Journal
JOURNAL OF BIOMECHANICS
Volume 91, Issue -, Pages 51-60Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jbiomech.2019.05.001
Keywords
Lower limb; PID control; CMC control; Muscle activation; Finite element analysis
Categories
Funding
- National Natural Science Foundation of China [51875187, 51621004]
- Hunan Province Science and Technology Plan [2019JJ40021]
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Computational biomechanics for human body modeling has generally been categorized into two separated domains: finite element analysis and multibody dynamics. Combining the advantages of both domains is necessary when tissue stress and physical body motion are both of interest. However, the method for this topic is still in exploration. The aim of this study is to implement unique controlling strategies in finite element model for simultaneously simulating musculoskeletal body dynamics and in vivo stress inside human tissues. A finite element lower limb model with 3D active muscles was selected for the implementation of controlling strategies, which was further validated against in-vivo human motion experiments. A unique feedback control strategy that couples together a basic Proportion-Integration-Differentiation (PID) controller and generic active signals from Computed Muscle Control (CMC) method of the musculoskeletal model or normalized EMG singles was proposed and applied in the present model. The results show that the new proposed controlling strategy show a good correlation with experimental test data of the normal gait considering joint kinematics, while stress distribution of local lower limb tissue can be also detected in real-time with lower limb motion. In summary, the present work is the first step for the application of active controlling strategy in the finite element model for concurrent simulation of both body dynamics and tissue stress. In the future, the present method can be further developed to apply it in various fields for human biomechanical analysis to monitor local stress and strain distribution by simultaneously simulating human locomotion. (C) 2019 Elsevier Ltd. All rights reserved.
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