Abstract
Tracking patient progress through a course of robotic tele-rehabilitation requires constant position data logging and comparison, alongside periodic testing with no powered assistance. The test data must be compared with previous test attempts and an ideal baseline, for which a good understanding of the dynamics of the robot is required. The traditional dynamic modelling techniques for serial chain robotics, which involve forming and solving equations of motion, do not adequately describe the multi-domain phenomena that affect the movement of the rehabilitation robot. In this study, a multi-domain dynamic model for an upper limb rehabilitation robot is described. The model, built using a combination of MATLAB, SimScape, and SimScape Multibody, comprises the mechanical electro-mechanical and control domains. The performance of the model was validated against the performance of the robot when unloaded and when loaded with a human arm proxy. It is shown that this combination of software is appropriate for building a dynamic model of the robot and provides advantages over the traditional modelling approach. It is demonstrated that the responses of the model match the responses of the robot with acceptable accuracy, though the inability to model backlash was a limitation.
Highlights
There is increasing interest in the use of robots to assist the rehabilitation of stroke patients, partly due to the repetitive nature of post-stroke rehabilitation and the integration of stimulating video games [1] to increase patient motivation and partly due to a projected increase in strokes due to an ageing population, causing a strain on rehabilitation services [2]
The graph given by Figure shows the simulated response and the real responses of MyPAM when subjected to an x-direction minimum jerk trajectory, with the x- and y-positions across all repeats against time shown by Figure. In both the unloaded and loaded cases, the x-direction trajectory tracking shown by Figures 7 and 15 (Tests 1 and 3) is much smoother than the y-direction trajectory tracking shown by Figures 11 and 19 (Tests 2 and 4) for both the simulated response and the robot response
The effects of inertia are less pronounced when the majority of the movement occurs at Joint 1 because the majority of the mass of the robot is located between Joint 0 and Joint 1
Summary
There is increasing interest in the use of robots to assist the rehabilitation of stroke patients, partly due to the repetitive nature of post-stroke rehabilitation and the integration of stimulating video games [1] to increase patient motivation and partly due to a projected increase in strokes due to an ageing population, causing a strain on rehabilitation services [2]. Class 1 robots are high cost and are designed for clinical use with a therapist. Class 2 robots are low cost and intended for home use. Rehabilitation robots that are commercially available are Class 1 robots, and high cost. A large study has recently shown that the use of expensive robotics in a clinical setting provides little additional benefit to traditional rehabilitation alone and is not cost effective [10]. If there is a choice between traditional physiotherapist-led poststroke rehabilitation or robot-based rehabilitation, there is little benefit to selecting robot-based rehabilitation. Both options require travel to a clinical setting and face-to-face contact with a physiotherapist
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