Somatosensory Aspects of Robotic Training for Motor Learning and Neurorehabilitation
Project Members: Özhan Özen, Laura Marchal-Crespo
Project Start: 2018
Robots have the great advantage of being able to support the human limbs by applying precise forces. Robotic training has mainly target in enhancing learning (or relearning) of motor skills. However, another important aspect that has a crucial effect on regaining motor skills remains lacking the attention it deserves: sensory training.
Human motion control is a closed-loop control, i.e. the motor activations of the limbs are based on the somatosensory information they gather. We depend on the signals coming from our moving body parts to be able to navigate and interact within dynamic environments. Furthermore, several studies have associated sensory impairment at baseline with poorer motor recovery and function.
Lucky, robots provide great opportunities for training sensorimotor skills. We can create virtual environments easily, supplied with intelligently designed visuo-haptic elements that trainees can sense and interact with. Within this project, we design and regulate virtual mechanical training environments, which adjust their sensation elements online, according to specific somatosensory skills/deficits of the trainees.
We aim to use virtual objects which have high/rich dynamics, surface properties that provide purposeful sensations, and modulate the oscillation dynamics of the environment to train the trainees’ sensory system while simultaneously training their motor system. We believe this research has a great potential to impact the field of robotic neurorehabilitation.
Keywords: Motor Learning, neurorehabilitation, robotics, haptics, motion control, somatosensory training