EAGER: Treatment Planning for Gait Pathologies Based on Whole-Body Angular and Linear Momentum

主要研究者：Fregly，Benjamin J.和Hass，Christopher J.提案编号：1052754该提案旨在开发一个计算框架，该框架将有助于识别步态病理个体的有效个性化康复策略。四个主要目标是：1）证明正常和病理步态的全身动量变化彼此不同，并且这些聚类可以被视为不同步态模式的“动量特征”; 2）开发优化方法，以使用与指定动量特征匹配的受试者特定计算模型来预测不同受试者特定步态模式; 3）通过将正常步态动量特征应用于患者的计算模型来预测具有步态病理的个体的正常步态应该是什么样子;以及关于协调、力量、功率或关节运动范围），并评估不同的限制如何影响患者接近正常步态动量特征的能力。 计算模型对于开发和测试假设是有价值的，否则不可能通过实验探索。它们还可以提供一个理论框架来解释实验观察。在病理步态的情况下，尽管许多研究报告说，中枢神经系统（CNS）调节角动量在步行过程中，没有简单的控制法律目前存在的解释中枢神经系统如何使步行效率，甚至可能。很少有研究关注线性动量在人类运动过程中是如何守恒的，尽管最近的研究结果表明守恒发生在各种运动任务中。 使用基本动量考虑因素来预测病理步态个体可实现的、改进的步态模式的计算模型可能是一个有价值的工具，可以帮助临床医生做出客观、高效的治疗决策。拟议活动的智力价值拟议研究的智力价值将是开发一种简单的方法，用于根据患者具体情况生成不同的步态模式。最近的研究结果表明，运动任务表现出集群的动量变化。这一发现表明，针对这些变化的优化方法可能能够预测哪些康复策略对特定患者最有效。这种新的方法将是有价值的残疾人造成的神经系统疾病（即，脑性麻痹、中风）或活动障碍（即，依靠拐杖或拐杖），帮助他们实现更正常的步态模式。这项拟议研究的变革性质是从基于主观经验做出治疗决定的范式转变，而是基于患者特定计算模型做出的客观预测，这些模型遵守物理定律并考虑患者特定的限制。所提出的计算方法可以提供一种客观的手段，用于识别将康复努力集中在哪里，该康复努力可能为特定患者产生最大的功能改善。它不仅对患有病理性步态的人有益，而且拟议的研究还可以应用于其他领域，包括深空健康（即，通过帮助宇航员在失重环境中获得足够的载荷以减少骨和肌肉损失）和一般的移动性（即，通过帮助患者改善他们在非运动任务中的移动性）。此外，这项研究将包括一个代表性不足的研究生谁将通过这个项目的完成辅导。研究结果将通过比较优化预测与正常和模拟病理步态模式的实验测量进行评估。结果将通过出版物和会议介绍加以传播。

PI: Fregly, Benjamin J. and Hass, Christopher J.Proposal Number: 1052754 This proposal seeks to develop a computational framework that will facilitate identification of effective personalized rehabilitation strategies for individuals with gait pathologies. The four main objectives are to: 1) Demonstrate that whole-body momentum variations for normal and pathological gait cluster differently from one another and that these clusters can be viewed as "momentum signatures" for different gait patterns; 2) Develop an optimization methodology to predict different subject-specific gait patterns using a subject-specific computational model that matches a specified momentum signature; 3) Predict what normal gait should look like for individuals with a gait pathology by applying a normal gait momentum signature to a computational model of the patient; and 4) Predict where to focus rehabilitation efforts for specific patients by imposing patient-specific limitations (e.g., on coordination, strength, power, or joint ranges of motion) on the patient's computational model and evaluating how different limitations affect the patient's ability to approach a normal gait momentum signature. Computational models are valuable for developing and testing hypotheses that otherwise would be impossible to explore experimentally. They can also provide a theoretical framework to explain experimental observations. In the case of pathological gait, despite many studies reporting that the central nervous system (CNS) regulates angular momentum during walking, no simple control law currently exists to explain how the CNS makes walking efficient or even possible. Fewer studies have looked at how linear momentum is conserved during human locomotion, although recent findings indicate conservation occurs for various locomotion tasks. A computational model that uses basic momentum considerations to predict achievable, improved gait patterns for individuals with pathological gait could be a valuable tool to aid clinicians in making objective, highly effective treatment decisions.Intellectual Merit of the Proposed ActivityThe intellectual merit of the proposed research will be the development of a simple method for generating different gait patterns on a patient-specific basis. Recent results indicate that locomotion tasks exhibit clusters of momentum variations. This finding suggests that an optimization approach that targets these variations may be able to predict which rehabilitation strategies would be most effective for a specific patient. This novel approach will be valuable for people with disabilities resulting from either neurological disorders (i.e., cerebral palsy, stroke) or mobility impairments (i.e., dependence on a cane or crutches) by helping them achieve more normal gait patterns. The transformative nature of this proposed research is the paradigm shift away from making treatment decisions based on subjective experience and instead basing them on objective predictions made by patient-specific computational models that obey the laws of physics and account for patient-specific limitations.Broader Impact Resulting from the Proposed ActivityIf successful, the proposed computational methodology may provide an objective means for identifying where to focus rehabilitation efforts that are likely to produce the largest functional improvement for a particular patient. Not only will it be beneficial for people with pathological gait, but the proposed research can also be applied to other areas, including deep space health (i.e., by helping astronauts achieve adequate loading in a weightless environment to reduce bone and muscle loss) and general mobility (i.e., by helping patients improve their mobility for non-locomotion tasks). In addition, this research will include an underrepresented graduate student who will be mentored through the completion of this project. The research results will be evaluated by comparing the optimization predictions with experimental measurements for normal and emulated pathological gait patterns. The results will be disseminated through publications and conference presentations.