Abstract
Biomechanical analyses provide an extensive source of data that are deeply explored by physicians, engineers and trainers from the mechanical and physiological point of view. This data includes kinetic and kinematic parameters that are quite useful to study human locomotion. However, most of these analyses stay on a very superficial level. Recently data and computational science expanded their coverage to new areas and new analysis tools are available. These analyses include the use of machine learning tools for data mining processes. All of these new tools open a total new level of data analysis, thus newer and deeper questions are proposed in order to provide more accurate prediction results with strict decision support. On the other hand, Squat is an exercise widely used for physical conditioning since it puts into operation various muscles at the same time of the lower and upper train. However bad squatting could drive to injuries at the back and knee level. These injuries are especially common in patients without physical conditioning. In this study, squat data is analyzed using Self-Organizing Maps (SOM) to identify possible relevant parameters from the subjects that could affect the movement performance especially at the knee joint.
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References
Caicedo Bravo, E.F., Lopez Sotelo, J.A.: Una Aproximación Práctica a Las Redes Neuronales Artificiales. Cali, Colombia (2017)
Lamb, P., Bartlett, R.: Self-organizing maps as a tool to analyze movement variability. Int. J. Comput. Sci. Sport. 7, 28–39 (2008)
Rodrigo, S.E., Lescano, C.N., Rodrigo, R.H.: Application of Kohonen maps to kinetic analysis of human gait. Rev. Bras. Eng. Biomédica 28, 217–226 (2012)
Serrien, B., Blondeel, J., Clijsen, R., Goossens, M., Baeyens, J.-P.: Analysis of 3D motion patterns with self-organising maps (SOM) and statistical parametric mapping (SPM): a methodological proposal. Comput. Methods Biomech. Biomed. Eng. 17, 162–163 (2014)
Hoerzer, S., Jacob, C.: Defining functional groups in biomechanics using self-organizing maps, pp. 1–11 (2015)
Hoerzer, S., von Tscharner, V., Jacob, C., Nigg, B.M.: Defining functional groups based on running kinematics using self-organizing maps and support vector machines. J. Biomech. 48, 2072–2079 (2015)
Chulvi Medrano, I.: Revisión narrativa del rol de la sentadilla en los programas de acondicionamiento neuromuscular y rehabilitación TT - Narrative review of the role of the squatting in neuromuscular conditioning and rehabilitation programs (2009)
Braidot, A.A., Brusa, M.H., Lestussi, F.E., Parera, G.P.: Biomechanics of front and back squat exercises. J. Phys. Conf. Ser. 90, 012009 (2007)
Mirzaei, B., Nia, F.R., Saberi, Y.: Comparison of 3 different rest intervals on sustainability of squat repetitions with heavy vs. light loads. Brazilian J. Biomotricity 2, 220–229 (2008)
Escamilla, R.F., et al.: Effects of technique variations on knee biomechanics during the squat and leg press. Med. Sci. Sports Exerc. 33, 1552–1566 (2001)
Escamilla, R.F.: Knee biomechanics of the dynamic squat exercise. Med. Sci. Sports Exerc. 33, 127–141 (2001)
Miguel, A., Pereira, N.V.: Comparación entre la Sentadilla y la “Sentadilla a una pierna con Pié lastrado” con respecto a la Actividad Electromiográfica, la Fuerza Resultante y la Sobrecarga (2006)
Ariel, B.G.: Biomechanical analysis of the knee joint during deep knee bends with heavy load. Biomechanics IV, 44–52 (2016)
Myer, G.D., et al.: The back squat: a proposed assessment of functional deficits and technical factors that limit performance. Strength Cond. J. 36, 4–27 (2014)
Kanungo, T., Mount, D.M., Netanyahu, N.S., Piatko, C.D., Silverman, R., Wu, A.Y.: An efficient k-means clustering algorithm: analysis and implementation. IEEE Trans. Pattern Anal. Mach. Intell. 24, 881–892 (2002)
Slater, L.V., Hart, J.M.: Muscle activation patterns during different squat techniques. J. Strength Cond. Res. 31, 667–676 (2017)
Gullett, J.C., Tillman, M.D., Gutierrez, G.M., Chow, J.W.: A biomechanical comparison of back and front squats in healthy trained individuals. J. Strength Cond. Res. 23, 284–292 (2009)
Ostermann, M., et al.: How to squat? Effects of various stance widths, foot placement angles and level of experience on knee, hip and trunk motion and loading. BMC Sports Sci. Med. Rehabil. 10, 14 (2018)
Diggin, D., et al.: A biomechanical analysis of front versus back squat: injury implications kinematic differences occurring between both front squat and back squat techniques using 2D video analysis. Biomech. Sport. 11, 643–646 (2011)
Lander, J.E., Bates, B.T., Devita, P.: Biomechanics of the squat exercise using a modified center of mass bar. Med. Sci. Sports Exerc. 18, 469–478 (1986)
Gawda, P., Zawadka, M., Skublewska-Paszkowska, M., Smołka, J., Łukasik, E.: Biomechanics of the squat in rehabilitation and sports training. Med. Sport./Polish J. Sports Med. 24, 87–96 (2017)
Schoenfeld, B.J.: Squatting kinematics and kinetics and their application to exercise performance. J. Strength Cond. Res. 24, 3497–3506 (2010)
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Authors want to thank to the Universidad Antonio Nariño for all the financial support to this work under Project number 2017217.
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Plazas Molano, A.C., Jaramillo-Isaza, S., Orjuela-Cañon, Á.D. (2019). Self-Organized Maps for the Analysis of the Biomechanical Response of the Knee Joint During Squat-Like Movements in Subjects Without Physical Conditioning. In: Figueroa-García, J., Duarte-González, M., Jaramillo-Isaza, S., Orjuela-Cañon, A., Díaz-Gutierrez, Y. (eds) Applied Computer Sciences in Engineering. WEA 2019. Communications in Computer and Information Science, vol 1052. Springer, Cham. https://doi.org/10.1007/978-3-030-31019-6_29
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