Modelling of the achilles and patella tendon forces during treadmill running.
Date
2021-03
Authors
Journal Title
Journal ISSN
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Publisher
Stellenbosch : Stellenbosch University
Abstract
ENGLISH ABSTRACT: Tendons are dense connective tissue bands which attach muscle to bone, and facilitate the movement of the musculoskeletal system during locomotion. Although tendon loading during running is one of several biomechanical factors that have been linked to economical running gait and performance (Moore, 2012; Moore et al., 2014; Moore,2016), it has not been widely researched. Traditionally,in-vivo measurement techniques are used to quantify dynamic tendon loads; however, these experimental procedures are expensive and high-risk. In-silico gait analysis workflows and musculoskeletal modelling platforms allow researchers to non-invasively investigate the relationship between body motion and internal biomechanical loads during locomotion (Wilke and Galbusera,2018). The following study is a continuation of a previous Masters project (Groeneveld,2020), and aimed to develop and investigate an open-source, subject non-specific in-silico method which may be used to estimate the dynamic loading profiles of the Achilles and patella tendons during treadmill running. The robustness and reliability of the developed in-silicomethod was also examined. It is important to note that the raw experimental data sets used throughout this study were captured during the previous study (Groeneveld, 2020).
The developed in-silico method comprises of pre-existing (Hamneret al., 2010) and modified OpenSim musculoskeletal models, as well as a fully automated gait analysis pipeline. In addition to the generic implementations of the Achilles and patella tendons(Hamneret al., 2010), a modified variation of the Achilles tendon, and three modified variations of the patella tendon, were adapted from literature (Arnoldet al., 2010;Schmitz and Piovesan, 2016; Rajagopalet al., 2016; Laiet al., 2017) and investigated.Two-samplet-tests (Pataky, 2012) were used to examine the robustness of the modified models (with respect to the modifications realized within them) and found that the implemented modifications did not significantly impact model accuracy.
The processing pipeline was programmed in Python and utilized the OpenSim-Python API feed to implement a generic running gait analysis workflow. The analysis workflow comprised of five processes, namely: Scaling, Inverse Kinematics, Residual Reduction Algorithm, Computed Muscle Control, and Muscle Analysis. Additionally, the pipeline incorporated a novel pre-analysis data processing functionality and post-analysis results processing method. The study utilized the in-silico method to investigate 5 participants,running on 3 gradient-variant surfaces, namely: level (0◦), incline (9◦), and decline (-9◦)surfaces. To investigate the reliability of the resulting in-silico tendon loads, a comparison between the normalized trends observed in the in-silico and corresponding in-vivo tendon loads (Groeneveld, 2020), was realized. Notably, the modified tendon implementations out-performed the original variations (Hamneret al., 2010).
The study concluded that subject non-specific modelling and gait analysis techniques may be used to achieve reasonable estimations of the dynamic loading profiles of the Achilles tendon during level, incline, and decline running conditions. Realizing reason-able approximations for the patella tendon proved to be challenging, as the developed method did not account for subject-specific quadriceps muscle activity during locomotion. Additionally, the study concluded that the resulting in-silico method is best suited for level running gait analyses.
ENGLISH ABSTRACT: Raadpleeg teks vir opsomming
ENGLISH ABSTRACT: Raadpleeg teks vir opsomming
Description
Thesis (MEng)--Stellenbosch University, 2021.
Keywords
Musculoskeletal system, Achilles tendon, Running -- Gait analysis, Patella tendon, UCTD, Tendons