CAREER: Neuromechanics of human-robot interaction via robot-assisted in-vivo imaging of neuromuscular function
职业:通过机器人辅助神经肌肉功能体内成像研究人机交互的神经力学
基本信息
- 批准号:1943712
- 负责人:
- 金额:$ 50万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-01-15 至 2024-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Robots are used more and more to support human motor function in neurorehabilitation, performance augmentation, robot-assisted manufacturing, and powered prosthetics. While improvement in technological capabilities has been impressive during the last 20 years, progress has been limited by poor fundamental understanding of the human component during human-robot-assisted motor function. This CAREER project will address this limitation by noninvasively measuring brain function and muscle force and stiffness while a subject interacts with a robot to perform wrist tasks within a magnetic resonance scanner. This framework will be used to study how neuromotor impairment affects muscle coordination, paving the way for refined neuromusculoskeletal models of robot-assisted motor function and for personalized human-robot interaction strategies for performance augmentation and neurorehabilitation. This project will provide training for graduate and undergraduate students in problems at the intersection between biomechanics, neuroscience, and robotics, helping create a multidisciplinary workforce ready to tackle the complex challenges of rehabilitation engineering research in both academia and industry. The computational model developed will form the basis of a new outreach program that introduces gaming within the context of neuromuscular modeling, which will be administered to middle and high school students to raise interest in pursuing STEM education.The investigator’s long-term research goal is to develop novel neuroscience-grounded interventions for movement rehabilitation after neuromotor disorders. Toward this goal, the investigator’s current research is focused on 1) developing and validating robotic technologies for human assistance and rehabilitation and on 2) using such novel technologies in experimental studies modeling the healthy and impaired human motor control. This CAREER project seeks to use MRI-compatible robots to non-invasively measure brain function via functional magnetic resonance imaging (fMRI) and muscle function via magnetic resonance elastography(MRE) during motor tasks that require subjects to perform dynamic point-to-point and isometric wrist tasks in an MR scanner. Combining neuromechanical modeling with advanced experimental methods and with hypothesis-driven experiments, this framework will be used to quantify how the intrinsic neuromuscular dynamics of the human body affect physical human-interaction and to study optimal control policies for human-robot interaction in the presence of realistic neuromuscular dynamics. The project builds on the investigator’s success in developing a family of MRI-compatible robotic devices and a multi-muscle magnetic resonance elastography (MM-MRE) imaging technique for identifying fundamental criteria of muscle-coordination. The research plan is divided into two thrusts. The FIRST thrust focuses on studying the neural mechanisms underscoring force and impedance control using a multifaceted approach that combines modeling, behavioral experiments, and neuroimaging. A computational framework will be developed for analyzing force and impedance control for wrist pointing movements that includes accurate musculoskeletal dynamics. This framework will be validated in experiments conducted on healthy subjects that learn to control force or impedance in stable or unstable tasks. Brain regions involved in learning to generate proper force and impedance required for task execution will be identified. A neuroimaging experiment that uses fMRI and an MRI-compatible wrist robot will be used to test hypotheses on the neural representation of force and impedance during dynamic tasks, specifically that "force and impedance are controlled in different cortical regions" and that "the representation of muscle co-activation overlaps with the representation of the fast learning state." The SECOND thrust focuses on using MM-MRE to estimate the mechanical properties of multiple muscles in the forearm. The new technique integrates muscle-specific MRE measurements with measurements of joint torque obtained via an MRI-compatible instrumented handle. This technique will be used to identify criteria of muscle coordination that apply for tasks of the hand and wrist and to quantify how these criteria change in post-stroke individuals. Based on the unique measurements obtained, the currently accepted short-range stiffness model, not yet directly validated in-vivo and in-humans, will be tested using robotic perturbations applied by a high power MRI-compatible robot.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.
