CAREER: Towards An Optimization-Based and Experimentally Verified Predictive Theory of Human Locomotion

该学院早期职业生涯规划（CAREER）奖的研究目标是获得一个足够准确，广泛适用的预测理论，人们如何走路，跑步和稳定他们的运动。通过计算最小化能量消耗的运动，已经有可能预测人类行走和跑步的某些方面。然而，目前还不知道这种最小化是否可以同时预测许多不同实验的结果，或者不同受试者之间的差异。PI将使用大规模逆优化来尝试推导出一个单一的目标函数，该目标函数可能与能量使用松散相关，当在人体计算机模型的背景下最小化时，可以预测许多不同实验的结果。建议的项目有四个相互关联的部分：（1）在各种情况下合并运动数据：不同的速度，倾斜，身体变化，如增加质量等;（2）逆优化，以推断目标函数，当最小化时，同时解释了相当大的一部分（3）正向优化，以预测在反向优化中未使用的运动情况下的行为;（4）利用最优性预测扰动响应，并与扰动实验进行比较。例如，一个准确和广泛适用的人类运动理论将使假肢和矫形装置的系统化模型设计成为可能，并为运动病理的诊断和治疗提供信息，包括可能指导手术干预。该项目将把研究纳入一些教育活动，针对不同的学生群体，从K-12到研究生。PI将与俄勒冈州立大学的女性工程项目合作，为女高中生创建一个教育模块，旨在增加她们在STEM学科接受进一步教育的可能性。 这些教育模块将强调数学理论，计算机模拟和科学与工程实验之间的相互作用，以及提高人类生活质量。

The research objective of this Faculty Early Career Develpment (CAREER) award is to obtain a sufficiently accurate, and broadly applicable, predictive theory of how people walk, run, and stabilize their movements. It is already possible to predict some aspects of human walking and running, by computing motions that minimize energy consumption. However, it is not known if such minimization can simultaneously predict the results of many different experiments, or the differences between different subjects. The PI will use large-scale inverse optimization to try to deduce a single objective function, perhaps loosely correlated with energy use, which, when minimized in the context of a computer model of the human-body, predicts the outcomes of many different experiments. The proposed project has four inter-related pieces: (1) Consolidation of locomotion data under a variety of situations: different speeds, inclines, body changes like addition of masses, etc; (2) Inverse optimization to infer the objective function which when minimized, simultaneously explains a substantial fraction (but not all) of the collected data; (3) Forward optimization to predict behavior in locomotor situations not used in the inverse optimization; and (4) Predict responses to perturbations using optimality and compare with perturbation experiments. An accurate and broadly applicable theory of human locomotion will, for instance, enable the systematic model-based design of prosthetic and orthotic devices, and inform the diagnosis and treatment of movement pathologies, including possibly guiding surgical interventions. The project will integrate the research into a number of educational activities, aimed at different student groups, from K-12 to graduate students. The PI will work with OSU's Women in Engineering program to create an educational module for female high school students, targeted at increasing their likelihood of pursuing further education in the STEM disciplines. These educational modules will emphasize the interplay between mathematical theories, computer simulations, and experiments in science and engineering, and in improving the quality of human life.