Hybrid Position and Force Control for Upper Limb Rehabilitation of Stroke Patient

This paper presents hybrid position and force control (HPFC) methodology for position and as well as force tracking for upper limb rehabilitation of stroke patients. Stroke is a leading cause of disability in humans. Traditional rehabilitative therapies help regain motor function and ameliorate impairment, but they depend on the therapist’s experience and require many therapists, which is cost-prohibitive. Most robotic tasks with high severity such as rehabilitation, demands an effective force as well as position control scheme to ensure the safe physical contact between the robot and its environment in this case the patient. Some rehabilitation robots have been developed to help stroke survivors recover motor function. In past robots used for upper-limb rehabilitation employed general control schemes such as proportional integral derivative. To overcome the problem of force tracking in rehabilitation, robots require modern control techniques. To mimic the human upper-limb, and universality of application, an end-effector based robot is used for this study. To ensure the convergence of position and force errors to zero extensive simulations are performed. Two of assistant modes passive and active assistive rehabilitation are considered. Most common rehabilitation trajectories horizontal reaching, and vertical reaching are selected as robot’s motion for both passive and active assistive activities. The mathematical model of robots’ kinematics, dynamics, alongside the proposed control scheme has been discussed in detail.