Abstract
Abrupt deceleration is a common practice in several sports, where sudden changes of direction are needed to perform at the highest level. The aim of this study is the comparison between static and dynamic optimization methods for muscle force estimation using a musculoskeletal modelling approach. Six elite male indoor elite athletes participated in this work. Musculoskeletal models, consisting of 12 segments, 23 degrees of freedom and 92 musculotendon actuators was used. Kinematic and kinetic data were collected at 300 Hz using 8 infrared cameras (Qualisys) and 2 force plates (Kistler). Muscle forces were attained through OpenSim. Similarities between force estimations using static optimization (SO) and computed muscle control (CMC) were quantified using a correlation coefficient. Stronger correlations occurred along the muscles Vasti (0.712 ± 0.292), Gluteus Maximus (0.619 ± 0.277), Soleus (0.755 ± 0.255) and Erector Spinae (0.855 ± 0.150). These muscles only span one joint. Moderate to weak correlations arise when comparing both methods in biarticular muscles, such as the hamstrings (0.422 ± 0.475), Rectus Femoris (0.356 ± 0.404), Gastrocnemius (0.325 ± 0.387), with the Tibialis Anterior (−0.211 ± 0.321) showing a weak negative correlation. muscles synergies are in agreement with the joint moments and measured kinematic data. Both SO and CMC predicted similar results in terms of force profile and magnitudes during an abrupt A/P deceleration task, albeit caution must be taken when biarticular muscles, such as the hamstrings or gastrocnemius, are concerned, so CMC might be the better choice.
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This work was supported by CIPER-FCT (PEST-OE/SAU/UI447/2014 & UID/DTP/00447/2013).
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Mateus, R., João, F., Veloso, A.P. (2020). Differences Between Static and Dynamical Optimization Methods in Musculoskeletal Modeling Estimations to Study Elite Athletes. In: Ateshian, G., Myers, K., Tavares, J. (eds) Computer Methods, Imaging and Visualization in Biomechanics and Biomedical Engineering. CMBBE 2019. Lecture Notes in Computational Vision and Biomechanics, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-030-43195-2_52
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