PFI-RP: From the Ground Up: Using Soft Robotic Sensors to Create a Foot and Ankle Wearable that Accurately Captures Real-time, Kinematic and Kinetic Data During Athletic Training

PFI-RP：从头开始：使用软机器人传感器创建足部和脚踝可穿戴设备，可在运动训练期间准确捕获实时、运动学和动力学数据

• 批准号: 1827652
• 负责人: Reuben Burch
• 金额: $ 74.99万
• 依托单位: Mississippi State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1827652&HistoricalAwards=false
• 关键词: PFI; RP; Ground; Up; Using

The broader impact/commercial potential of this PFI project will advance the health and welfare of the American public by using a new type of wearable technology solution. This liquid metal sensors-based wearable is designed to move human movement evaluation from laboratory environments to where people normally perform work: the real world. This project will create an affordable foot-ankle wearable to properly assess wearer gait and leg symmetry for people of all shapes and sizes without requiring expensive, bulky equipment or a practitioner's expertise. Moreover, the proposed tool is accurate, yet is also accessible meaning that this capability could improve quality of life via proper prognosis and diagnosis within competitive athletics as well as for medical patients during real-world task assessments. This project can also be used to support the national defense of the United States by providing the ability to assess movement measures, such as step count, acceleration, and ground reaction force estimation of military personnel, aiding in tactical planning and identification of oncoming injuries to limb segments. Over time, joints will fatigue and failure to identify these stressors can have a severe impact on the battlefield just as in the practice courts or industrial environments. The proposed project repurposes soft robotic sensors to accurately and noninvasively capture movement and force data in near real-time at the foot-ankle to provide meaningful performance and risk assessment for tailoring training regimens. This wearable solution is in response to collegiate and professional-level strength and conditioning coaches and trainers desire for a precise solution that captures movement data "from the ground up". The proposed solution will accurately capture ankle kinematic and kinetic data outside of the lab, giving coaches, trainers, medical staff, and researches a wealth of information that was previously not available or trusted by field practitioners. Intellectual merits include: (a) expanding state-of-the-art wearable solutions to measure absolute foot-ankle angles, (b) using custom liquid metal sensors to measure foot forces, and (c) combining complex angle and force measurements into machine learning systems estimating ankle injury risk thereby allowing practitioners to effectively monitor repetitive movements. The project goal is to create an accurate yet affordable wearable system that can identify potential risks of the most common injury, ankle strain. Collegiate student athletes will be used for design validation as initial project scope is designed for competitive sports; however, the solution will be expandable to industrial and military repetitive motions.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.

这个PFI项目的广泛影响/商业潜力将通过使用一种新型的可穿戴技术解决方案来促进美国公众的健康和福利。这种基于液态金属传感器的可穿戴设备旨在将人体运动评估从实验室环境转移到人们通常工作的地方：现实世界。该项目将创造一种价格合理的脚踝穿戴设备，以正确评估佩戴者的步态和腿部对称性，适合各种体型和大小的人，而不需要昂贵、笨重的设备或从业者的专业知识。此外，所提出的工具是准确的，但也是可访问的，这意味着这种能力可以通过在竞技运动中以及在现实世界的任务评估中对医疗患者进行适当的预后和诊断来提高生活质量。该项目还可以通过提供评估运动措施的能力来支持美国的国防，例如步数、加速度和军事人员的地面反作用力估计，帮助战术规划和识别即将到来的肢体损伤。随着时间的推移，关节会疲劳，无法识别这些压力源会对战场产生严重影响，就像在练习法庭或工业环境中一样。拟议中的项目重新利用软机器人传感器，精确、无创地捕捉足踝部近实时的运动和力量数据，为定制训练方案提供有意义的性能和风险评估。这种可穿戴解决方案是为了满足大学和专业水平的力量和体能教练和训练师对精确解决方案的需求，这种解决方案可以“从头开始”捕获运动数据。所提出的解决方案将在实验室之外准确捕获踝关节的运动学和动力学数据，为教练、训练员、医务人员和研究人员提供丰富的信息，这些信息以前是现场从业人员无法获得或信任的。智力优势包括：(a)扩展了最先进的可穿戴解决方案，以测量脚-脚踝的绝对角度；(b)使用定制液态金属传感器来测量足部力；(c)将复杂的角度和力测量结合到机器学习系统中，估计脚踝损伤风险，从而使从业者能够有效地监测重复运动。该项目的目标是创造一种准确且价格合理的可穿戴系统，可以识别最常见的伤害，脚踝拉伤的潜在风险。由于初始项目范围为竞技体育，将使用大学生运动员进行设计验证；然而，该解决方案将扩展到工业和军事重复运动。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。

项目成果

Closing the Wearable Gap-Part VII: A Retrospective of Stretch Sensor Tool Kit Development for Benchmark Testing

• DOI: 10.3390/electronics9091457
• 发表时间: 2020-09
• 期刊: Electronics
• 影响因子: 2.9
• 作者: Purva Talegaonkar;D. Saucier;Will Carroll;Preston Peranich;Erin Parker;Carver Middleton;Samaneh Davarza

Deterioration of textile vs. electronic components over time in athletic wearable devices

运动可穿戴设备中纺织品与电子元件随着时间的推移而劣化

• DOI: 10.1117/12.2587975
• 发表时间: 2021
• 期刊: Smart Biomedical and Physiological Sensor Technology XVIII
• 作者: Parker, Erin;Freeman, Charles;Persons, Karen;Burch, Reuben;Ball, John E.;Saucier, David;Middleton, Carver;Peranich, Preston;Chander, Harish;Knight, Adam
• 通讯作者: Knight, Adam

Closing the Wearable Gap: Foot–ankle kinematic modeling via deep learning models based on a smart sock wearable

• DOI: 10.1017/wtc.2023.3
• 发表时间: 2023-02
• 期刊: Wearable Technologies
• 作者: Samaneh Davarzani;D. Saucier;Purva Talegaonkar;Erin Parker;Alana Turner;Carver Middleton;William O. Carroll;J. Ball;A. Gurbuz;H. Chander;Reuben F. Burch;Brian K. Smith;A. Knight;Charles E. Freeman

Incorporation of a smart sock with the virtual immersive test for postural stability

将智能袜子与虚拟沉浸式姿势稳定性测试相结合

• 发表时间: 2023
• 期刊: The American Journal of the Medical Sciences 2023 Southern Regional Meeting
• 作者: Burch, RF;Chander, H;Saucier, D;Ball, J
• 通讯作者: Ball, J

Electromechanical Fatigue Properties of Dielectric Elastomer Capacitive Sensors Based on Plantarflexion of the Human Ankle Joint

• DOI: 10.1149/2754-2726/acb21e
• 发表时间: 2023-01
• 期刊: ECS Sensors Plus
• 作者: A. Persons;Carver Middleton;Erin Parker;J. Ball;R. Burch V.;David Macias;C. L. Simpson;S. Elder