Extrapolation of an empirical elbow muscle co-activation relationship to a novel task set: implications for predictions of individual muscle demands.

Biomechanical optimisation models applying efficiency-based objective functions often underestimate antagonist contributions. Previous work has quantified an empirical co-activation relationship in the elbow musculature, demonstrating that implementing this relationship as a constraint in an elbow muscle force prediction model improves muscle force predictions. The current study evaluated this modified model by extrapolating the co-activation relationship to 36 novel isometric unilateral, right-handed exertions, including those requiring greater intensity of effort and performed in different postures. Surface electromyography was recorded from the elbow flexors and extensors. Novel extrapolative co-activation relationships were developed and used as constraints in a muscle force prediction model. Model predictions using both constraints were compared with empirical biophysical data. Predictions by the modified model were more consistent with biophysical data than those by the original model for the novel exertions. Novel co-activation relationships did not further enhance predictions when compared with the previous relationship, suggesting that extrapolation of the previous relationship is feasible.

Analysis of the influence of rotator cuff impingements on upper limb kinematics in an elderly population during activities of daily living.

BACKGROUND: Despite a high prevalence of rotator cuff impingements or tears in the elderly population, little research has focused on how this injured population adapts to perform tasks of daily living. The current study investigated the influence of rotator cuff impingements in this population on kinematics and shoulder loading differences, while completing activities of daily living. METHODS: Upper limb and trunk movement was measured for thirteen asymptomatic elderly and ten elderly subjects with rotator cuff impingements during five range of motion tasks and six activities of daily living. Thoracohumeral kinematics was derived from this data. FINDINGS: Symptomatic populations showed significantly decreased ranges of flexion/extension, abduction and internal and external rotation when compared to the asymptomatic population. The asymptomatic population had a 44% larger range of angle of elevation than the symptomatic population. Task was found to be a main effect for most variables examined including angle of elevation. Participants with impingements had significantly lower ranges of humeral rotations during the tasks with ranges of 40° (SD 40°) and 51° (SD 36°) respectively. Perineal care, hair-combing and reaching tasks were the most demanding in terms of the required range of motion. The reaching tasks resulted in the highest shoulder moment. INTERPRETATION: Developing adaptations for perineal care, hair-combing and reaching tasks should be prioritized when working with persons with rotator cuff impingements, as these tasks demanded the largest ranges of motion while producing high shoulder moments. Substantial differences existed between the experimental groups for a number of kinematic measures.

The utility of an empirically derived co-activation ratio for muscle force prediction through optimization.

Biomechanical optimization models that apply efficiency-based objective functions often underestimate or negate antagonist co-activation. Co-activation assists movement control, joint stabilization and limb stiffness and should be carefully incorporated into models. The purposes of this study were to mathematically describe co-activation relationships between elbow flexors and extensors during isometric exertions at varying intensity levels and postures, and secondly, to apply these co-activation relationships as constraints in an optimization muscle force prediction model of the elbow and assess changes in predictions made while including these constraints. Sixteen individuals performed 72 isometric exertions while holding a load in their right hand. Surface EMG was recorded from elbow flexors and extensors. A co-activation index provided a relative measure of flexor contribution to total activation about the elbow. Parsimonious models of co-activation during flexion and extension exertions were developed and added as constraints to a muscle force prediction model to enforce co-activation. Three different PCSA data sets were used. Elbow co-activation was sensitive to changes in posture and load. During flexion exertions the elbow flexors were activated about 75% MVC (this amount varied according to elbow angle, shoulder flexion and abduction angles, and load). During extension exertions the elbow flexors were activated about 11% MVC (this amount varied according to elbow angle, shoulder flexion angle and load). The larger PCSA values appeared to be more representative of the subject pool. Inclusion of these co-activation constraints improved the model predictions, bringing them closer to the empirically measured activation levels.