I-Corps: Vision analysis system using inferred three-dimensional data to analyze and correct a user’s pose in relation to 3D space

I-Corps：视觉分析系统，使用推断的三维数据来分析和纠正用户相对于 3D 空间的姿势

• 批准号: 2403992
• 负责人: Christopher Heylman
• 金额: $ 5万
• 依托单位: California Polytechnic State University Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-02-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2403992&HistoricalAwards=false
• 关键词: Corps; Vision; analysis; system; using

The broader impact/commercial potential of this I-Corps project is the development of rehabilitative technology, focusing on augmenting home-based exercise regimens for precise mobility recovery. Currently, there is a growing need for accessible and consistent physical therapy support while current tools lead to poor adherence and ultimately poor recovery outcomes. The proposed technology provides an analysis of the human body to encourage recovery for physical therapy patients both in-clinic and at home through audio/visual feedback and corrective coaching. The technology is designed to provide instantaneous corrections and synchronized progress with care providers, while the pose analysis and real-time guidance system provides confidence during exercise sessions. The goal is to facilitate better health outcomes and improved quality of life by improving access to personalized rehabilitation, potentially reducing healthcare disparities and cost of knowledgeable, accessible care. This I-Corps project is based on the development of a software tool for physical rehabilitation, that addresses independently performed exercises for patients in physical therapy. Currently, clinicians are limited by home exercise tools that do not have customizable features. The proposed vision analysis system uses inferred three-dimensional data to analyze and correct a user’s pose in relation to 3D space. The technology includes a machine learning (ML) algorithm to dynamically extrapolate human pose insights and offers corrective action as needed. In addition, the proposed tool leverages a deep-learning approach that continues to improve through learning from outcomes and identifying engaging techniques for continued recovery. The goal is to provide high-precision support at-home that complements physical recovery and directly impacts mobility and therapy objectives. The proposed technology provides real-time guidance, corrective coaching, and integrated progress tracking, which may significantly improve the effectiveness of home-based exercises.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I-Corps项目的更广泛的影响/商业潜力是开发康复技术，重点是增强基于家庭的运动方案以进行精确的移动性恢复。当前，对可访问和一致的物理疗法支持的需求日益增长，而当前工具导致依从性差，最终导致恢复结果差。提出的技术对人体进行了分析，以通过音频/视觉反馈和正确的教练来鼓励临床和家里的物理治疗患者恢复。该技术旨在提供瞬时校正和与护理提供者同步的进度，而姿势分析和实时指导系统在练习期间提供了信心。目的是通过改善获得个性化康复的机会，潜在地减少医疗保健分配以及知识渊博，可访问的护理成本，从而促进更好的健康成果和改善生活质量。这个I-Corps项目基于开发用于物理康复的软件工具，该工具针对物理治疗中的患者独立进行练习。目前，临床医生受到没有可自定义功能的家庭锻炼工具的限制。提出的视觉分析系统使用推断的三维数据来分析和纠正用户相对于3D空间的姿势。该技术包括一种机器学习（ML）算法，以动态推断人姿势见解并根据需要提供纠正措施。此外，提议的工具还利用了一种深入学习的方法，该方法通过从结果中学习和确定引人入胜的技术来继续改善，以持续恢复。目的是提供高精度支持，以完成身体恢复并直接影响移动性和治疗目标。拟议的技术提供了实时指导，纠正辅导和综合进度跟踪，这可能会大大提高基于家庭练习的有效性。该奖项反映了NSF的法定任务，并通过评估该基金会的知识分子优点和更广泛的影响来审查标准。