Simulação computacional do movimento de flexão/extensão do cotovelo de uma órtese híbrida para membro superior

Abstract

Stroke frequently causes motor deficits in upper limbs, whose rehabilitation can be enhanced by hybrid robotic orthoses combined with Functional Electrical Stimulation (FES), improving muscle control and promoting neuroplasticity. Computational simulation of musculoskeletal systems allows optimization of these FES-assisted orthoses designs, reducing development costs and time. This work aims to develop a computational simulation of a hybrid orthosis (FES/mechanical) for post-stroke rehabilitation, focusing on musculoskeletal modeling and Proportional-Integral (PI) control of elbow flexion/extension movements, while also evaluating strategies to minimize muscle fatigue and analyze metabolic energy consumption (Bhargava model) in biceps and triceps muscles. This study expands previous research that developed a robotic orthosis and subsequently a hybrid version with FES (open-loop control), whose description provides context. For computational simulation, OpenSim software was adopted, containing a simplified upper limb model called arm26. The orthosis was rigidly fixed to the model through a WeldJoint. For dynamic simulations, Matrix Laboratory (MATLAB) with OpenSim library was used. MATLAB was employed for system identification in transfer function form (mapping muscle excitation signals as input and elbow angle as output) and to determine PI controller parameters. Subsequently, Simulink was used to implement and test the designed controller. The simulations implement a mechanical locking mechanism for joint immobilization with concurrent FES deactivation, resulting in significant reduction of metabolic energy consumption (biceps: 15.87 W to 5.96 W; triceps: 7.47 W to 6.02 W) and muscle fatigue. The PI controllers demonstrated satisfactory performance, with settling times between 1.38 and 2.96 s (4.85 s for the triceps) and overshoot below 0.7%. Additionally, the transfer function models achieved over 97% accuracy. Therefore, It is concluded that OpenSim is an effective tool for orthosis development, enabling the implementation of closed-loop control (with settling times close to 3 seconds) and mechanical locking mechanisms, which are the primary objectives of this work. Furthermore, computational simulations demonstrated that deactivating FES during the locking mechanism’s operation reduces metabolic energy consumption, suggesting lower fatigue. As a limitation, the use of a simplified upper limb model is noted, recommending the adoption of more complex models in future studies.