Understanding the underlying mechanisms of motor learning is crucial to improve neurorehabilitation. We aim to investigate the use of neural signals reflecting the cognitive and motor status of the trainee to adapt robotic training strategies to the patient’s individual needs and improve neurorehabilitation.
The addition of virtual reality during robotic training has been shown to improve patients’ motivation. Yet, the virtual reality environments currently employed in rehabilitation practice are displayed on 2D screens. This transformation removes the focus of attention from the real movement and results in games that are cognitively too demanding for brain-injured patients. We aim to explore how the use of augmented and immersive virtual reality can improve motor learning and neurorehabilitation.
Although there is increasing interest in using robotic devices to deliver rehabilitation therapy following neurologic injuries, to date, the functional gains associated to robotic rehabilitation are limited. We aim to improve neurorehabilitation by developing novel adaptive robotic training strategies that augment or reduce movement errors based on patients’ special needs, age, and characteristics of the trained motor task.