Event Location: NSH 1305
Bio: Gentiane Venture has completed an Engineer’s degree from the Ecole Centrale of Nantes (France) in 2000 specialized in Robotics and Automation. In the mean time she has obtained a MS degree from the Unversity of Nantes (France) in Robotics. In 2003, she obtained a PhD on Modelling and Identification of Car Dynamics from the University of Nantes (France). Her works were supported by the French car-manufacturer PSA Peugeot-Citroen (Paris, France). In 2004 she joined for 1 year the French Nuclear Agency (Paris, France) as a research assistant, working in collaboration with the Robotics Lab. of Paris University on the control of a tele-operated micro-manipulator. She was also teaching Automatics in a couple of Engineering schools. In 2004 she joined the YNL at the University of Tokyo with the support of the Japan Society for Promotion of Science for a two years postdoc fellowship. In 2006, still as a member of YNL, she joined the IRT project a Project Assistant Professor. In March 2009, she becomes an Associate Professor and starts a new lab at the Tokyo University of Agriculture and Technology. Her main research interests are: Human behavior understanding from motion, Dynamic modelling and identification of human musculo-tendon complex, Identification of humanoid robots dynamics, Micro-teleoperation, Modelling and identification of car dynamics, Path planning and movement generation for non holonomic robots.

Abstract: The dynamic properties of the human body are crucial in biomechanics studies, in gait studies and for some medical applications: orthopedics, neurology, musculoskeletal disorders. To monitor the variation of muscle mass during hospitalization, rehabilitation, the measurement of the inertia and the position of the center of mass (COM) of each link of the body is a key-data to refine the diagnosis and to provide personalized health-care. In this talk I will propose solutions to identify the human body dynamics from motion based on robotics formalism.

Three types of dynamics will be considered: the mass-parameters or segment parameters, the passive joint dynamics and finally the muscle dynamics. The main focus will be on the segment parameters. My recent research has allow to develop a tool to systematize the identification of segment parameters using whether pre-recorded or a real-time algorithm and a visual interface. I will put emphasis on the validation of the obtained results and the importance of the results for medical applications.