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

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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.