Miqus hybrid video cameras to integrate markerless motion tracking into a state-of-art motion analysis laboratory

Miqus 混合摄像机将无标记运动跟踪集成到最先进的运动分析实验室

• 批准号: RTI-2023-00269
• 负责人: Burkhart, Timothy
• 金额: $ 8.17万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Research Tools and Instruments
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=757863
• 关键词: Miqus; hybrid; video; cameras; integrate

The technology and equipment requested in the current RTI grant is necessary to support and enhance two NSERC Discovery Grant projects: "Contributions of lower extremity musculature to hip and knee joint co-ordination, stability, and regional tissue mechanics" (Dr. Timothy Burkhart [PI]); and, "The planning and control of movements in social contexts" (Dr. Timothy Welsh [Co-I]). A Miqus hybrid camera system, composed of eight cameras, Manfrotto Tripods, a designated computer and accessories, is needed to quantify the fundamental mechanisms of human motion and coordination. People rely on joint stability, coordination, and motor learning to move around in their daily lives. But there are relationships between the motions of the different joints and complex nervous and muscle system conditions that affect motion. To solve this problem, motion data, force data, and muscle activation patterns have to be collected and analyzed accurately. Recent advances in artificial intelligence have led to the development of markerless motion tracking systems, that are less time consuming and more portable than traditional motion analysis methods. We need to acquire a special set of cameras to allow for synchronization with force, electromyography (EMG), and other data types. The research objectives include: Objective 1- quantify the individual muscle contributions to knee and hip joint motion and stability: Motion profiles will be collected synchronously with six-degree-of-freedom force plate and multi-muscle EMG in response to a variety of tasks. In addition to quantifying joint coupling and function curves, the individual muscle contributions to joint stability and kinematics will be calculated. The data will be integrated into a validated musculoskeletal model to calculate the muscle forces. Objective 2- Understand the processes underlying the prediction of the actions of a co-actor. The requested technology will enable the integration of eye-tracking data and will eliminate concerns of volume and line-of-sight to allow expanded investigations of action coordination and related phenomena (including procrastination in joint action) using full body tasks involving walking. The primary purpose of this researc is to provide a more thorough and inclusive understanding of the underlying mechanisms of human motion. This work is essential to identifying strategies to reduce the risk of injury and musculoskeletal disease in Canada and improve activity performance. Our long-term vision is that this information will be used to develop more effective injury reduction, treatment, and rehabilitation strategies, that will improve quality life of the general Canadian population and will result in reduced health-care costs.

当前 RTI 拨款中要求的技术和设备对于支持和加强两个 NSERC 发现拨款项目是必要的：“下肢肌肉组织对髋关节和膝关节协调、稳定性和区域组织力学的贡献”（Timothy Burkhart 博士 [ PI]）；以及“社会环境中运动的规划和控制”（Timothy Welsh 博士 [Co-I]）。 Miqus 混合相机系统由八个相机、曼富图三脚架、指定计算机和配件组成，需要量化人体运动和协调的基本机制。人们在日常生活中依靠关节稳定性、协调性和运动学习来移动。但不同关节的运动与影响运动的复杂神经和肌肉系统条件之间存在着关系。为了解决这个问题，必须准确地收集和分析运动数据、力数据和肌肉激活模式。人工智能的最新进展促进了无标记运动跟踪系统的发展，该系统比传统的运动分析方法耗时更少且更便携。我们需要获取一组特殊的相机，以实现与力、肌电图 (EMG) 和其他数据类型的同步。 研究目标包括： 目标 1 - 量化个体肌肉对膝关节和髋关节运动和稳定性的贡献：将使用六自由度测力台和多肌肉肌电图同步收集运动曲线，以响应各种任务。除了量化关节耦合和功能曲线之外，还将计算个体肌肉对关节稳定性和运动学的贡献。这些数据将被整合到经过验证的肌肉骨骼模型中以计算肌肉力量。目标 2 - 了解预测共同参与者行为的基本过程。所需的技术将能够整合眼球追踪数据，并消除对体积和视线的担忧，以便利用涉及步行的全身任务来扩大对行动协调和相关现象（包括联合行动中的拖延）的调查。这项研究的主要目的是提供对人体运动的基本机制的更彻底和更包容的理解。这项工作对于确定降低加拿大受伤和肌肉骨骼疾病风险并提高活动表现的策略至关重要。我们的长期愿景是，这些信息将用于制定更有效的减少伤害、治疗和康复策略，从而提高加拿大普通民众的生活质量，并降低医疗保健成本。