User-friendly IMU-based Human Motion Measurement

提案：1805896中风、帕金森病和骨关节炎影响了大约15%的美国成年人，经常损害行走能力，导致严重健康状况的风险增加，生活质量下降。评估患者功能和提供康复处方的传统方法要求患者反复访问诊所，这对患者、临床医生和卫生保健系统来说既昂贵又耗时。理想情况下，当患者在家或在社区时，临床医生可以收集有关患者行走功能的定量信息，并提供康复处方。无线惯性测量单元（imu）是一种电子设备，它使用加速度计来测量直线加速度（沿着直线），使用陀螺仪来测量角速度（旋转），目前已经在探索提供这种功能。然而，将IMU测量值转换为关节角度测量值的现有计算算法（解决问题的说明）不足以支持基于IMU的运动测量系统，该系统提供准确的关节运动测量值，并且非常简单，患者，家庭成员或护理人员可以在没有技术专长的情况下可靠地使用它。该项目旨在开发一种新的计算算法来实现这些目标。该算法结合了几种独特的计算方法，达到了精确和简单的目的。拟议的项目将1)使用同时收集的预先存在的动作捕捉数据开发必要的计算算法，2)通过让10名健康受试者收集他们自己的基于imu的动作捕捉数据来评估算法的易用性和准确性，以及3)将算法部署在Windows平板电脑或Mac笔记本电脑上，以证明它可以用于实时反馈应用。如果取得成功，该项目可促进开发有效的远程监测和远程康复方法，从而减少临床医生的时间和患者就诊次数，降低医疗保健成本，提高治疗效果。为了推广，休斯敦一所中学的“危险”学生将通过互联网（Skype）与新西兰奥克兰一所姐妹中学的学生参加一年一度的“Jump Off”比赛，亲身体验这项技术。该项目的目标是开发一种无线用户友好的基于imu的运动测量系统，该系统非常简单易用，几乎任何患者或护理人员都可以使用它来测量家中或社区的全身步行运动，只需少量训练。这样的系统在临床上对使用记录数据的患者功能远程评估和使用实时反馈的康复处方远程交付都是有益的。该系统的核心是一种新的运动估计算法，可用于数据记录和实时应用。该算法只需要6个imu——每只脚、每只骨盆、每只躯干和每只手腕——就能轻松、重复地测量全身行走运动学。该项目将分三个阶段进行。第一阶段将涉及算法开发。该算法将是为研究现有平面6自由度行走模型而开发的无气味过滤器（UF）算法的扩展版本。第一个任务是通过添加更多坐标并将其扩展到3D，使该模型更加通用和灵活。该算法将使用实验步行数据和从代表现实条件的现有29自由度步行模型中获得的数据进行测试。第二阶段将涉及离线应用的算法评估。为了证明，只需最少的训练，任何环境中的个体都可以使用该算法收集自己的运动学步行数据，10名健康受试者将收集自己基于imu的步行数据，同时佩戴标记，以实现基于标记的同步运动捕捉，以验证结果。第三阶段将涉及实时应用程序的算法部署。将评估该算法在硬件上部署用于实时应用时的计算速度。将开发一种基于无线IMU的运动反馈系统，该系统由6个无线IMU和一个Windows（或Mac）平板电脑控制单元组成，该控制单元具有实时计算和显示行走过程中关节角度的软件。为了验证该系统是否符合项目的目标——易于使用、快速校准、实时收集和显示计算出的关节位置，另外3名受试者将在不佩戴标记的情况下进行实时数据收集。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

PI: Fregly, Benjamin J.Proposal: 1805896Stroke, Parkinson's disease, and osteoarthritis affect roughly 15% of the U.S. adult population and often impair walking ability, leading to an increased risk of serious health conditions and a decreased quality of life. Traditional approaches for assessing patient function and delivering rehabilitation prescriptions require that the patient make repeated visits to the clinic, which is expensive and time consuming for the patient, the clinician, and the health care system. Ideally, clinicians could gather quantitative information about patient walking function, as well as deliver rehabilitation prescriptions, when the patient is at home or in the community. Wireless inertial measurement units (IMUs), which are electronic devices that use accelerometers to measure linear acceleration (along a straight line) and gyroscopes to measure angular velocity (rotation), are already being explored to provide such capabilities. However, existing computational algorithms (problem solving instructions) that convert IMU measurements into joint angle measurements are inadequate to support an IMU-based motion measurement system that provides accurate joint motion measurements AND is so simple that patients, family members, or caregivers can use it reliably with no technical expertise. This project seeks to develop a novel computational algorithm that achieves these goals. The algorithm will achieve accuracy and simplicity by combining several unique computational approaches. The proposed project will 1) DEVELOP the necessary computational algorithm using preexisting motion capture data collected simultaneously, 2) EVALUATE the algorithm's ease of use and accuracy by having 10 healthy subjects collect their own IMU-based motion capture data, and 3) DEPLOY the algorithm on a Windows tablet or Mac laptop to demonstrate that it can be used for real-time feedback applications. If successful, this project could facilitate the development of effective remote monitoring and telerehabilitation methods that reduce the need for clinician time and patient office visits, decrease healthcare costs, and increase treatment effectiveness. For outreach, "at risk" students in a Houston middle school will interact with the technology firsthand by competing in an annual "Jump Off" competition held via the internet (Skype) with students in a sister middle school in Auckland, New Zealand.The goal of this project is to develop a wireless user-friendly IMU-based motion measurement system that is so simple and easy to use that virtually any patient or caregiver can use it to measure full-body walking movements at home or in the community with little training. Such a system could be clinically beneficial for both remote assessment of patient function using logged data and remote delivery of rehabilitation prescriptions using real-time feedback. The core of the stem is a novel motion estimation algorithm that will work for data logging and real-time applications. The algorithm will require only 6 IMUs-- each foot, pelvis, torso and each wrist--to measure full-body walking kinematics easily and repeatably. The project will progress in three phases. Phase 1 will involve algorithm development. The algorithm will be an expanded version of an unscented filter (UF) algorithm developed for studying an existing planar 6 DOF walking model. The first task will be to make that model more general and flexible by adding more coordinates and extending it to 3D. The algorithm will be tested using experimental walking data and data obtained from an existing 29 DOF walking model representative of real-life conditions. Phase 2 will involve algorithm evaluation for off-line applications. To demonstrate that, with minimum training, individuals in any environment can collect their own kinematic walking data using the algorithm, 10 healthy subjects will collect their own IMU-based walking data while also wearing markers to enable simultaneous marker-based motion capture to validate results. Phase 3 will involve algorithm deployment for real-time applications. The computational speed of the algorithm when deployed on hardware for real-time applications will be evaluated. A wireless IMU based motion feedback system, consisting of 6 wireless IMUs and a Windows (or Mac) tablet control unit with software for real-time calculation and display of joint angles during walking, will be developed. To verify that the system meets the project's goals --ease of use, rapid calibration, and collection and display of calculated joint positions in real time, 3 additional subjects will perform real-time data collection on themselves without wearing markers.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.