A computational musculoskeletal model of the human elbow and forearm in the analysis of ballistic movements

This dissertation describes the development and evaluation of a musculoskeletal model of the elbow joint complex (EJC) that represents human elbow flexion-extension and forearm pronation-supination. This study showed that EJC movements can be accurately modeled when the kinematics, kinetics, musculotendon characteristics, and muscle excitation patterns are precisely represented. Eight musculotendon actuators were represented at the EJC. The length, velocity, and moment arm for each of the eight musculotendon actuators were based on skeletal anatomy and joint position. Previously determined musculotendon parameters and skeletal geometry were utilized in the musculoskeletal model for the analysis of ballistic (rapid-directed) elbow joint complex movements. The key objective was to develop a computational model, guided by parameterized optimal control, to investigate the relationship among patterns of muscle excitation and kinematics, and to determine the effects of forearm and elbow position on the recruitment of individual muscles during a variety of ballistic movements. An extension of this model also characterized the function and movement of the elbow and forearm system by using processed electromyography (EMG) as the model driver. The model was verified using data from two volunteer subjects performing sixteen tasks that involved combinations of ballistic elbow flexion-extension and forearm pronation-supination. The testing and evaluation stage included electrogoniometer recordings of arm kinematics in conjunction with calibrated EMG recordings for numerical analysis. The modeling results showed (1) muscles which cross the EJC are affected in their recruitment by the orientation of the joint, (2) no fixed synergistic muscle recruitment was observed, (3) recruitment of the flexor muscles are most affected by the orientation of the EJC while recruitment of the extensor muscles are least affected, (4) Anconeus muscle activation likely represents its role in stabilization of the EJC, (5) for particular movements, the model results showed how it could be advantageous to activate a muscle that is antagonist to the movement desired in order to further minimize the final movement time, (6) triphasic patterns were demonstrated in the solutions predicted, and (7) an EMG signal processing scheme provided not only the trend but also the general magnitude of EJC movements when used to drive the model