Analysis of movement of an elbow joint with a wearable robotic exoskeleton Using OpenSim software

Human body movement occurs as a result of a coordinated effort between the skeleton, muscles, tendons, ligaments, cartilage, and other connective tissue. The study of movement is crucial in the treatment of some neurological and musculoskeletal diseases. The advancement of science and technology has led to the development of musculoskeletal model simulation software such as OpenSim that plays a very significant role in tackling complex bioengineering challenges and assists in our understanding of human movement. Such biomechanical models of musculoskeletal systems may also facilitate medical decision-making. Through fast and accurate calculations, OpenSim modelling enables prediction and visualisation of motion problems. OpenSim has been used in many studies to investigate and assess movements of the upper limb under various scenarios. This work investigates elbow movement of a paretic arm wearing a myoelectric robotic exoskeleton. The simulation focuses on the exoskeleton elbow joint with one degree of freedom for individuals that we have developed to support and rehabilitate a weakened/paretic arm due to a spinal cord injury for example. Accordingly, it simulates the kinematic characteristics of the human arm whilst the exoskeleton assists the arm flexion/extension to maximise its range of motion. To obtain the motion data required for this study, a forward dynamics method must be implemented. Firstly, inverse kinematics is applied to the joint angles, and then, the torque and force required for angular motion of the elbow joint are calculated using forward dynamics. The results show that the muscle forces required to generate an elbow flexion are considerably less when the exoskeleton is worn. Clinical Relevance--- The exoskeleton assists patients to extend and flex their arm, thus supporting rehabilitation and arm function during activities of daily living. Exoskeleton movement is derived from residual myoelectric signals extracted from the patient's arm muscles. Modelling the dynamics and kinematics of the arm with the exoskeleton can reveal and predict any movement issues that need to be addressed.