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NRI: INT: COLLAB: Muscle Ultrasound Sensing for Intuitive Control of Robotic Leg Prostheses

NRI：INT：COLLAB：用于机器人假肢直观控制的肌肉超声传感

基本信息

批准号：
2054343
负责人：
Nicholas Fey
金额：
$ 57.82万
依托单位：
University of Texas at Austin
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2024-10-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2054343&HistoricalAwards=false
关键词：
NRI INT COLLAB Muscle Ultrasound

项目摘要

The research objective of this project is to enable volitional control over lower-limb prostheses through the integration of sonomyographic sensing - the ultrasound imaging of amputated (i.e., residual) limb muscle morphology - to control the Utah Lightweight Leg. This powered prosthetic leg is comprised of powered ankle and knee modules, and is roughly half the weight of contemporary technologies. The project team will use sonomyographic sensors in combination with mechanical sensors to infer the user's intent in anticipation of ambulation mode or joint motion, for example locomotor transitions from walking over level ground to ramps or stairs. The team will then perform human subject experiments comparing the ability of participants with transfemoral amputation to ambulate with and without various sonomyographic control algorithms enabled. If successful, the project will have positive impact on national health and welfare by improving the lives of individuals with amputation in terms of their independence and ambulation abilities, and by mitigating undesirable secondary effects of amputation such as a fear of falling and long-term joint health. Additional broader impacts of the work include enhanced undergraduate and graduate research experiences for veterans and underrepresented minorities, as well as outreach activities to K-12 students.Robotic leg prostheses can overcome the limitations of conventional passive prostheses by generating net-positive energy during the gait cycle and actively regulating joint motion. However, scientific barriers must be overcome for robotic leg prosthesis to safely and effectively operate in real-world settings. The goal of this project is to fill the knowledge gap regarding the integration of the user's volition in the control of lightweight robotic ankle and knee prostheses. The research team will measure muscle contractions of the user's residual limb using wearable ultrasound probes. Specific objectives of this project are: 1) to identify optimal design guidelines to integrate sonomyographic sensing into state-of-the-art powered knee-ankle prostheses; 2) to determine specific algorithms that best anticipate the user's intention to perform different ambulation modes in a timely, accurate, and reliable manner; and 3) to understand how to optimally combine information gathered from sonomyography and mechanical sensors to control a robotic leg prosthesis within specific ambulation modes. Algorithms will be implemented on a lightweight robotic ankle and knee prosthesis to evaluate the hypothesis that providing users with anticipatory volitional control will lead to enhanced performance in complex and uncertain environments, thereby fostering seamless integration of robotic prostheses with human users.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.

该项目的研究目标是通过集成声学传感--截肢(即残肢)肌肉形态的超声成像--来控制犹他州的轻量级腿部，从而实现对下肢假体的意志控制。这种电动假肢由电动脚踝和膝盖模块组成，重量大约是当代技术的一半。项目团队将使用声学传感器与机械传感器相结合来推断用户在预期行走模式或关节运动时的意图，例如从平地步行到坡道或楼梯的运动过渡。然后，该团队将进行人体受试者实验，比较在启用和不启用各种声学控制算法的情况下，经股截肢的参与者行走的能力。如果成功，该项目将对国家健康和福利产生积极影响，因为它将改善截肢者的生活，改善他们的独立和行走能力，并减轻截肢的不良次要影响，如对跌倒的恐惧和长期的关节健康。这项工作的其他更广泛的影响包括增强退伍军人和代表性不足的少数民族的本科生和研究生的研究经验，以及面向K-12学生的外联活动。机械腿假肢可以通过在步态周期中产生净正能量并积极调节关节运动来克服传统被动假肢的局限性。然而，必须克服科学障碍，才能使机械腿假肢在现实世界中安全有效地运作。该项目的目标是填补在轻型机器人踝关节和膝关节假体控制中整合用户意志的知识空白。研究小组将使用可穿戴式超声波探头测量使用者残肢的肌肉收缩。该项目的具体目标是：1)确定最佳设计指南，将声学传感集成到最先进的动力型膝关节-踝关节假体中；2)确定最能预测用户意图的特定算法，以及时、准确和可靠地执行不同的行走模式；以及3)了解如何以最佳方式结合从声学和机械传感器收集的信息，以在特定的行走模式下控制机械腿假肢。算法将在轻量级机器人踝关节和膝关节假体上实施，以评估为用户提供预期意志控制将导致在复杂和不确定环境中增强性能的假设，从而促进机器人假肢与人类用户的无缝集成。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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

期刊论文数量（18）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Relating Underlying Performance Objectives of Overground Walking to Observable Walking Mechanics using Predictive Musculoskeletal Simulations

使用预测性肌肉骨骼模拟将地面步行的基本性能目标与可观察的步行力学联系起来

DOI：
10.1109/icorr55369.2022.9896553
发表时间：
2022
期刊：
IEEE
影响因子：
0
作者：
Li, Wentao;Fey, Nicholas P.
通讯作者：
Fey, Nicholas P.

Modeling the Influence of the Human Form and Ambulation Context on Moment- and Power-Generating Abilities of Soft Hip-Flexion Exosuits

模拟人体形态和行走环境对软髋屈曲外装套装的力矩和发电能力的影响

DOI：
10.1109/icorr55369.2022.9896601
发表时间：
2022
期刊：
IEEE
影响因子：
0
作者：
Neuman, Ross M.;Fey, Nicholas P.
通讯作者：
Fey, Nicholas P.

Continuous Prediction of Leg Kinematics During Ambulation using Peripheral Sensing of Muscle Activity and Morphology

使用肌肉活动和形态的外周传感连续预测行走过程中的腿部运动学

DOI：
10.1109/ismr48346.2021.9661485
发表时间：
2021
期刊：
IEEE
影响因子：
0
作者：
Rabe, Kaitlin G.;Fey, Nicholas P.
通讯作者：
Fey, Nicholas P.

Use of Sonomyographic Sensing to Estimate Knee Angular Velocity During Varying Modes of Ambulation*

DOI：
10.1109/embc44109.2020.9176674
发表时间：
2020-07
期刊：
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
影响因子：
0
作者：
Kaitlin G. Rabe;M. H. Jahanandish;K. Hoyt;Nicholas P. Fey
通讯作者：
Kaitlin G. Rabe;M. H. Jahanandish;K. Hoyt;Nicholas P. Fey

Performance of Sonomyographic and Electromyographic Sensing for Continuous Estimation of Joint Torque During Ambulation on Multiple Terrains

用于在多地形上行走期间连续估计关节扭矩的声肌图和肌电图传感性能