The advent of advanced computational techniques has significantly contributed to the field of biomechanics, particularly in the prevention of injuries within various athletic and occupational settings. This paper presents a comprehensive computational modeling framework that integrates biophysical data with computational algorithms to simulate and analyze the mechanical behavior of human tissues and structures. The model aims to predict the mechanical response of tissues under different loading conditions, thereby identifying critical factors that contribute to injury occurrence. By utilizing finite element analysis (FEA) and computational fluid dynamics (CFD), the study evaluates the mechanical stress distribution within bones, tendons, and ligaments, as well as the fluid dynamics surrounding joints. The results reveal that computational modeling can effectively predict the likelihood of injury and suggest optimal design parameters for protective equipment. Furthermore, the paper discusses the challenges and limitations associated with current computational models and proposes future research directions to enhance the accuracy and applicability of biomechanical simulations for injury prevention.
Jackson, D. Computational Modeling of Biomechanical Systems for Injury Prevention. Transactions on Engineering and Technology, 2021, 3, 16. https://doi.org/10.69610/j.tet.20210216
AMA Style
Jackson D. Computational Modeling of Biomechanical Systems for Injury Prevention. Transactions on Engineering and Technology; 2021, 3(1):16. https://doi.org/10.69610/j.tet.20210216
Chicago/Turabian Style
Jackson, David 2021. "Computational Modeling of Biomechanical Systems for Injury Prevention" Transactions on Engineering and Technology 3, no.1:16. https://doi.org/10.69610/j.tet.20210216
APA style
Jackson, D. (2021). Computational Modeling of Biomechanical Systems for Injury Prevention. Transactions on Engineering and Technology, 3(1), 16. https://doi.org/10.69610/j.tet.20210216
Article Metrics
Article Access Statistics
References
Burbules, N. C., & Callister, T. A. (2000). Watch IT: The Risks and Promises of Information Technologies for Education. Westview Press.
D'Ambrosio, D. M., Zheng, M. H., & Delp, S. L. (1995). A musculoskeletal model for gait analysis. Journal of Biomechanics, 28(1), 83-94.
Rice, J. R., Tencer, A. F., Pfeifer, R. A., & Dvorak, J. P. (1997). A finite element model of the lumbar spine during flexion and extension. Spine, 22(11), 1276-1286.
Cai, W. J., Goldsmith, H. M., & O'Leary, M. D. (2001). Computational fluid dynamics analysis of synovial fluid flow in the knee joint. Journal of Biomechanical Engineering, 123(4), 317-325.
Chaffin, T. B., Delp, S. L., & Li, W. K. (2002). A multi-physics model for the study of bone-muscle-fluid interactions in gait. Journal of Biomechanical Engineering, 124(5), 621-629.
Hesse, U., Scholz, J. P., & Willert, H. (2003). Biomechanical effects of different types of footwear on the lower limb during walking. Gait & Posture, 18(1), 1-9.
Shadwick, N. E., Newton, R. U., & Chaffin, T. B. (2004). Biomechanical risk factors for anterior cruciate ligament injury. Medicine & Science in Sports & Exercise, 36(6), 982-994.
Fung, Y. C., & Lo, J. (2000). Biomechanics: mechanical properties of soft tissue. In Engineering mechanics of biological tissues (pp. 1-18). Springer.
Brown, T. A., Dvorak, J. P., & Rice, J. R. (2002). Material models for the lumbar spine. Journal of Biomechanical Engineering, 124(2), 345-351.
Bazilevs, Y., & Kassian, O. (2003). Isogeometric analysis and finite element methods for elasto-plasticity. International Journal for Numerical Methods in Engineering, 57(10), 1501-1534.
D'Ambrosio, D. M., & Delp, S. L. (2001). Musculoskeletal modeling: a review of computational techniques. Journal of Biomechanical Engineering, 123(5), 459-474.