在神经康复、性能增强、机器人辅助制造和动力假肢等领域,机器人越来越多地用于支持人类运动功能。虽然在过去的20年里,技术能力的进步令人印象深刻,但由于对人-机器人辅助运动功能中人类成分的基本理解不足,进步受到限制。这个CAREER项目将通过无创测量大脑功能、肌肉力量和刚度来解决这一限制,同时受试者在磁共振扫描仪内与机器人互动,执行手腕任务。该框架将用于研究神经运动损伤如何影响肌肉协调,为机器人辅助运动功能的精细神经肌肉骨骼模型以及性能增强和神经康复的个性化人机交互策略铺平道路。该项目将为研究生和本科生提供生物力学、神经科学和机器人交叉问题的培训,帮助培养一支多学科的劳动力队伍,以应对学术界和工业界康复工程研究的复杂挑战。开发的计算模型将构成一个新的推广计划的基础,该计划将在神经肌肉建模的背景下引入游戏,该计划将对初高中学生进行管理,以提高他们追求STEM教育的兴趣。研究者的长期研究目标是开发新的基于神经科学的干预措施,用于神经运动障碍后的运动康复。为了实现这一目标,研究者目前的研究重点是:1)开发和验证用于人类辅助和康复的机器人技术;2)在实验研究中使用这些新技术来模拟健康和受损的人类运动控制。这个CAREER项目寻求使用mri兼容机器人在运动任务中通过功能性磁共振成像(fMRI)和磁共振弹性成像(MRE)非侵入性测量大脑功能,这些任务需要受试者在MR扫描仪中执行动态点对点和等距手腕任务。将神经力学建模与先进的实验方法和假设驱动的实验相结合,该框架将用于量化人体内在神经肌肉动力学如何影响物理人机交互,并在现实神经肌肉动力学的存在下研究人机交互的最优控制策略。该项目建立在研究者成功开发一系列mri兼容机器人设备和用于识别肌肉协调基本标准的多肌肉磁共振弹性成像(MM-MRE)成像技术的基础上。研究计划分为两个重点。FIRST重点研究神经机制,强调力和阻抗控制,采用多方面的方法,结合建模、行为实验和神经成像。将开发一个计算框架,用于分析手腕指向运动的力和阻抗控制,包括精确的肌肉骨骼动力学。这一框架将在健康受试者身上进行的实验中得到验证,这些受试者将学习在稳定或不稳定的任务中控制力或阻抗。大脑区域参与学习产生适当的力量和阻抗所需的任务执行将被确定。一项使用fMRI和兼容mri的手腕机器人的神经成像实验将用于测试动态任务中力和阻抗的神经表征的假设,特别是“力和阻抗在不同的皮层区域受到控制”以及“肌肉共同激活的表征与快速学习状态的表征重叠”。第二个重点是使用MM-MRE来估计前臂多块肌肉的力学特性。这项新技术将肌肉特定的MRE测量与通过mri兼容的仪器手柄获得的关节扭矩测量相结合。这项技术将用于确定适用于手和手腕任务的肌肉协调标准,并量化这些标准在中风后个体中的变化。基于获得的独特测量结果,目前接受的短距离刚度模型尚未直接在体内和人体中验证,将使用高功率mri兼容机器人施加的机器人扰动进行测试。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
期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Kinematic Compatibility of a Wrist Robot With Cable Differential Actuation: Effects of Misalignment Compensation via Passive Joints
具有电缆差速驱动的腕式机器人的运动兼容性:通过被动关节进行不对中补偿的效果
- DOI:10.1109/tmrb.2021.3123528
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Chishty, Haider A.;Zonnino, Andrea;Farrens, Andria J.;Sergi, Fabrizio
- 通讯作者:Sergi, Fabrizio
Characterizing adaptive behavior of the wrist during lateral force perturbations
表征横向力扰动期间手腕的自适应行为
- DOI:10.1109/biorob49111.2020.9224280
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Farrens, Andria J.;Sergi, Fabrizio
- 通讯作者:Sergi, Fabrizio
Individual Muscle Force Estimation in the Human Forearm Using Multi-Muscle MR Elastography (MM-MRE)
使用多肌肉 MR 弹性成像 (MM-MRE) 估计人体前臂的个体肌肉力量
- DOI:10.1109/tbme.2023.3283185
- 发表时间:2023
- 期刊:
- 影响因子:4.6
- 作者:Smith, Daniel R.;Helm, Cody A.;Zonnino, Andrea;McGarry, Matthew D.J.;Johnson, Curtis L.;Sergi, Fabrizio
- 通讯作者:Sergi, Fabrizio
Changes in Resting State Functional Connectivity Associated with Dynamic Adaptation of Wrist Movements
与手腕运动动态适应相关的静息状态功能连接的变化
- DOI:10.1523/jneurosci.1916-22.2023
- 发表时间:2023
- 期刊:
- 影响因子:0
- 作者:Farrens, Andria J.;Vahdat, Shahabeddin;Sergi, Fabrizio
- 通讯作者:Sergi, Fabrizio
Concurrent Contribution of Co-Contraction to Error Reduction During Dynamic Adaptation of the Wrist
手腕动态适应期间共同收缩对减少误差的同时贡献
- DOI:10.1109/tnsre.2023.3242601
- 发表时间:2023
- 期刊:
- 影响因子:4.9
- 作者:Farrens, Andria J.;Schmidt, Kristin;Cohen, Hannah;Sergi, Fabrizio
- 通讯作者:Sergi, Fabrizio
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Fabrizio Sergi其他文献
Inhibitory Effect of Subthreshold TMS on the Long-Latency Response in the Flexor Carpi Radialis
阈下 TMS 对桡侧腕屈肌长潜伏期反应的抑制作用
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Cody A. Helm;Fabrizio Sergi - 通讯作者:
Fabrizio Sergi
Development of an Experimental Protocol to Study the Neural Control of Force and Impedance in Wrist Movements with Robotics and fMRI
