Subject: Personalization of learning recommendations and support in simulation-based physiotherapy education using multimodal sensory data generated by a robotic leg

This PhD position is in the domain of Artificial Intelligence in Education (AIED). The objective is to automatically personalize learning recommendations and support in simulation-based physiotherapy education using multimodal sensory data generated by a robotic leg. The main challenge of the research is in handling multimodal kinematic data generated by several sensors embedded into the robotic leg, in order to infer the skills and errors of physiotherapy students while they perform motor disorder diagnostics on the robotic leg for training purposes. Based on the inferred skills and errors, an intelligent system will be developed to recommend more personalized motor disorder cases to the students to maximize their learning.

The research will take place at the LIP6 research laboratory of Sorbonne University in Paris.

See the attached document for a full description of the position.