This Mind, Machine, and Motor Nexus (M3X) project plans to use a wearable upper extremity robotic exoskeleton to address the open question of how best to train people to perform new motor tasks. Two objectives will be pursued. First, the project team will use the robotic exoskeleton in a series of human subject experiments to identify "source tasks" that can be combined to learn a dynamically challenging motor skill. Second, the team will use the identified source tasks to explore the efficacy of "curriculum-based" task training that seeks to build skills efficiently and effectively through a progression of sub-tasks of increasing challenge. The experimental task to be learned requires a high degree of manual coordination in the manipulation of a hand-held tool with challenging internal continuum dynamics. This research involves several disciplines including mechanical engineering, computer science, neuroscience, medical sciences, and education. The project will promote the progress of science and advance the national health by developing fundamental knowledge in support of a robot-mediated coaching system for motor skills training. Education and outreach activities engage the participation of undergraduate students from underrepresented groups in the research.
This project will pursue two objectives to advance the state-of-the-art in robot-mediated coaching for motor skills training. For the first objective, the project team will use a wearable upper extremity robotic exoskeleton and an immersive Virtual Reality system to analyze movement kinematics, kinetics, and surface electromyographic activity during tool manipulation as people perform a challenging dynamic task. The result of this effort will be an identified set of "source tasks" that will form the building blocks of a motor skill training "curriculum" to be developed and tested in the project's second objective. For that objective, additional human subject studies will evaluate the efficacy of a variety of curricula (i.e., combinations of source tasks, source task orders, and training task transition times) to be developed using a Reinforcement Learning agent that will sequence the source tasks during training. The research explores the mechanisms by which human motor function can be shaped and directed by interactions with robotic exoskeletons. The major outcome of this work will be a robot-mediated coaching system for motor skills training, which holds potential to improve human motor performance in a variety of scenarios ranging from robot-assisted surgery, sports, and physical rehabilitation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
