EFRI-M3C: A Hybrid Control Systems Approach to Brain-Machine Interfaces for Exoskeleton Control

EFRI-M3C：用于外骨骼控制的脑机接口混合控制系统方法

• 批准号: 1137267
• 负责人: Jose Carmena
• 金额: $ 200万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2016-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1137267&HistoricalAwards=false
• 关键词: EFRI; M3C; Hybrid; Control; Systems

This interdisciplinary research proposal brings together leaders in neurophysiology and brain-machine interfaces (BMI), control systems, and exoskeleton design to significantly advance our understanding of fundamental principles in the neural control of movement in scenarios that involve physical interactions with the world. Furthermore, this work will transform neuroprosthetic systems to improve the quality of life for a large number of neurological patients. The central question that motivates this proposal is: Does the brain use motor programs to help it control a highly redundant multi-degree of freedom (DOF) biomechanical plant such as the arm? To answer this question, this project will conduct a series of experiments that require a combination of three major innovations at the experimental (BMI), theoretical (hybrid control), and technical (exoskeleton design) level. This proposal aims to synthesize all three innovations into a new experimental paradigm unifying brain, biomechanics, and behavior. Specifically, visually-cued motor plans in the motor cortices of macaque monkeys will be: 1) read by a BMI, 2) interpreted by a hybrid controller and a musculoskeletal model, and 3) translated into appropriate movements and stiffness in a multi-DOF upper-limb exoskeleton. Intellectual MeritAt a societal level, this proposal seeks to create a significant advancement in neuroprosthetic systems to improve the quality of life of patients suffering from paralysis due to lesions of the central nervous system or other neurological disorders. BMIs will make a great impact in the quality of life for neurological patients by providing reliable performance when interacting with real objects and in real-world scenarios. This proposal also informs motor systems neuroscience by proposing a novel framework to study how neural ensembles can learn to control a multi-DOF exoskeleton by volitional modulation of neural activity in real-world tasks. It provides a critical link between neural events and real-world dynamics through a novel hierarchical distributed control scheme for hybrid systems identification and control that captures the continuous time evolution of the arm/exoskeleton, as well as the dynamically changing sequence of tasks. No motor task of this complexity has ever been demonstrated in a BMI system. The potential impact of the proposed work is immense. If successful, this work will transform our understanding about how the brain controls movement, and will introduce a paradigm shift in the development of the next generation of neural prosthetics that will restore motor function in millions of neurologically impaired patients ? a development which may very well impact other domains such as human-machine interaction and innovative user interfaces. Broader ImpactThe dissemination of data and research findings from this project will be done through a project website. Our codes will be open source, and the methods, algorithms and results will be available through publications in the fields of neuroscience, control and robotics. Through the Center for Information Technology Research in the Interest of Society (CITRIS) at Berkeley, research results from this program will be immediately accessible and distributed to a large engineering community, in particular other interdisciplinary research groups. Also, the findings in the proposed research will be outreached to K-12 students and their parents through various activities at UC Berkeley and Lawrence Hall of Science (LHS), such as CAL-day. In addition, research findings will be disseminated through workshops at the main annual conferences in neuroscience, robotics, control, and biomedical engineering. The educational component of this proposal relies on BMI as a platform for interdisciplinary education in science and engineering. New graduate-level courses will be introduced and existing courses will be enhanced based on results of this project. The proposed efforts will open doors to student rotations between neuroscientists, control theorists and roboticists. In addition to postdocs and graduate students, undergraduate students will participate in all aspects of the project: modeling, analysis, simulation, prototype development and experimentation. Special effort will be placed on the recruitment of individuals from underrepresented groups including women, thereby building on the strong record the PIs have in this area.

这项跨学科的研究提案汇集了神经生理学和脑机接口（BMI），控制系统和外骨骼设计的领导者，以显着提高我们对涉及与世界物理交互的场景中运动神经控制基本原理的理解。此外，这项工作将改变神经假体系统，以改善大量神经系统患者的生活质量。促使这一提议的核心问题是：大脑是否使用运动程序来帮助它控制高度冗余的多自由度（DOF）生物力学工厂，如手臂？为了回答这个问题，该项目将进行一系列实验，这些实验需要在实验（BMI）、理论（混合控制）和技术（外骨骼设计）层面上结合三大创新。该提案旨在将所有三项创新综合成一个统一大脑、生物力学和行为的新实验范式。具体而言，猕猴运动皮层中的视觉提示运动计划将：1）由BMI读取，2）由混合控制器和肌肉骨骼模型解释，以及3）转化为多DOF上肢外骨骼中的适当运动和刚度。在社会层面上，该提案旨在促进神经修复系统的重大进步，以改善因中枢神经系统病变或其他神经系统疾病而瘫痪的患者的生活质量。当与真实的物体和真实场景交互时，BMI将通过提供可靠的性能对神经系统患者的生活质量产生重大影响。该提案还通过提出一种新的框架来研究神经集合如何通过现实任务中神经活动的意志调制来学习控制多自由度外骨骼，从而为运动系统神经科学提供了信息。它提供了一个关键的神经事件和现实世界的动态之间的联系，通过一种新的分层分布式控制方案的混合动力系统的识别和控制，捕捉连续的时间演变的手臂/外骨骼，以及动态变化的任务序列。在BMI系统中还没有证明过这种复杂性的运动任务。拟议工作的潜在影响是巨大的。如果成功，这项工作将改变我们对大脑如何控制运动的理解，并将在下一代神经修复术的开发中引入范式转变，这将恢复数百万神经受损患者的运动功能。这种发展可能会很好地影响其他领域，如人机交互和创新的用户界面。将通过一个项目网站传播该项目的数据和研究结果。我们的代码将是开源的，方法，算法和结果将通过神经科学，控制和机器人领域的出版物提供。通过伯克利的社会利益信息技术研究中心（CITRIS），该计划的研究成果将立即提供给大型工程社区，特别是其他跨学科研究小组。此外，拟议研究的结果将通过加州大学伯克利分校和劳伦斯科学厅（LHS）的各种活动，如CAL日，向K-12学生及其家长推广。此外，研究成果将通过在神经科学，机器人，控制和生物医学工程的主要年度会议研讨会传播。该提案的教育部分依赖于BMI作为科学和工程跨学科教育的平台。将根据这一项目的结果，开设新的研究生课程，并加强现有课程。这项提议将为神经科学家、控制理论家和机器人专家之间的学生轮换打开大门。除了博士后和研究生，本科生将参与项目的各个方面：建模，分析，模拟，原型开发和实验。将特别努力从代表性不足的群体中征聘个人，包括妇女，从而在首席执行官在这一领域的良好记录的基础上再接再厉。