Rationale for Researching in DOB/OC-Based Rehabilitation Robots: Simulation Results

In the design of rehabilitation robots, it is important to accurately describe the interaction between the body of the patient and the hand of the therapist. Traditional methods based on variable impedance and “help as needed” support do not have the ability to completely understand how the functional characteristics of the musculoskeletal system determine a movement pattern. The disturbance observer (DOB) is a robust tool widely used to estimate external disturbances and system uncertainties frequently embedded in rehabilitation robots to estimate the human effort. On the other hand, optimal control (OC) is the main tool used to model the human movement realisation. Despite the potential that DOB/OC-based robots can hold, they are poorly investigated because the modelling complexity of the constrained human movement. Therefore our goal was to simulate the interaction between a musculoskeletal model driven by an OC algorithm and a DOB based robot. The constrained movement has been simulated with a closed loop resembling the afferent feedback of the sensorimotor system. A inner closed loop with higher updating frequency, was used to model the superior ability of the robot to react to external forces. The simulations revealed that a DOB/OC-based rehabilitation robot could be effective in: 1) guiding the patient during very specific movements while taking into account muscle disorders and joint mobility and 2) designing more precise and effective rehabilitation robots that could target specific muscle groups.