May 22, 2015, Webb 1100

In recent years, robotics computational strategies have been seen to contribute significantly to the analysis of human motion and manipulation skills. The analyses have led to the advancements in the field of robotics, such as by allowing human inspired capabilities in robots and simulated systems as well as the nature inspired techniques of robot learning through observation. Furthermore, they also allowed the deeper understanding of human body and its motion generation strategies. This requires accurate reconstruction of movement sequences, modeling of musculoskeletal kinematics, dynamics, and actuation, and suitable criteria for the characterization of performance. Building on methodologies and techniques developed in robotics, a host of new effective tools have been established for the synthesis of human motion. In this talk, I present roboticsbasedalgorithms and advanced computational tools to (i) characterizenatural human motion and the higher level strategies of its realization of complex tasks and in interactingwith the external environment; (ii) predict behavior and synthesize humanlikemotions; (iii) developstrategies for human motion reconstruction on engineered anthropometric systems; and (iv) develop modelsof human neuromusculoskeletalsystem for balance and posture control. The roboticsbasedreconstruction and synthesis approaches presented in this talk provide an importantbasis for understanding natural human motion. These developments are applicable to efficient robot controland human performance prediction with tremendous benefits in rehabilitation, athletic training, ergonomics,injury biomechanics, and humanrobotinteraction.

Emel Demircan received her Ph.D.’12 in Mechanical Engineering from Stanford University. She was
graduate research and teaching assistant during her PhD under the supervision of Professor Oussama
Khatib. From October 2012 to December 2013 she was postdoctoral scholar in the Robotics Research Laboratory in the Computer Science department at Stanford University. In January 2014, Dr. Demircan was invited by Graduate Program for Social ICT Global Creative Leaders (GCL) to become project assistant professor of the Department of MechanoInformatics within the Graduate School of Information Science and Technology at University of Tokyo, where she is the lecturer of “Biomechanics of Human Movement”. She also acts as a parttime researcher at Lucile Salter Packard Children’s Hospital Gait Analysis Lab at Stanford University. Her research focuses on the application of dynamics and control methods for the simulation and analysis of biomechanical and robotic systems. Her research interests include experimental and computational approaches to study human movement, rehabilitation robotics, sports biomechanics, human motion synthesis, natural motion generation in humanoid robotics, and human motor control. In 2014, Dr. Demircan established an IEEE RAS Technical Committee on “Human Movement Understanding”. She is a recipient of the IEEE RAS Creation of Educational Materials in Robotics and Automation (CEMRA) funding. Dr. Demircan is an OpenSim Fellow, an honor from N ational Center for Simulation in Rehabilitation Research (NCSRR) in recognition for her strong commitment to the OpenSim community and her deep expertise in biomechanical modeling and simulation.