Measure: Biomechanics via Wearable Sensors

测量：通过可穿戴传感器进行生物力学

• 批准号: 10581470
• 负责人: SCOTT L DELP
• 金额: $ 31.26万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-04 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10581470
• 关键词: Acceleration; Address; Affect; Algorithms; Anthropometry; Behavioral Model; Binding; Biomechanics; Biomedical Research; Biomedical Technology; Cellular Phone; Cerebral Palsy; Characteristics; Clinic; Clinical; Communities; Complex; Computer software; Data; Degenerative polyarthritis; Diagnosis; Disease; Energy consumption; Equipment; Exercise; Foundations; Future; Gait; Goals; Human; Image; Individual; Joints; Kinetics; Knee; Leadership; Length; Locomotion; Magnetic Resonance Imaging; Measurement; Measures; Metabolic; Modeling; Monitor; Motion; Movement; Movement Disorders; Muscle; Muscle Fibers; Musculoskeletal; Obesity; Operative Surgical Procedures; Optics; Osteoporosis; Parkinson Disease; Pathologic; Patients; Persons; Publications; Records; Rehabilitation Outcome; Rehabilitation therapy; Research; Research Personnel; Resources; Risk; Series; Services; Skeletal system; System; Tendon structure; Time; Upper Extremity; Work; adduct; biomechanical model; biomechanical test; cost; crouch gait; data-driven model; design; experience; foot; functional improvement; health goals; improved; improved mobility; individualized medicine; innovation; insight; joint loading; kinematics; machine learning method; machine learning model; mobile sensing; mobile sensor; multidimensional data; muscular system; neural; open source; pressure; robot assistance; robot rehabilitation; sensor; sensor technology; skills; societal costs; success; terabyte; tool; treatment planning; wearable sensor technology; wireless

Limited mobility due to conditions like osteoarthritis (OA), cerebral palsy, and Parkinson’s disease affects millions of individuals, at enormous personal and societal cost. Rehabilitation can dramatically improve mobility and function, but current rehabilitation practice requires in-person guidance by a skilled clinician, increasing expense and limiting access. Mobile sensing technologies are now ubiquitous and have the potential to measure patient function and guide treatment outside the clinic, but they currently fail to capture the characteristics of motion required to accurately monitor function and customize treatment. Millions of low-cost mobile sensors are generating terabytes of data that could be analyzed in combination with other data, such as images, clinical records, and video, to enable studies of unprecedented scale, but machine learning models for analyzing these large-scale, heterogeneous, time-varying data are lacking. To address these challenges, we will establish a Biomedical Technology Resource Center —The Mobilize Center. Through the leadership of an experienced scientific team, we will create and disseminate innovative tools to quantify movement biomechanics with mobile sensors. Specifically, we will: 1. Push the bounds of what we can measure via wearable sensors using models that compute muscle and joint forces and metabolic cost of locomotion. These models, based on biomechanical and machine learning models, will be disseminated via our newly created OpenSense software, which will be used by thousands of researchers to gain new insights into patient biomechanics using mobile sensors. 2. Meet the need for tools that analyze data about movement dynamics and develop machine learning models to analyze and generate insights from unstructured, high-dimensional data, including time- series (e.g., from mobile sensors), images (e.g., MRI), and video (e.g., smartphone video of a patient’s gait). 3. Provide tools needed to intervene in the real-world. We will develop algorithms to accurately quantify kinematics outside the lab for long durations using data from inertial measurement units (IMUs). We will also build behavioral models to adapt and personalize goal setting, drawing on movement records from 6 million individuals, as well as health goals and exercise for 1.7 million people. Through intensive interactions with our Collaborative Projects, we will focus on improving rehabilitation outcomes for individuals with limited mobility due to osteoarthritis, obesity, Parkinson’s disease, and cerebral palsy. The Center’s tools and services will enable researchers to revolutionize how we diagnose, monitor, and treat mobility disorders, providing tools needed to deliver precision rehabilitation at low cost and on a massive scale in the future.

诸如骨关节炎（OA），脑瘫和帕金森氏病等状况的流动性有限 数百万个人，以巨大的个人和社会成本。康复可以极大地改善活动能力 和功能，但是目前的康复实践需要熟练的临床指导，增加 费用和限制访问。移动传感器技术现在无处不在，有可能 测量患者功能和指导诊所外的治疗，但目前未能捕获 精确监控功能和自定义治疗所需的运动特征。数百万的低成本 移动传感器正在生成可与其他数据相结合分析的数据的tobytes 图像，临床记录和视频，以实现前所未有的规模研究，但机器学习模型 缺乏分析这些大规模，异质，时变的数据。 为了应对这些挑战，我们将建立一个生物医学技术资源中心 - 动员 中心。通过经验丰富的科学团队的领导，我们将创建和传播创新 用移动传感器量化运动生物力学的工具。 具体来说，我们将： 1。使用计算肌肉的型号来推动我们可以通过可穿戴传感器测量的边界 和运动的联合力量和代谢成本。这些模型，基于生物力学和机器 学习模型将通过我们新创建的OpenSense软件传播，将被使用 成千上万的研究人员使用移动传感器获得了对患者生物力学的新见解。 2.满足对分析有关运动动态数据和开发机器学习数据的工具的需求 分析和生成来自非结构化的高维数据的洞察力的模型，包括时间 系列（例如，来自移动传感器），图像（例如MRI）和视频（例如，患者的智能手机视频 步态）。 3。提供干预现实世界所需的工具。我们将开发算法以准确量化 实验室外部的运动学长期使用惯性测量单元（IMU）的数据。我们将 还建立行为模型以适应和个性化目标设定，利用运动记录 600万个人以及170万人的健康目标和锻炼。 通过与我们的协作项目进行密集的互动，我们将专注于改善康复 由于骨关节炎，肥胖，帕金森氏病和大脑而导致流动性有限的人的结果 麻痹。该中心的工具和服务将使研究人员能够彻底改变我们的诊断，监测和 治疗移动性障碍，提供以低成本和大量提供精确康复所需的工具 将来扩展。