NRI: INT: COLLAB: Muscle Ultrasound Sensing for Intuitive Control of Robotic Leg Prostheses
NRI: INT: COLLAB: Muscle Ultrasound Sensing for Intuitive Control of Robotic Leg Prostheses
批准号:
1925371
负责人:
Tommaso Lenzi
金额:
$60.1万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2024-08-31
中文摘要
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英文摘要
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.
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DOI:
10.1109/tnsre.2023.3248647
发表时间:
2023-02
期刊:
IEEE Transactions on Neural Systems and Rehabilitation Engineering
影响因子:
4.9
作者:
[Joel Mendez;Rosemarie Murray;Lukas Gabert;Nicholas P. Fey;Honghai Liu;T. Lenzi]
通讯作者:
Joel Mendez;Rosemarie Murray;Lukas Gabert;Nicholas P. Fey;Honghai Liu;T. Lenzi
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.
Ambulation Mode Classification of Individuals with Transfemoral Amputation through A-Mode Sonomyography and Convolutional Neural Networks.
通过 A 模式超声检查和卷积神经网络对经股截肢患者的步行模式进行分类。
DOI:
10.3390/s22239350
发表时间:
2022-12-01
期刊:
Sensors (Basel, Switzerland)
影响因子:
--
作者:
[Murray R, Mendez J, Gabert L, Fey NP, Liu H, Lenzi T]
通讯作者:
Lenzi T
DOI:
10.1186/s12984-023-01177-w
发表时间:
2023-05-02
期刊:
JOURNAL OF NEUROENGINEERING AND REHABILITATION
影响因子:
5.1
作者:
[Hunt, Grace R., Hood, Sarah, Gabert, Lukas, Lenzi, Tommaso]
通讯作者:
Lenzi, Tommaso
CAREER: Bio-inspired Multi-joint Design and Control for Efficient and Lightweight Wearable Robots
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批准号:2046287
-
项目类别:Standard Grant
-
资助金额:$58.43万
-
财政年份:2021
-
负责人:Tommaso Lenzi
-
依托单位:
国内基金
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