Toward a Mechanistic Understanding of Optimization Principles Underlying Hemiparetic Gait

对偏瘫步态优化原理的机械理解

• 批准号: 9753311
• 负责人: James M. Finley
• 金额: $ 38.11万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9753311
• 关键词: Acceleration; Acoustics; Address; Affect; Amputees; Automobile Driving; Behavioral; Biomechanics; Brain; Brain Injuries; Clinical; Computer Simulation; Computing Methodologies; Cost-Benefit Analysis; Development; Environment; Equilibrium; Exercise Physiology; Functional disorder; Gait; Gases; Goals; Health Care Costs; Impairment; Individual; Individual Differences; Intervention; Knowledge; Lead; Learning; Left; Length; Link; Location; Machine Learning; Measures; Mechanics; Metabolic; Movement; Nervous system structure; Paresis; Parkinson Disease; Participant; Patients; Pattern; Physical therapy; Physiological; Process; Psychological reinforcement; Reaction; Rehabilitation therapy; Research; Research Personnel; Side; Societies; Specific qualifier value; Speed; Step training; Stroke; Testing; Time; Uncertainty; Walking; Work; behavior observation; clinical practice; computer science; computerized tools; cost; design; effective intervention; experience; fall risk; foot; functional independence; gait rehabilitation; hemiparesis; high risk; improved; injured; locomotor control; machine learning algorithm; motor control; motor impairment; novel strategies; patient population; post stroke; public health relevance; rehabilitation strategy; relating to nervous system; social stigma; spatiotemporal; stroke rehabilitation; stroke survivor; success; treadmill; treadmill training; visual feedback; walking speed

This project seeks to identify how motor impairments in stroke survivors contribute to mobility deficits through the use of behavioral observations and computational models. Ultimately, this knowledge could be used to design more effective interventions to improve walking ability, increase functional independence, and reduce fall risk in individuals post-stroke. After a stroke, walking ability is affected by motor control deficits which are often characterized by hemiparesis, or weakness on one side of the body. During walking, hemiparesis is often associated with a visible limp that is due to differences in step lengths and stance times between the right and left sides of the body. Reducing these right-left asymmetries are a common objective of rehabilitation, and recently researchers have developed a number of approaches designed to reduce asymmetries such as acoustic pacing, unilateral step training, and split-belt treadmill training. Despite the recent clinical focus on reducing asymmetry, the potential functional benefits of improving symmetry have yet to be established. This research will address this gap by answering two fundamental questions: 1) Do improvements in symmetry lead to functional benefits such as a more efficient walking pattern or improvements in balance? 2) If stroke survivors retain the capacity to walk more symmetrically why do they choose to do otherwise? Although improvements in symmetry can no doubt reduce the potential stigma of walking with a limp, it is possible that a symmetric walking pattern could be less efficient or put patients at a higher risk of falls if it requires that they push the limits of their capacity. Alternatively, it is possible that, through repeated stepping practice, post- stroke individuals have reinforced a suboptimal pattern due to insufficient experience with a more optimal, symmetric pattern. Addressing these issues requires a thorough understanding of the processes by which stroke survivors optimize their walking pattern. Here, these issues are addressed using behavioral approaches to quantify tradeoffs between asymmetry and measures of walking ability such as stability and economy, and computational methods to identify the causal relationships linking these variables. Ultimately, the knowledge derived from this work will provide a mechanistic understanding of how the damaged brain optimizes movement, and may also inform the way in which clinicians develop personalized rehabilitation objectives for stroke survivors. Our findings may also inform cost/benefit analyses of walking in other patient populations known to have asymmetric walking patterns such as amputees or individuals with Parkinson's disease. Furthermore, providing a more mechanistic rationale for gait rehabilitation interventions could improve the efficiency of physical therapy, reduce health care costs, and ultimately help to better reintegrate individuals with neuromotor impairments into society by maximizing their mobility.

该项目试图确定中风幸存者的运动障碍是如何通过 行为观察和计算模型的使用。最终，这些知识可以被用来 设计更有效的干预措施，以改善步行能力，增加功能独立性，减少 中风后个体的跌倒风险。中风后，行走能力会受到运动控制缺陷的影响，这些缺陷 偏瘫的通常以偏瘫或身体一侧虚弱为特征的在行走时，偏瘫通常是 与可见的跛行有关，这是由于右腿和右腿之间的步长和站立时间不同造成的 身体的左侧。减少这些左右不对称是康复的共同目标，以及 最近，研究人员开发了许多旨在减少不对称性的方法，例如 声学起搏、单侧踏步训练和分体带跑步机训练。尽管最近临床上关注的是 减少不对称性，改善对称性的潜在功能好处尚未确定。这 研究将通过回答两个基本问题来解决这一差距：1)对称性的改善是否领先 是否有功能上的好处，如更有效的步行模式或改善平衡？2)如果中风 幸存者仍然有能力更对称地行走，为什么他们会选择其他方式呢？虽然 对称性的改善无疑可以减少跛行的潜在耻辱，有可能 对称步行模式可能效率较低，或者使患者面临更高的跌倒风险，如果它要求患者 将他们的能力推向极限。或者，也可以通过反复的踏步练习，后- 中风患者由于经验不足而强化了一种次优模式， 对称图案。解决这些问题需要透彻地了解通过哪些过程 中风幸存者优化了他们的行走模式。在这里，使用行为方法来解决这些问题 量化不对称性与稳定性和经济性等步行能力指标之间的权衡，以及 确定这些变量之间因果关系的计算方法。归根结底，知识 从这项工作中衍生出来的将提供对受损大脑如何优化的机械性理解 运动，还可以为临床医生制定个性化的康复目标提供参考 中风幸存者。我们的发现也可能为在其他患者群体中步行的成本/收益分析提供参考 已知有不对称行走模式，如截肢者或帕金森氏症患者。 此外，为步态康复干预提供更机械化的理论基础可以改善 物理治疗的效率，降低医疗保健成本，最终帮助个人更好地重新融入社会 通过最大限度地提高他们的行动能力，将神经运动障碍带入社会。