Abstract
Most upper-extremity musculoskeletal models represent the glenohumeral joint with an inherently stable ball-and-socket, but the physiological joint requires active muscle coordination for stability. The authors evaluated sensitivity of common predicted outcomes (instability, net glenohumeral reaction force, and rotator cuff activations) to different implementations of active stabilizing mechanisms (constraining net joint reaction direction and incorporating normalized surface electromyography [EMG]). Both EMG and reaction force constraints successfully reduced joint instability. For flexion, incorporating any normalized surface EMG data reduced predicted instability by 54.8%, whereas incorporating any force constraint reduced predicted instability by 43.1%. Other outcomes were sensitive to EMG constraints, but not to force constraints. For flexion, incorporating normalized surface EMG data increased predicted magnitudes of joint reaction force and rotator cuff activations by 28.7% and 88.4%, respectively. Force constraints had no influence on these predicted outcomes for all tasks evaluated. More restrictive EMG constraints also tended to overconstrain the model, making it challenging to accurately track input kinematics. Therefore, force constraints may be a more robust choice when representing stability.
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