Biomechanics of the run-up and take-off of track and field athletes based on linear regression and factor analysis
Abstract
The current biomechanical analysis of track and field athletes during run-up and take-off suffers from large errors and poor accuracy in analyzing the relationship between biomechanical variables. To address this problem, this study used the factor analysis model to optimize the linear regression model and analyzed the biomechanics of track and field athletes at different levels based on the optimized model. To verify the new performance of the optimized model, the study compared the model with other models in a comparative test. The outcomes indicated that the prediction accuracy of the model reached 97.6%, and the model took only 1.2s to predict. The model’s data detection completeness rate reached 100%, and all the performances were better than other models. The model was then used to analyze the biomechanics during run-up and take-off of athletes of different levels. The analysis results showed that during the run-up and take-off process, the horizontal velocity of the athlete’s center of mass first decreased, then increased, and finally decreased again. The maximum horizontal velocity of the national first-class athlete’s center of mass was 8.62 m/s. Moreover, the relative center of mass height of athletes gradually increased during the run-up and take-off process. Furthermore, the relative center of mass height of national level athletes reached up to 0.72%, while the reaction force of national level athletes was slightly lower than that of other athletes. It is clear from the aforementioned findings that the suggested optimization model is capable of precisely analyzing track and field players’ biomechanics during run-up and takeoff.
References
1. Teng S, Hu X, Deng P, Li B, Li Y, Ai Y. Motion planning for autonomous driving: The state of the art and future perspectives. IEEE Transactions on Intelligent Vehicles, 2023, 8(6): 3692-3711.
2. Prasetiyo A, Nugroho R A, Bastian A A. Physical Condition of Athletes of the All Indonesian Athletics Association, Pesawaran Regency. JOURNAL RESPECS (Research Physical Education and Sports), 2023, 5(2): 399-405.
3. Kluch Y, Wright-Mair R, Swim N, Turick R. “It’s like being on an island by yourself”: Diversity, equity, and inclusion administrators’ perceptions of barriers to diversity, equity, and inclusion work in intercollegiate athletics. Journal of Sport Management, 2022, 37(1): 1-14.
4. Lee K. The relationship of trunk muscle activation and core stability: a biomechanical analysis of pilates-based stabilization exercise. International journal of environmental research and public health, 2021, 18(23): 12804.
5. Trasolini N A, Nicholson K F, Mylott J, Bullock G S. Biomechanical analysis of the throwing athlete and its impact on return to sport. Arthroscopy, Sports Medicine, and Rehabilitation, 2022, 4(1): 83-91.
6. Ernstbrunner L, El Nashar R, Favre P, Bouaicha S, Wieser K, Gerber C. Chronic pseudoparalysis needs to be distinguished from pseudoparesis: a structural and biomechanical analysis. The American journal of sports medicine, 2021, 49(2): 291-297.
7. Colella R, Tumolo M R, Sabina S, Leo C G, Mincarone P, Guarino R. Design of UHF RFID sensor-tags for the biomechanical analysis of human body movements. IEEE sensors Journal, 2021, 21(13): 14090-14098.
8. Lempke L B, Oh J, Johnson R S, Schmidt J D, Lynall R C. Single-versus dual-task functional movement paradigms: a biomechanical analysis. Journal of sport rehabilitation, 2021, 30(5): 774-785.
9. Rios-Avila F, Maroto M L. Moving beyond linear regression: Implementing and interpreting quantile regression models with fixed effects. Sociological Methods & Research, 2024, 53(2): 639-682.
10. Singh P, Adebanjo A, Shafiq N, et al. Development of performance-based models for green concrete using multiple linear regression and artificial neural network. International Journal on Interactive Design and Manufacturing (IJIDeM), 2024, 18(5): 2945-2956.
11. Wellendorf A, Tichelmann P, Uhl J. Performance Analysis of a Dynamic Test Bench Based on a Linear Direct Drive. Archives of Advanced Engineering Science, 2023, 1(1):55-62.
12. Yıldırım M, Güler A. Factor analysis of the COVID-19 perceived risk scale: A preliminary study. Death studies, 2022, 46(5): 1065-1072.
13. Le Toquin B, Schipman J, De Larochelambert Q. Is the visual impairment origin a performance factor? Analysis of international-level para swimmers and para athletes. Journal of Sports Sciences, 2022, 40(5): 489-497.
14. Imhoff F B, Comer B, Obopilwe E, Beitzel K, Arciero R A, Mehl J T. Effect of slope and varus correction high tibial osteotomy in the ACL-deficient and ACL-reconstructed knee on kinematics and ACL graft force: a biomechanical analysis. The American journal of sports medicine, 2021, 49(2): 410-416.
15. Zhang H, Dong G, Wang J, Zhang T L, Meng X, Yang D. Understanding and extending the geographical detector model under a linear regression framework. International Journal of Geographical Information Science, 2023, 37(11): 2437-2453.
16. Li X, Hu Y, Li C, Yang X, Jiang T. Sparse estimation via lower-order penalty optimization methods in high-dimensional linear regression. Journal of Global Optimization, 2023, 85(2): 315-349.
17. Griffiths M D, Pakpour A H, Mamun M A. Correction to: psychometric validation of the bangla fear of covid-19 scale: confirmatory factor analysis and rasch analysis. International journal of mental health and addiction, 2022, 20(4): 2520-2522.
18. D’Urso E D, De Roover K, Vermunt J K, Tijmstra J. Scale length does matter: Recommendations for measurement invariance testing with categorical factor analysis and item response theory approaches. Behavior Research Methods, 2022, 54(5): 2114-2145.
19. Zou D, Yue L, Fan Z, Zhao Y, Leng H, Sun Z, Li W. Biomechanical analysis of lumbar interbody fusion cages with various elastic moduli in osteoporotic and non-osteoporotic lumbar spine: a finite element analysis. Global Spine Journal, 2024, 14(7): 2053-2061.
20. Roupa I, da Silva M R, Marques F, Gonçalves S B, Flores P. On the modeling of biomechanical systems for human movement analysis: a narrative review. Archives of Computational Methods in Engineering, 2022, 29(7): 4915-4958.
21. Hu L, Liu L, Zhao K. [Retracted] Biomechanics of Volleyball Players’ Run‐Up and Take‐Off Link under Deep Learning. Computational intelligence and neuroscience, 2022, 2022(1): 8409626-8409634.
22. Van Oeveren B T, de Ruiter C J, Beek P J, van Dieën J H. The biomechanics of running and running styles: a synthesis. Sports biomechanics, 2024, 23(4): 516-554.
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