MEIE Seminar Presentation: Modeling and Identification of Human Metabolic Energy Expenditure: Multibody Dynamic Systems Approach and Implications in Robotic Walking. By Dr. Joo Kim
~~Abstract: Energy expenditure of actuated multibody dynamic systems, such as humans and machines, is complicated to measure and difficult to predict. In this talk, a dynamic model of human metabolic energy expenditure (MEE) is rigorously derived by integrating the laws of thermodynamics and the principles of multibody system dynamics, which can evaluate MEE without the limitations inherent in experimental measurements (phase delays, steady state and task restrictions, limited range of motion) or muscle-space models (complexities and indeterminacies from excessive degrees of freedom, contacts and wrapping interactions, reliance on in vitro parameters). Muscle energetic components are mapped to the joint space of generalized coordinates, in which the MEE model is formulated. Experimental human walking data including oxygen uptake, kinematics, and kinetics was collected and used to estimate the model coefficients through a constrained nonlinear least squares algorithm. The joint-space coefficients estimated directly from active subjects provide reliable MEE estimates across different subjects, at different walking speeds, with improved accuracy as compared to existing muscle-based models. The subject-specific model also enables the calculation of instantaneous MEE rate and cost of transport as functions of time, and can be used for complex non-periodic tasks that may not be experimentally verifiable. The degree-of-freedom breakdown of the human MEE model has implications in biped robotic walking as well. An instrumentation system is designed to measure real-time current and voltage to fully characterize the electrical energy expenditure of a small biped robot. Experimental and computational results illustrate the energetic consequences of stable bent-kneed static walking in the biped robot versus the more efficient dynamic walking of humans that are evident at the joint level. In addition, the relative inefficiency of the robotic gait manifests as higher costs of transport with lower (normalized) speed ranges as compared with those of humans.
Brief Bio: Dr. Joo H. Kim is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at New York University (NYU). Dr. Kim directs the Applied Dynamics and Optimization Laboratory where his group focuses on fundamental research in multibody system dynamics, optimization theory and algorithms, and design and control of mechanical and biological systems. His group’s research for application includes robotics, biomechanics, and their intersections such as exoskeletons and prosthetics, with particular interest in balance/locomotion stability and energetics. Dr. Kim’s research has been sponsored by NSF, NASA, NYU, and industry. He received a Ph.D. degree in mechanical engineering in 2006, M.S. degrees in mathematics, mechanical engineering, and biomedical engineering, all from The University of Iowa, and a B.S. degree in mechanical engineering from Korea University in Seoul, South Korea. Before joining NYU in August 2009, he was an Adjunct Assistant Professor of Mechanical Engineering and Postdoctoral Research Scholar in the Center for Computer-Aided Design at the University of Iowa. Dr. Kim is a member of ASME, IEEE, and ASB, and organized numerous symposia and sessions in international conferences. He is currently serving as an Associate Editor for the Conference Editorial Board of the IEEE Robotics and Automation Society and a Program Committee Member for the 2015 IEEE International Conference on Humanoid Robots. Dr. Kim is the recipient of several awards and honors, including the 2007 Top Government Technology of the Year Award from the State of Iowa and the 2014 Best Paper Award from the ASME Computers and Information in Engineering Division.
Friday, September 19, 2014 at 10:30am to 11:30am