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Modulation of gait dynamics post-stroke

中风后步态动力学的调节

基本信息

批准号：
10677559
负责人：
Michael Charles Rosenberg
金额：
$ 7.41万
依托单位：
EMORY UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-06-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10677559
关键词：
Address Adult Biofeedback Biomechanics Cerebral Palsy Characteristics Child Classification Clinical Clinical Trials Complement Complex Computational Technique Data Data Set Exhibits Experimental Designs Functional disorder Gait Gait speed Goals Hemiplegia Impairment Individual Individual Differences Individuality Joints Lead Limb structure Literature Methodology Modeling Motion Movement Muscle Nervous System Nervous System Trauma Network-based Neuromechanics Paresis Pattern Prediction of Response to Therapy Rehabilitation therapy Research Series Speed Stroke Subgroup Techniques Testing Time Training Visual Walking Work career data-driven model design flexibility gait rehabilitation improved innovation model design neural novel patient population personalized medicine post stroke recurrent neural network rehabilitation technology response skills stroke survivor treadmill treatment responders treatment response walking speed

项目摘要

PROJECT SUMMARY/ABSTRACT My career goal is to improve the personalization of stroke gait rehabilitation and develop novel rehabilitation technologies using neuromechanics-based data-driven modeling in conjunction with hypothesis-driven experimental design. The proposed research aims to understand how neural constraints impact stroke survivors’ ability to coordinate execution-level joint dynamics to flexibly modulate whole-body center-of-mass (COM) dynamics between slow inverted pendulum and fast spring-mass dynamics during walking; a task critical to achieving stable, efficient, and rapid movement. My preliminary data in a single individual suggest that COM dynamics are asymmetric post-stroke, but further characterization of joint coordination and COM dynamics is needed to understand their relationship with interindividual and inter-limb differences in post-stroke walking function and treatment responses. Two major methodological barriers to characterizing these relationships are a lack of 1) metrics and techniques to encode complex, individual-specific gait dynamics post-stroke, and 2) long time-series datasets containing diverse movement patterns needed to test neuromechanical hypotheses about gait. To address these challenges, I will work with Sponsor Ting and Co-Sponsor Berman to extend data- driven techniques developed in my doctoral research to identify COM dynamics and characterize their relationships to joint dynamics; with Sponsor Ting and Co-Sponsor Kesar I will design and collect new datasets from stroke survivors of diverse movement patterns using biofeedback during walking. Aim 1: Test whether interindividual and inter-limb differences in COM dynamics post-stroke are associated with walking speed. I will evaluate the similarity of baseline post-stroke COM dynamics to able-bodied (AB) adults and between paretic and non-paretic limbs. Further, I will examine whether the paretic-limb transitions from inverted pendulum to spring-mass dynamics at faster treadmill speeds, decreasing asymmetry in COM dynamics. Aim 2: Characterize reductions in stroke survivors’ ability to modulate joint dynamics to achieve desired COM dynamics. Using visual biofeedback to prescribe COM dynamics, I will test whether stroke survivors have reduced ability to emulate COM dynamics compared to AB adults and determine if joint dynamics characterize COM dynamics less accurately in stroke survivors than AB adults. Aim 3: Test whether sub-groups of individuals with similar COM and joint dynamics predict biofeedback responses more accurately than discrete metrics. I will test whether, across a range of biofeedback-prescribed COM dynamics, baseline COM and joint dynamics can classify changes in joint dynamics with biofeedback more accurately than discrete clinical or biomechanical variables. I will also have training in clinical trials by participating in Sponsor Kesar’s ongoing gait rehabilitation study. The proposed research and training will complement my doctoral skillset, preparing me to lead independent research combining experimental design and computational techniques to discover neuromechanical mechanisms underlying gait dysfunction and develop novel gait rehabilitation for individuals with neurological injuries.

项目摘要/摘要我的职业目标是提高中风步态康复的个性化，并开发新的康复结合使用基于神经力学的数据驱动建模和假设驱动的技术实验设计。这项拟议的研究旨在了解神经约束如何影响中风幸存者的协调执行级关节动力学以灵活调整全身重心(COM)的能力在慢速倒立摆和快速弹簧-质量动力学之间行走的动力学；这是一个关键的任务实现稳定、高效、快速的运动。我个人的初步数据显示COM 动力学是不对称的卒中后，但关节协调和COM动力学的进一步特征是需要了解它们与卒中后步行的个体间和肢体间差异的关系功能和治疗反应。描述这些关系的两个主要方法障碍是缺乏1)标准和技术来编码中风后复杂的、特定于个人的步态动态，以及2)长包含不同运动模式的时间序列数据集需要测试以下神经力学假设步态。为了应对这些挑战，我将与赞助商Ting和共同赞助商Berman合作，扩展数据- 在我的博士研究中开发的驱动技术，用于识别COM动态并描述其与联合动力学的关系；与赞助商Ting和共同赞助商Kesar I将设计和收集新的数据集来自不同运动模式的中风幸存者，在步行过程中使用生物反馈。目标1：测试是否中风后COM动力学的个体间和肢体间差异与行走速度有关。这就做评估健康人(AB)和偏瘫患者卒中后基础COM动力学的相似性和非瘫痪的四肢。此外，我将研究偏瘫肢体是否从倒立摆过渡到跑步机速度更快时的弹簧-质量动力学，减少COM动力学中的不对称性。目标2：确定特征中风幸存者调节关节动力学以实现所需COM动力学的能力降低。使用可视生物反馈规定COM动力学，我将测试中风幸存者是否具有降低的模拟能力 COM动力学与AB成年人的比较，并确定关节动力学是否更少地表征COM动力学中风幸存者比AB成人更准确。目标3：测试具有相似COM的个体的子组关节动力学比离散度量更准确地预测生物反馈反应。我会测试一下是否，在一系列生物反馈规定的COM动力学中，基线COM和关节动力学可以分类使用生物反馈比离散的临床或生物力学变量更准确地改变关节动力学。我还将通过参与赞助商凯撒正在进行的步态康复研究，接受临床试验方面的培训。这个拟议的研究和培训将补充我的博士技能，为我领导独立研究做好准备结合实验设计和计算技术来发现神经力学机制潜在的步态功能障碍，并为神经损伤患者开发新的步态康复。