Biomechanical Modeling in Physical Therapy: Advancing the Science of Movement to Improve Patient Outcomes
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V1I2P102Keywords:
Biomechanical modeling, physical therapy, Movement, Rehabilitation, Injury preventionAbstract
Biomechanical modeling has emerged as a pivotal tool in physical therapy, enhancing the understanding of human movement and its implications for patient recovery. This modeling involves the application of principles from biomechanics to analyze and optimize movement patterns, which can significantly improve rehabilitation outcomes. By utilizing advanced technologies such as 3D motion capture and real-time biofeedback, therapists can gain insights into joint ranges of motion (ROM) and muscle dynamics during various activities. These analyses help identify underlying causes of pain and dysfunction, allowing for tailored treatment plans that address specific biomechanical issues. The integration of biomechanical modeling into physical therapy not only aids in injury prevention but also enhances the efficacy of rehabilitation programs. For instance, by assessing gait patterns and postural alignment, therapists can detect abnormalities that may lead to overuse injuries or chronic pain. Furthermore, biomechanical assessments enable practitioners to develop personalized exercise regimens aimed at strengthening weak muscles, improving flexibility, and correcting faulty movement patterns. In conclusion, biomechanical modeling represents a transformative approach in physical therapy, facilitating a deeper understanding of movement mechanics and promoting better patient outcomes through customized interventions
References
1. Zatsiorsky, V. M., & Prilutsky, B. I. (2012). Biomechanics of skeletal muscles. Human Kinetics.
2. Winter, D. A. (2009). Biomechanics and motor control of human movement (4th ed.). Wiley.
3. Robertson, D. G. E., Caldwell, G. E., Hamill, J., Kamen, G., & Whittlesey, S. (2013).
4. Delp, S. L., Anderson, F. C., Arnold, A. S., Loan, P., Habib, A., John, C. T., ... & Thelen, D. G. (2007). OpenSim: Opensource software to create and analyze dynamic simulations of movement. IEEE Transactions on Biomedical Engineering, 54(11), 1940-1950.
5. Rajagopal, A., Dembia, C. L., Demers, M. S., Delp, D. D., Hicks, J. L., & Delp, S. L. (2016). Full-body musculoskeletal model for muscle-driven simulation of human gait. IEEE Transactions on Biomedical Engineering, 63(10), 2068-2079.
6. Ackermann, M., & van den Bogert, A. J. (2010). Predictive simulation of gait at low speeds: Implications for orthotic design. Medical Engineering & Physics, 32(4), 326-333.
7. Seth, A., Sherman, M., Reinbolt, J. A., & Delp, S. L. (2011). OpenSim: A musculoskeletal modeling and simulation framework for in silico investigations and exchange. Procedia IUTAM, 2, 212-232.
8. Liew, B. X. W., Morris, S., Netto, K., & Rubenson, J. (2017). Joint-level mechanics of the human lower limb during walking and running throughout the lifespan. Journal of Biomechanics, 55, 1-10.
9. Mokhtarzadeh, H., Yeow, C. H., Goh, J. C. H., & Oetomo, D. (2014). Development of a subject-specific musculoskeletal model of the lower limb in gait analysis. Computer Methods in Biomechanics and Biomedical Engineering, 17(6), 595-600.
