research direction: Identification of biomechanical dynamics and muscle dynamics for neurologically damaged patient is already challenging as the system response can drastically vary depending on the degree of the patient deficiencies. In FES (Functional Electrical Stimulation), movement synthesis and control are still a challenging task due to the complexity of whole body dynamics computation and the nonlinearity of stimulated muscle dynamics. One of the challenge concerns the feedback (torque, EMG, joint angle) that can be used to control joint angle, torque or stiffness. Moreover, control strategies have to be designed in order to be performed on portable architecture and tuned through advanced modeling and simulation. In this context, the goal of this PhD work is to study the optimization-based motion synthesis and real-time control framework which can generate stimulation patterns from the pre-computed motion synthesis database. Motion capture system together with the estimation of the Center of Mass would be used to assess the strategies. This work aims at the development of automatic method to establish deficient limb stability in computer-aided rehabilitation. This PhD work is performed under the collaborative project named @walk (artificial walking) between INRIA DEMAR project and AI lab of Stanford University.
Research background: -Master in control engineering, computer science, biomechanics, robotics or related disciplines. – good knowledge of C/C++ programming and matlab.
Scholarship Deadline: Contact Employer
More info: View info