Shuo Liu, Jianying Li, and Lei Zhang*. Modeling and Simulation of Human Muscle Tissue Development in Biomechanics Based on Wavelet Neural Network Algorithm. Dynamic Systems and Applications 29 (2020) No. 4, 1660 – 1681

https://doi.org/10.46719/dsa202029448

ABSTRACT.
Human motion is one of the most complex phenomena in nature. Individual differences, diversity and limitations of in vivo experiments make it very difficult to carry out research on human biological characteristics. In order to explore the mechanical characteristics of human muscle work, reveal the mechanical regularity of motion, and find out the existing problems in sports biomechanics. A more suitable body motion system for biomechanics is designed. The wavelet neural network algorithm and the energy equation theory are used to obtain the influence relationship between wavelet neural network and human mechanics. The neural network theory is combined with the neural network theory to construct the muscle simulation model from the perspective of biological force. The simulation results show that the proposed method has high accuracy and provides an effective scientific basis for better study of the biomechanics of human muscle tissue system. Therefore, the wavelet neural network algorithm can be effectively applied to human muscle modeling, providing a new way for human muscle modeling.

Keywords: Wavelet neural network algorithm; biomechanics; human muscle tissue; modeling