PHASE-BASED CONTROL OF LOCOMOTION FOR HIGH-PERFORMANCE PROSTHESES AND ORTHOSES

描述（由申请人提供）：高性能下肢假肢和矫形器可以显著改善近100万美国截肢者和更多中风幸存者的生活质量，他们的截肢速度较慢，稳定性较差，效率低于健全人。尽管最近的机动假肢和矫形器有可能恢复受损人群的活动能力，但关键障碍仍然限制了它们的临床应用。 生存能力目前的动力腿独立地控制不同的关节和步态的时间段 循环，限制了对环境不确定性的鲁棒性，并要求临床医生花费大量时间针对个体调整每个控制模型。这种顺序控制方法是将人类步态模式视为时间函数的当前范例的直接结果。然而，最近的双足机器人可以用一个控制模型稳定地行走、跑步和爬楼梯，该控制模型驱动关节模式作为机械变量的函数，该机械变量连续地表示机器人通过步态周期的进展，即，一种“阶段感”。“机器人控制理论的这些新突破为解决假肢技术中的一个关键障碍提供了一个新的机会，即人类步态周期如何被视为一个相位变量而不是时间的函数。然后，假肢可以被设计成具有单个控制模型，该控制模型测量生物启发的相位变量以匹配人类的意志运动或对扰动做出响应。这一挑战的核心是人类神经肌肉系统如何保持阶段感的知识存在根本性差距。该项目旨在通过以下方式解决这一差距：1）识别用于人类运动的生物力学相变量; 2）为下肢假肢和矫形器设计统一的控制模型。我假设人类关节模式是由压力中心（COP）的脚跟到脚趾的运动驱动的-足底上的点，累积的反作用力被施加在地面上。我将测试这一假设，通过观察人体关节的COP扰动的反应，而走过一个机器人平台。然后，我将实施一种新的控制策略，使用这种感觉的相位的动力膝踝关节假体，这将是验证人类截肢者的科目。这项研究对于我们理解运动过程中的神经肌肉系统、分析步态周期的研究方法以及临床可行的假肢控制系统的设计具有重要意义。这项工作的创新包括：1）一种新的人类运动的相位依赖范式，挑战现有的时间依赖范式; 2）一种新的控制方法，将加速动力假肢和矫形器的临床应用。从这个大胆的新范式中获得的知识和概念将对物理医学和康复产生广泛的影响，促进中风后恢复活动能力的技术进步，脊髓损伤和周围神经病变。我在机器人控制和假肢博士后培训方面的专业知识使我有资格成功地执行这项高度创新的工作。

DESCRIPTION (provided by applicant): High-performance lower-limb prostheses and orthoses could significantly improve the quality of life for nearly a million American amputees and even more stroke survivors, whose ambulation is slower, less stable, and less efficient than that of able-bodied persons. Although recent motorized prostheses and orthoses have the potential to restore mobility in impaired populations, critical barriers still limit their clinical viability. Current powered legs independently control different joints and time periods of the gait cycle, limiting robustness to environmental uncertainty and requiring clinicians to spend significant amounts of time tuning each control model to the individual. This sequential control methodology is a direct consequence of the current paradigm for viewing human gait patterns as functions of time. However, recent bipedal robots can stably walk, run, and climb stairs with one control model that drives joint patterns as functions of a mechanical variable, which continuously represents the robot's progression through the gait cycle, i.e., a sense of "phase." These new breakthroughs in robot control theory present an emerging opportunity to address a key roadblock in prosthetic technology with a paradigm shift in how the human gait cycle is viewed: as a function of a phase variable rather than time. Prosthetic legs could then be designed with a single control model that measures a biologically-inspired phase variable to match the human's volitional movement or respond to perturbations. Central to this challenge is a fundamental gap in knowledge about how the human neuromuscular system might maintain a sense of phase. This project aims to address this gap by 1) identifying a biomechanical phase variable used in human locomotion, and 2) designing a unifying control model for lower-limb prostheses and orthoses. I hypothesize that human joint patterns are driven by the heel-to-toe movement of the center of pressure (COP)-the point on the foot sole where the cumulative reaction force is imparted against the ground. I will test this hypothesis by observing the response of human joints to perturbations of the COP while walking over a robotic platform. I will then implement a novel control strategy using this sense of phase on a powered knee-ankle prosthesis, which will be validated with human amputee subjects. This investigation will be significant to our understanding of the neuromuscular system during locomotion, research methods for analyzing the gait cycle, and the design of clinically viable prosthetic control systems. The innovation of this work is encompassed in 1) a new phase-dependent paradigm of human locomotion that challenges the existing time-dependent paradigm, and 2) a novel control methodology that will accelerate the clinical adoption of powered prostheses and orthoses. The knowledge and concepts gained from this bold new paradigm will have a broad impact in physical medicine and rehabilitation, catalyzing technological advances for restoring mobility after stroke, spinal cord injury, and peripheral neuropathy. My expertise in robot control and postdoctoral training in prosthetics make me uniquely qualified to successfully execute this highly innovative work.