SBIR Phase II: 3D Markerless Motion Capture Technology For Gait Analysis

SBIR 第二阶段：用于步态分析的 3D 无标记运动捕捉技术

• 批准号: 2153138
• 负责人: Andrew Ekelem
• 金额: $ 99.86万
• 依托单位: EVOLUTION DEVICES, INC.
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2153138&HistoricalAwards=false
• 关键词: SBIR; Phase; II; 3D; Markerless

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project benefitd the 70 million people struggling with gait disorders in the US. Gait analysis monitors how individuals walk to predict or prevent injuries and track rehabilitation progress. Due to the potentially high equipment costs, space requirements, and required technical expertise to collect and interpret results, detailed gait analyses are limited to a few centers and mainly used for surgical decision-making. This project uses Artificial Intelligence (AI) for gait analysis at roughly 70% less than typical costs, as well as offering reduced set-up time and improved workflow efficiency.The proposed project will address the existing technological and commercial barriers that make gait analysis an exclusive clinical tool restricted to only 300 gait labs across the country. This project will develop a cost-effective markerless motion 3D-tracking system. Technical activities include: (1) increase the motion database to a diverse population, including children and patients with mobility impairments; (2) improve the computer vision algorithms to account for multiple individuals within the camera system’s field of view; (3) integrate EMG and Force Plates; (4) implement skeletal geometry estimation from computed tomography; (5) develop a self-calibration system that can operate with HD low cost cameras; and (5) improve accuracy and usability substantially to reduce the expertise required for computational gait analysis.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.

这项小型企业创新研究（SBIR）II期项目的更广泛的影响/商业潜力使美国有7000万人在美国挣扎着疾病。步态分析监视个人如何步行以预测或预防伤害并追踪康复进展。由于设备成本，空间需求以及收集和解释结果所需的技术专业知识的可能性高，详细的GIT分析仅限于几个中心，主要用于外科决策。该项目使用人工智能（AI）进行步态分析，比典型成本少70％，并提供减少的设置时间和提高的工作流程效率。拟议的项目将解决现有的技术和商业障碍，使步态分析成为全国仅300个步态实验室的独家临床工具。该项目将开发一个具有成本效益的无标记运动3D跟踪系统。技术活动包括：（1）将运动数据库增加到多样性人群，包括儿童和流动性障碍患者； （2）改进计算机视觉算法，以说明相机系统视野中的多个人； （3）集成的EMG和力板； （4）从计算机断层扫描中实现骨骼几何估计； （5）开发一个可以使用高清低成本相机运行的自校准系统； （5）提高准确性和可用性，以减少计算步态分析所需的专业知识。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响评估标准来评估，被认为是珍贵的支持。