PhD Position Robotic Gait Rehabilitation

Updated: 24 days ago
Deadline: 01 May 2021

Most of the research in robot-assisted gait training in stroke rehabilitation has focused on designing rigid exoskeletons or end-effector devices to guide the legs/feet of neurologic patients in a “correct” gait pattern. However, research on motor learning has stated that patients’ effort and error/environment exploration (i.e., the active exploration of new motor tasks) is crucial to boost motor (re)learning. Further, Neuroscience suggests that both realistic visual and somatic sensory information play a fundamental role in generating skillful movements. Thus robots should be designed and controlled to adapt and respond to patients’ efforts while promoting an enriched somatosensory experience during training to achieve maximal and tailored therapeutic effects.

For this project, you will be involved in the (re)design of robotic devices for locomotion rehabilitation and in the development of new patient-personalized control strategies to enhance rehabilitation outcomes by leveraging realistic visual and somatic feedback. First, you will exploit VR-based techniques, such as embodiment and motivation, to design immersive VR that maximizes skill acquisition. Second, you will augment heavily-constructed exoskeletons with fine haptic capabilities through advanced controllers to provide congruent somatosensory stimulation during assisted training to enhance motor learning.

In this project, you will collaborate closely with our clinical partners at Erasmus MC, Rotterdam in the design concept and will evaluate the new technology in patients with brain injuries.

Near-future robot intelligence offers great potential for our society, provided we can co-operate with this technology. The Human-Robot Interaction group is embedded in the Cognitive Robotics Department at TU Delft, where we aim to contribute to the responsible development of robotic technologies in human-inhabited environments. We do so by research organized in four groups: computer vision for intelligent vehicles, machine learning for learning and autonomous control, robot dynamics and human-robot interaction.

In the Human-Robot Interaction group we work on Motor Learning and Neurorehabilitation Robotics (the team headed by Laura Marchal-Crespo), Cognitive Human-Robot Interaction (the team headed by Joost de Winter), and on Physical Human-Robot Interaction (the Delft Haptics Lab, a team headed by David Abbink). Strong collaborations exist with cross-faculty institutes (TU Delft Robotics Institute and TU Delft Transport Institute), our national robotic ecosystem (RoboValley, Holland Robotics), Clinical partners (Erasmus MC), and international industry and academia.

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