Physically correlated muscle activation for a human head and neck computational model
Document Type
Article
Publication Date
8-18-2005
Publication Title
Computer Methods in Biomechanics and Biomedical Engineering
Abstract
A computational 50th percentile male head and neck complex model was correlated to physical experimental data. The computational model utilizes 15 muscle pairs represented by the Hill Muscle Model with the complete head/neck system modeled using MADYMO™. The model was used for analysis and optimization of activation and deactivation of muscle activity in flexion and extension. Sensitivity analysis performed using the model shows that, of the multiple parameters within the Hill Model, activation level and timing prove to have the greatest effect on the system kinematics. In addition, the rate by which an activation level is changed becomes an important factor in the simulation. With the use of numerical optimization techniques, a pattern was determined for the applied activation/deactivation rates and timing of flexors and extensors during flexion and extension of the head. The numerical optimization result correlated to within 9% of measured value during the initial flexion of the head. The optimized activation model reflected an activation onset 90 ms after the start of the impulse load, which agrees with published reaction times of muscles. Activation and deactivation rates for the extensors were found to be 1.7 and 0.29%, respectively. While the onset of activation of the flexor muscles occurred before rebound, it was found that muscles, at near the mid-plane, were triggered by the optimized model to abate the flexion. Rates of activation and deactivation of the flexors were found to be 0.9 and 0.3%, respectively. Both the extensors as well as the flexors were found to activate only up to 70% before deactivating. Therefore, it was evident from this study that using the Hill Muscle Model with the activation parameter modeled as binary, 0 or 100%, may lead to inaccurate simulation results.
Volume
8
Issue
3
First Page
191
Last Page
199
DOI
10.1080/10255840500295829
ISSN
Print ISSN: 1025-5842 Online ISSN: 1476-8259
Rights
© 2005 Taylor & Francis.
Recommended Citation
Brelin-Fornari, Janet; Shah, Paras; and El-Sayed, Mohamed, "Physically correlated muscle activation for a human head and neck computational model" (2005). Mechanical Engineering Publications. 16.
https://digitalcommons.kettering.edu/mech_eng_facultypubs/16
