Abstract
Reduced mobility is a significant societal problem. In 2010, 30.6 million adults had ambulatory limitations, and 23.9 million individuals found it difficult to walk one-quarter mile, only in US alone. This reduced mobility is related to increased medical problems and can have detrimental socio-economical impacts. The problem will only increase with an aging population. The drive to discover effective strategies for human gait assistance has led to investigations into human-wearable robots. In response, my research strives to advance the field by focusing on wearable robots that can respond to individual users, resulting in a smart assistance strategy in which the robot adapts to the human wearers. Furthermore, my research includes the concept of co-adaptation, in which the human users receive guidance on how to adjust their movement patterns to optimize their benefit from the personalized robot. In this talk, I will introduce a robot adaption method to a user, human-in-the-loop (HIL) optimization, and the user guidance method to facilitate robot use. The HIL optimization is a machine learning approach using biofeedback, which significantly reduced walking and squatting efforts when users wore various wearable-robots such as hip and ankle soft exosuit, ankle-foot orthosis, and ankle-foot prosthesis. My group also found that user guidance via visual feedback can improve the wearable robot use, even for an unfavorable condition – initially increased the cost of walking. The seminar will be concluded with a discussion about the challenges and opportunities offered by the human-in-the-loop assistance controller and user guidance method.
Biography
About Dr. Myunghee Kim: Dr. Kim is as an assistant professor at UIC Department of Mechanical and Industrial Engineering. Her primary research focus is the development of assistive robotic devices for improving mobility and quality of life through integrative approaches of numerical dynamic models, machine learning techniques, experimental testbeds, and controlled human-subject experiments. She received her M.S. degrees from Korea Advanced Institute of Science (KAIST) and Technology and Massachusetts Institute of Technology (MIT), a Ph.D. degree from Carnegie Mellon University and held a post-doctoral appointment at Harvard University. She was a control engineer at Samsung. She received Best Paper Award in the Medical Devices category at International Conference on Robotics and Automation (ICRA), 2015. Recently, her group work on a data-driven model estimation method resulted in the Best Poster Award at the US-Korea Conference (UKC) 2019. Her research and education have received funding from a federal source (National Science Foundation (NSF) with National Institute for Occupational Safety and Health (NIOSH)), a defense agency (Army Research Lab), an internal fund for global collaboration (UIC-TEC), a research institute (Korea Institute of Robotics & Technology Convergence), a consortium of companies (Office Ergonomics Research Committee), and private company (LIG Nex1).
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