CHS: Medium: Collaborative Research: Novel Optimal Control for Co-Adaptation of Human and Powered Lower Limb Prosthesis

新兴的动力下肢假体对恢复截肢者的正常运动有很大的希望。然而，这些机器人设备目前缺乏穿戴者之间和内部的适应性，以应对穿戴者的身体变化和变化。频繁的手动和启发式调整在诊所是必需的，这限制了这些先进的假体的实际使用。为了更好地支持下肢截肢者的行走功能，提高其生活质量，需要一种智能、适应性强、互动性强的新一代假肢控制系统。pi的长期研究目标是创造出能够适应截肢者个人身体和认知能力的仿生腿，与佩戴者的运动和意图相协调，适应不断变化的环境，并从根本上恢复下肢损伤患者的全部功能。为此，pi在这个项目中的目标是为这些假肢创建一个新的最佳控制框架。他们将系统地解决支持自动适应佩戴者的身体能力的挑战，同时实现集成截肢假肢系统所需的步态性能。他们将为交互式界面提供初步设计和评估，该界面将允许佩戴者安全轻松地个性化假肢控制。项目成果将开辟可穿戴机器人的新前沿，并为这些创新设备的临床应用奠定基础，这不仅将影响假肢和矫形器行业，还将影响机器人社区，提供与人机交互相关的新知识，通过阐明截肢者运动的控制机制，生物力学和神经运动控制社区。通过提供创新和具有成本效益的假肢解决方案。这项工作将介绍的用于控制动力下肢假肢的新的基于截肢者-假肢性能的框架，代表了主要关注假肢（局部机器）设计的现有方法的偏离，因为它采用了一种全局方法，考虑了截肢者和假肢之间的共同适应，以便根据佩戴者的身体状况提供最佳的个性化帮助。pi将使用近似动态规划（ADP）来实现全局控制目标。ADP的这种创新使用将提供一个机会，在一个新的自适应机器人假体测试领域展示其最佳的自适应控制能力，这是一个独特而重大的挑战，只在人类可穿戴机器人中看到，但在没有生命的机器人中却没有。ADP方案基于近似和学习，缓解了与准确建模佩戴者的神经肌肉控制和动力学相关的问题，这些问题很难（如果不是不可能的话）实现。此外，pi将对经股截肢患者进行实验调查，研究截肢者与假肢之间的相互作用，包括评估截肢者的代偿策略，以及评估假肢控制中主观（人）和客观（机器）偏好的差异。

Emerging powered lower limb prostheses hold great promise for restoring normative locomotion in amputees. However, these robotic devices currently lack inter- and intra-wearer adaptability to cope with wearers' physical variations and changes. Frequent manual and heuristic adjustment in clinics is required, which limits the practical use of these advanced prostheses. A new generation of prosthesis control that is intelligent, adaptable, and interactive is needed to better support walking function and improve the quality of life of lower limb amputees. The PIs' long-term research goal is to create bionic legs that can adapt to the individual amputee's physical and cognitive capabilities, coordinate with the wearer's movement and intent, adjust to changing environments, and essentially restore the full function of patients with lower limb impairments. To this end, the PIs' objective in this project is to create a novel optimal control framework for these prostheses. They will systematically address the challenge of supporting automatic adaptation to the wearer's physical capability while achieving desired gait performance for the integrated amputee-prosthesis system. And they will provide a preliminary design and evaluation for an interactive interface that would allow wearers to personalize prosthesis control safely and easily. Project outcomes will open up a new frontier of wearable robotics and lay the foundation for clinical translations of these innovative devices, which will impact not only the prosthetics and orthotics industry but also the robotics community by providing new knowledge relating to human-robot interaction, the biomechanics and neuromotor control community by elucidating the control mechanism of amputee locomotion, and healthcare in general by providing innovative and cost-effective prosthesis solutions.The new amputee-prosthesis performance-based framework for control of powered lower limb prostheses which this work will introduce represents a departure from existing approaches that mainly focus on design for the prosthesis (a local machine), in that it adopts a global approach by accounting for co-adaptation between amputees and prostheses in order to provide optimal, personalized assistance based on wearers' physical conditions. The PIs will use approximate dynamic programming (ADP) to achieve the global control goal. Such innovative use of ADP will provide an opportunity to demonstrate its optimal adaptive control capability in a new test domain of co-adaptive robotic prosthesis, a unique and significant challenge only seen in human wearable robotics but not in lifeless robots. The ADP scheme is based on approximation and learning that alleviate problems associated with the requirement of accurately modeling wearers' neuromuscular control and dynamics that is difficult, if not impossible, to achieve. Additionally, the PIs will conduct an experimental investigation on subjects with transfemoral amputations of the interactions between amputees and prostheses, including evaluations of the compensatory strategies of amputees, and discrepancy assessment between subjective (human) and objective (machine) preferences in prosthesis control.