

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