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.

该项目的研究目的是通过整合了体力学传感的整合 - 截肢（即残留）肢体肌肉形态的超声成像来实现对下limb假体的自愿控制 - 控制犹他州轻量级腿。这款动力的假肢腿由动力的脚踝和膝盖模块组成，大约是当代技术的一半。该项目团队将使用机械传感器结合使用Sonomography传感器来推断用户在预期行动模式或关节运动方面的意图，例如从行走上走到水平地面到坡道或楼梯的运动过渡。然后，该团队将进行人类主题实验，以比较具有跨性截肢的参与者在有和没有各种体力学控制算法的情况下移动的能力。如果成功的话，该项目将通过改善截肢和行动能力截肢的人的生活以及减轻截肢的不良次要影响，例如害怕落下和长期联合健康的不良次要影响，从而对国家卫生和福利产生积极影响。这项工作的其他更广泛的影响包括为退伍军人和代表性不足的少数群体增强的本科生和研究生研究经验，以及向K-12学生提供的外展活动。动物腿前提可以克服传统的被动假体的局限性，通过在GAIT周期中产生净阳性能量的局限性，并在GAIT周期中产生净阳性。但是，机器人腿假体必须克服科学障碍，以在现实环境中安全有效地运行。该项目的目的是填补有关用户意志在控制轻型机器人踝关节和膝盖假体中的知识差距。研究团队将使用可穿戴超声探针测量用户残留肢体的肌肉收缩。该项目的具体目标是：1）确定最佳设计指南，以将声学摄影的传感整合到最先进的膝盖障碍假肢中； 2）确定特定算法，这些算法可以最好地预期用户及时，准确和可靠的方式执行不同的行动模式； 3）了解如何最佳地组合从系统学和机械传感器中收集的信息，以控制特定的行动模式中的机器人腿假体。算法将在轻巧的机器人脚踝和膝盖假体上实施，以评估以下假设，即为用户提供预期的自愿控制，将导致在复杂和不确定的环境中提高性能，从而促进了与人类的依据，从而促进了NSF的构建范围，从而促进了无缝的机器人假设的依据。标准。

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）

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

DOI：
10.1109/tnsre.2021.3134189
发表时间：
2021
期刊：
IEEE Transactions on Neural Systems and Rehabilitation Engineering
影响因子：
4.9
作者：
Rabe, Kaitlin G.;Lenzi, Tommaso;Fey, Nicholas P.
通讯作者：
Fey, Nicholas P.

Ultrasound-Derived Features of Muscle Architecture Provide Unique Temporal Characterization of Volitional Knee Motion

DOI：
10.1109/embc46164.2021.9630650
发表时间：
2021-11
期刊：
2021 43rd 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;Nicholas P. Fey
通讯作者：
Kaitlin G. Rabe;M. H. Jahanandish;Nicholas P. Fey