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 项目更广泛的影响/商业潜力是康复技术的开发，重点是增强家庭锻炼方案以实现精确的活动恢复。目前，在当前工具领先的情况下，对可访问和一致的物理治疗支持的需求不断增长。所提出的技术提供了对人体的分析，通过音频/视觉反馈和纠正指导来鼓励物理治疗患者的康复。和与护理提供者同步进展，而姿势分析和实时指导系统在运动过程中提供信心，目标是通过改善个性化康复的机会来促进更好的健康结果和提高生活质量，从而可能减少医疗保健差异和知识成本。该 I-Corps 项目基于物理康复软件工具的开发，旨在解决患者在物理治疗中独立进行的锻炼，目前，指挥官受到不具有可定制功能的家庭锻炼工具的限制。视觉分析系统使用推断该技术包括机器学习 (ML) 算法，可动态推断人体姿势洞察并根据需要提供纠正措施。通过从结果中学习并确定持续康复的参与技术来不断改进的学习方法，其目标是提供高精度的家庭支持，以补充身体康复并直接影响活动能力和治疗目标。 、纠正性辅导和综合进度跟踪，这可以显着提高家庭练习的有效性。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。