Dynamic Spatial Tuning Patterns of Shoulder Muscles with Volunteers in a Driving Posture

Abstract

Computational human body models (HBMs) of drivers for pre-crash simulations need active shoulder muscle control, and volunteer data are lacking. The goal of this paper was to build shoulder muscle dynamic spatial tuning patterns, with a secondary focus to present shoulder kinematic evaluation data. 8M and 9F volunteers sat in a driver posture, with their torso restrained, and were exposed to upper arm dynamic perturbations in eight directions perpendicular to the humerus. A dropping 8-kg weight connected to the elbow through pulleys applied the loads; the exact timing and direction were unknown. Activity in 11 shoulder muscles was measured using surface electrodes, and upper arm kinematics were measured with three cameras. We found directionally specific muscle activity and presented dynamic spatial tuning patterns for each muscle separated by sex. The preferred directions, i.e. the vector mean of a spatial tuning pattern, were similar between males and females, with the largest difference of 31° in the pectoralis major muscle. Males and females had similar elbow displacements. The maxima of elbow displacements in the loading plane for males was 189 ± 36 mm during flexion loading, and for females, it was 196 ± 36 mm during adduction loading. The data presented here can be used to design shoulder muscle controllers for HBMs and evaluate the performance of shoulder models.

Development and verification of a physiologically motivated internal controller for the open-source extended Hill-type muscle model in LS-DYNA

“…A similar approach for the neck muscles is taken in the VIVA OpenHBM model, which has implemented angular position feedback (APF) and muscle length feedback (MLF) controllers with optimised gains but no additional controllers for other body regions (Putra et al 2020 ). The SAFER HBM (Östh et al 2015 ), in addition to the full-body omni-directional APF and MLF closed-loop controllers (Ólafsdóttir et al 2019 ), has a dedicated shoulder muscle feedback controller to model the load transfer from the steering wheel to the torso, which was added recently (Fice et al 2021 ). The model uses PID controllers to govern the angles between body parts and selected muscle lengths in the neck and upper extremity regions.…”