CPS:Medium:Quantitative Visual Sensing of Dynamic Behaviors for Home-based Progressive Rehabilitation

CPS：中：基于家庭渐进式康复的动态行为的定量视觉感知

• 批准号: 1314484
• 负责人: Yun Fu
• 金额: $ 101.14万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-29 至 2016-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1314484&HistoricalAwards=false
• 关键词: CPS; Medium; Quantitative; Visual; Sensing

The objective of this research is to develop a comprehensive theoretical and experimental cyber-physical framework to enable intelligent human-environment interaction capabilities by a synergistic combination of computer vision and robotics. Specifically, the approach is applied to examine individualized remote rehabilitation with an intelligent, articulated, and adjustable lower limb orthotic brace to manage Knee Osteoarthritis, where a visual-sensing/dynamical-systems perspective is adopted to: (1) track and record patient/device interactions with internet-enabled commercial-off-the-shelf computer-vision-devices; (2) abstract the interactions into parametric and composable low-dimensional manifold representations; (3) link to quantitative biomechanical assessment of the individual patients; (4) facilitate development of individualized user models and exercise regimen; and (5) aid the progressive parametric refinement of exercises and adjustment of bracing devices. This research and its results will enable us to understand underlying human neuro-musculo-skeletal and locomotion principles by merging notions of quantitative data acquisition, and lower-order modeling coupled with individualized feedback. Beyond efficient representation, the quantitative visual models offer the potential to capture fundamental underlying physical, physiological, and behavioral mechanisms grounded on biomechanical assessments, and thereby afford insights into the generative hypotheses of human actions.Knee osteoarthritis is an important public health issue, because of high costs associated with treatments. The ability to leverage a quantitative paradigm, both in terms of diagnosis and prescription, to improve mobility and reduce pain in patients would be a significant benefit. Moreover, the home-based rehabilitation setting offers not only immense flexibility, but also access to a significantly greater portion of the patient population. The project is also integrated with extensive educational and outreach activities to serve a variety of communities.

本研究的目标是开发一个全面的理论和实验网络物理框架，通过计算机视觉和机器人技术的协同结合，实现智能的人与环境交互能力。具体地说，该方法被应用于研究使用智能的、铰接的和可调节的下肢矫形支具来管理膝骨关节炎的个性化远程康复，其中采用视觉传感/动态系统的观点来：（1）跟踪和记录患者/设备与互联网使能的商业现成计算机视觉设备的交互;（2）将交互抽象为参数化和可组合的低维流形表示;（3）链接到个体患者的定量生物力学评估;（4）促进个性化用户模型和锻炼方案的开发;以及（5）帮助锻炼的渐进参数细化和支撑装置的调整。这项研究及其结果将使我们能够通过合并定量数据采集和低阶建模与个性化反馈的概念来理解潜在的人类神经肌肉骨骼和运动原理。除了有效的代表性，定量视觉模型提供了潜在的捕获基本的物理，生理和行为机制的基础上的生物力学评估，从而提供洞察人类action.Knee骨关节炎的生成假说是一个重要的公共卫生问题，因为与治疗相关的高成本。在诊断和处方方面利用定量范例来改善患者的移动性和减少疼痛的能力将是一个显著的益处。此外，以家庭为基础的康复环境不仅提供了巨大的灵活性，而且还可以接触到更大比例的患者。该项目还与广泛的教育和外展活动相结合，为各种社区服务。