A new robot-based proprioceptive training algorithm to induce sensorimotor enhancement in the human wrist

Afferent proprioceptive signals, responsible for body awareness, have a crucial role when planning and executing motor tasks. Increasing evidence suggests that proprioceptive sensory training may improve motor performance. Although this topic had been partially investigated, there was a lack of studies involving the wrist joint. Proprioception at the wrist level is particularly relevant to interact with the environment through actions that require an accurate sense of position and motion, and fine haptic perception. In this study, we implemented and tested a robotic training algorithm of human wrist proprioception. The proposed task was a continuous tracking in the workspace identified by flexion-extension and radial-ulnar deviation movements. Healthy subjects were haptically guided towards the target, without any visual feedback of the position of the end-effector. Our results showed that, after the training, participants improved their motor performance in a different tracking task, completely active and with visual feedback. Additionally, the training led them to more efficient use of kinesthetic feedback during haptically-guided reaching tasks. Our findings demonstrated that the proposed training algorithm of wrist proprioception induced a task-specific sensorimotor enhancement. From the perspective of a rehabilitative intervention, this robot-based training has the potential to improve motor functions and the quality of life of subjects with sensorimotor deficits.