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Human Movement Understanding for Intelligent Robots and Systems

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Abstract : 

Human motor performance is a key area of investigation in biomechanics, robotics, and machine learning. Understanding human neuromuscular

control is important to synthesize prosthetic motions and ensure safe human-robot interaction. Building controllable biomechanical models through modeling and algorithmic tools from both robotics and biomechanics increases our scientific understanding of musculoskeletal mechanics and control. The resulting models can consequently help quantifying the characteristics of a subject’s motion and in designing effective treatments, like predictive simulations and motion training. My objective is to explore how neural control dictates motor performance in humans by developing a portable, soft, cyberphysical system and a computational framework - which incorporates real-time roboticsbased control, AI-based perception and learning, and OpenSim’s musculoskeletal models.

In this talk, I will present the modeling, control, and simulation components of this new framework with two examples on human manipulation and locomotion skills. The presented framework has promise to advance the field of rehabilitation robotics by deepening our scientific understanding of human motor performance dictated by musculoskeletal physics and neural control. Automated and real-time motion improvement and retraining, facilitated with such frameworks, promise to transform the neuromuscular health, longevity, and independence of millions of people, utilizing a cost effective approach.

Speaker：

Dr. Emel Demircan is an Associate Professor at the Departments of Mechanical and Aerospace Engineering and Biomedical Engineering at California State University, Long Beach. Dr. Demircan obtained her Ph.D in Mechanical Engineering from Stanford University in 2012. She was a postdoctoral scholar at Stanford from 2012 to 2014 and a visiting assistant professor at the University of Tokyo from 2014 to 2015. She was also a part-time scientist at Lucile Salter Packard Children's Hospital Gait Analysis Lab at Stanford University. Dr. Demircan's research focuses on the application of dynamics and control theory for the simulation and analysis of biomechanical and robotic systems. Her research interests include cyber-physical systems, rehabilitation robotics, sports.