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.

该PFI项目的更广泛的影响/商业潜力将通过使用新型可穿戴技术解决方案来提高美国公众的健康和福利。这种基于液体金属传感器的可穿戴设备旨在将人类运动评估从实验室环境转移到人们通常从事工作的地方：现实世界。该项目将创建一个负担得起的脚部可穿戴设备，以适当评估各种形状和尺寸的人的穿着者步态和腿对称性，而无需昂贵，笨重的设备或从业者的专业知识。此外，提出的工具是准确的，但也可以访问，这意味着这种能力可以通过在现实世界中的任务评估中通过适当的预后和诊断来改善生活质量以及医疗患者的诊断。该项目还可以通过提供评估行动措施的能力，例如对军事人员的步骤计数，加速和地面反作用力估算，帮助战术规划和识别肢体段受伤的识别，来支持美国国防。随着时间的流逝，关节将疲劳和未能识别这些压力源可能对战场产生严重影响，就像在实践法院或工业环境中一样。拟议的项目重新利用了软机器人传感器，以准确，非侵入性地捕获移动和迫使数据在脚部界的近乎实时捕获数据，以提供有意义的绩效和风险评估，以定制培训方案。这种可穿戴的解决方案是为了回应大学和专业水平的力量，调理教练和教练希望获得“从头开始”捕获运动数据的精确解决方案。拟议的解决方案将准确捕获实验室之外的踝运动学和动力学数据，从而为教练，培训师，医务人员提供研究，并研究大量以前无法获得现场从业者提供或信任的信息。智力优点包括：（a）扩展最先进的可穿戴解决方案，以测量绝对脚部轴角，（b）使用定制的液态金属传感器来测量足部力量，以及（c）将复杂角度和力量测量结合到机器学习系统中，以估算脚踝损伤风险，从而使实践者有效地监测重复的运动。项目目标是创建一个准确但负担得起的可穿戴系统，该系统可以识别出最常见的伤害脚踝菌株的潜在风险。大学学生运动员将用于设计验证，因为初始项目范围是为竞争性运动而设计的；但是，该解决方案将可以扩展到工业和军事重复动议。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。

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

Wearable Stretch Sensors for Human Movement Monitoring and Fall Detection in Ergonomics

• DOI: 10.3390/ijerph17103554
• 发表时间: 2020-05-01
• 期刊: INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
• 作者: Chander, Harish;Burch, Reuben F.;Prabhu, Raj K.
• 通讯作者: Prabhu, Raj K.

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

In Silico Finite Element Analysis of the Foot Ankle Complex Biomechanics: A Literature Review

• DOI: 10.1115/1.4050667
• 发表时间: 2021-09-01
• 期刊: JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME
• 影响因子: 1.7
• 作者: Phan, P. K.;Vo, A. T. N.;Prabhu, R. K.
• 通讯作者: Prabhu, R. K.