The aim of this study was to determine the relative contributions of the deltoid and rotator cuff muscles to glenohumeral joint stability during arm abduction. A three-dimensional model of the upper limb was used to calculate the muscle and joint-contact forces at the shoulder for abduction in the scapular plane. The joints of the shoulder girdle-sternoclavicular joint, acromioclavicular joint, and glenohumeral joint-were each represented as an ideal three degree-of-freedom ball-and-socket joint. The articulation between the scapula and thorax was modeled using two kinematic constraints. Eighteen muscle bundles were used to represent the lines of action of 11 muscle groups spanning the glenohumeral joint. The three-dimensional positions of the clavicle, scapula, and humerus during abduction were measured using intracortical bone pins implanted into one subject. The measured bone positions were inputted into the model, and an optimization problem was solved to calculate the forces developed by the shoulder muscles for abduction in the scapular plane. The model calculations showed that the rotator cuff muscles (specifically, supraspinatus, subscapularis, and infraspinatus) by virtue of their lines of action are perfectly positioned to apply compressive load across the glenohumeral joint, and that these muscles contribute most significantly to shoulder joint stability during abduction. The middle deltoid provides most of the compressive force acting between the humeral head and the glenoid, but this muscle also creates most of the shear, and so its contribution to joint stability is less than that of any of the rotator cuff muscles.

The objectives of this chapter are as follows. First, a background in anatomy and biomechanics of the shoulder complex is presented to provide a brief review of the essential functions of the shoulder. Second, important features of practical shoulder models are discussed with reference to capabilities of current computational modelling techniques. Third, techniques in computational modelling of the shoulder complex are compared and contrasted for their effectiveness in representing shoulder biomechanics in situ, with some sample calculations included. Fourth, in vivo and in vitro techniques for verifying computational models will be briefly reviewed. Finally, a summary of emerging trends will indicate the clinical impact that computational modelling can be expected to have in progressing our understanding of shoulder complex movement and its fundamental biomechanics.

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