开发实验方案以研究机器人和功能磁共振成像手腕运动中力和阻抗的神经控制
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Kristin Schmidt;B. Berret;Fabrizio Sergi - 通讯作者:
Fabrizio Sergi
A Multi-objective Simulation-Optimization Framework for the Design of a Compliant Gravity Balancing Orthosis
用于设计顺应性重力平衡矫形器的多目标仿真优化框架
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
H. A. Chishty;Fabrizio Sergi - 通讯作者:
Fabrizio Sergi
Forearm orientation guidance with a vibrotactile feedback bracelet: On the directionality of tactile motor communication
使用振动触觉反馈手环进行前臂定向引导:关于触觉运动通信的方向性
- DOI:
10.1109/biorob.2008.4762827 - 发表时间:
2008 - 期刊:
- 影响因子:0
- 作者:
Fabrizio Sergi;D. Accoto;D. Campolo;Eugenio Guglielmelli - 通讯作者:
Eugenio Guglielmelli
Co-evolution of Morphology and Control of a Wearable Robot for Human Locomotion Assistance Exploiting Variable Impedance Actuators
- DOI:
10.1016/j.procs.2011.09.043 - 发表时间:
2011-01-01 - 期刊:
- 影响因子:
- 作者:
Jesse van den Kieboom;Fabrizio Sergi;Dino Accoto;Eugenio Guglielmelli;Renaud Ronsse;Auke J. Ijspeert - 通讯作者:
Auke J. Ijspeert
Fabrizio Sergi的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Fabrizio Sergi', 18)}}的其他基金
Multi-Muscle Magnetic Resonance Elastography (MM-MRE): a new technique to measure non-invasively individual force of forearm muscles during fine motor tasks
多肌肉磁共振弹性成像(MM-MRE):一种在精细运动任务期间无创地测量前臂肌肉个体力量的新技术
- 批准号:
1911683 - 财政年份:2019
- 资助金额:
$ 50万 - 项目类别:
Standard Grant
NRI: Goal-Oriented, subject-Adaptive, robot-assisted Locomotor Learning (GOALL)
NRI:目标导向、主题自适应、机器人辅助运动学习 (GOALL)
- 批准号:
1638007 - 财政年份:2016
- 资助金额:
$ 50万 - 项目类别:
Standard Grant
相似海外基金
Neuromechanics and Human Physiology
神经力学和人体生理学
- 批准号:
CRC-2019-00276 - 财政年份:2022
- 资助金额:
$ 50万 - 项目类别:
Canada Research Chairs
Novel Approaches for Modeling, Mapping, and Restoring Human Trunk Neuromechanics
人体躯干神经力学建模、绘图和恢复的新方法
- 批准号:
RGPIN-2021-04041 - 财政年份:2022
- 资助金额:
$ 50万 - 项目类别:
Discovery Grants Program - Individual
Novel Approaches for Modeling, Mapping, and Restoring Human Trunk Neuromechanics
人体躯干神经力学建模、绘图和恢复的新方法
- 批准号:
RGPAS-2021-00043 - 财政年份:2022
- 资助金额:
$ 50万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Novel Approaches for Modeling, Mapping, and Restoring Human Trunk Neuromechanics
人体躯干神经力学建模、绘图和恢复的新方法
- 批准号:
RGPIN-2021-04041 - 财政年份:2021
- 资助金额:
$ 50万 - 项目类别:
Discovery Grants Program - Individual
Neuromechanics And Human Physiology
神经力学和人体生理学
- 批准号:
CRC-2019-00276 - 财政年份:2021
- 资助金额:
$ 50万 - 项目类别:
Canada Research Chairs
Novel Approaches for Modeling, Mapping, and Restoring Human Trunk Neuromechanics
人体躯干神经力学建模、绘图和恢复的新方法
- 批准号:
RGPAS-2021-00043 - 财政年份:2021
- 资助金额:
$ 50万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Neuromechanics and Human Physiology
神经力学和人体生理学
- 批准号:
CRC-2019-00276 - 财政年份:2020
- 资助金额:
$ 50万 - 项目类别:
Canada Research Chairs
Understanding The Neuromechanics of the Human Foot and Ankle Joint Complex
了解人类足部和踝关节复合体的神经力学
- 批准号:
524829-2018 - 财政年份:2018
- 资助金额:
$ 50万 - 项目类别:
University Undergraduate Student Research Awards
Neuromechanics of learned sensorimotor vocal integration
学习感觉运动声音整合的神经力学
- 批准号:
8578948 - 财政年份:2013
- 资助金额:
$ 50万 - 项目类别:
Neuromechanics of learned sensorimotor vocal integration
学习感觉运动声音整合的神经力学
- 批准号:
8695323 - 财政年份:2013
- 资助金额:
$ 50万 - 项目类别: