939 Sweetwater Drive
Gainesville, FL 32611-6250
Enhancing Acquisition and Performance
of Complex Motor Skill
Meghan E. Huber
Postdoctoral Research Associate,
Department of Mechanical Engineering
Massachusetts Institute of Technology
Understanding how human learn and perform motor skills is not only important for developing theoretically-based interventions for physical assistance and rehabilitation, but also for improving human-robot interaction and advancing robot capabilities. Most of what we understand about human motor skill acquisition, however, stems from assessing performance on tasks that lack the complexity of real-world tasks. This talk presents a methodological approach to study the acquisition of novel and richer skills that capture coordination challenges inherent to everyday motor skills, such as managing task redundancy and physical interaction. Through the use of mathematical modeling and virtual technologies, this approach allows one to accurately examine the control and acquisition of complex skills in a controlled manner, without sacrificing task complexity. Analysis of a discrete throwing skill and a rhythmic ball bouncing skill exemplify how this approach was used to understand, and even enhance, novel skill acquisition and retention. An extension of this method to understand what perceptual information humans use to understand and learn from observing the motor behavior of others is also described. Ultimately, this research serves to both advance our fundamental understanding of human neuromotor control and provide novel insights to improve how robotic systems can guide, assess, and learn from human motor behavior.
Dr. Meghan E. Huber is a postdoctoral research associate in the Department of Mechanical Engineering at the Massachusetts Institute of Technology and a member of the Newman Laboratory for Biomechanics and Human Rehabilitation led by Professor Neville Hogan. She received her B.S. degree in Biomedical Engineering from Rutgers University in 2009 and her M.S. degree in Biomedical Engineering from The University of Texas at Dallas in 2011. She received her Ph.D. in Bioengineering from Northeastern University in 2016 under the advisement of Professor Dagmar Sternad. During her doctoral training, she was also a Visiting Junior Scientist in the Autonomous Motion Department at the Max Planck Institute for Intelligent Systems in Tübingen, Germany in 2014-2015. Her research addresses the challenges that intelligent systems face when guiding and learning from human behavior.