Prediction of muscle force involved in shoulder internal rotation.

Abstract

The estimation of shoulder muscle force is important to understand the mechanism of rotator cuff injury. In general, mean parameter values are used as input for computational models. However, anatomic and biomechanical parameters vary widely among people. The purpose of this study was to evaluate shoulder muscle forces predicted by an electromyography-driven muscle model given neuromuscular parameters generated by Monte Carlo simulation. Normal distributions were used to model muscle moment arms; electromyographic and muscle physiological cross-sectional area data were modeled with log-normal distributions. Eight muscles were included in the model. Muscle force and joint moment were predicted on the basis of the simulated parameters. The results showed that the subscapularis and pectoralis major were substantial actuators for shoulder internal rotation. During maximum voluntary contraction the median of the muscle forces of the subscapularis and the pectoralis major were 1030 N and 462 N, respectively. This study demonstrated that the Monte Carlo method could be used for muscle force prediction by integrating population variability of physiological parameter into a biomechanical muscle model.