In-vitro identification of shoulder joint and muscle dynamics based on motion capture and musculoskeletal computation.

Abstract

Dynamics properties of shoulder joint and muscle are experimentally identified under different musculoskeletal conditions for a digital human model with accurate dynamics. Passive swing motions of scapula and upper limb bones in cadaveric specimen with and without muscles are measured by an optical motion capture system. External forces that are applied to the scapula bone are simultaneously measured by a force plate. The dynamics identification process consists of 3 steps: 1) identify the inertial parameters of the cadaveric specimen with and without muscles respectively, 2) identify the viscosity of the glenohumeral joint from the specimen without muscles, and 3) identify the viscosity of the shoulder muscles from the specimen with muscles and the identified joint viscosity. These parameters are identified in six cadaveric specimens. Their joint viscosities are 5.33E-02 ± 1.33E-02 Nms/rad (without muscles) and 1.07E-01 ± 2.28E-02 Nms/rad (with muscle), and their muscle viscosities are 6.69E+02 ± 8.11E+02 Ns/m (mean ± SD). The identified joint viscosity corresponds with the literature value. This measurement and identification algorithm would improve the dynamics of the digital human model and realize the accurate muscle activity estimation and the motion simulation.