A Fuzzy Controller for Movement Stabilization Using Afferent Control: Controller Synthesis and Simulation.

Stimulation of spinal sensorimotor circuits can improve motor control in animal models and humans with spinal cord injury (SCI). More recent evidence suggests that the stimulation increases the level of excitability in the spinal circuits, activates central pattern generators, and it is also able to recruit distinctive afferent pathways connected to specific sensorimotor circuits. In addition, the stimulation generates well-defined responses in leg muscles after each pulse. The problem is that in most of the neuromodulation devices, electrical stimulation parameters are regulated manually and stay constant during movement. Such a technique is likely suboptimal to intercede maximum therapeutic effects in patients. Therefore, in this article, a fuzzy controller has been designed to control limb kinematics during locomotion using the afferent control in a neuromechanical model without supraspinal drive simulating post-SCI situation. The proposed controller automatically tunes the weights of group Ia afferent inputs of the spinal cord to reset the phase appropriately during the reaction to an external perturbation. The kinematic motion data and weights of group Ia afferent inputs were the input and output of the controller, respectively. Simulation results showed the acceptable performance of the controller to establish adaptive locomotion against the perturbing forces based on the phase resetting of the walking rhythm.