Idiopathic clubfoot causes severe deformity of the foot and lower leg. Due to the complex anatomy and small size of the foot, the condition is difficult to define and describe. This study focused on 3D modeling of different foot positions associated with clubfoot relapse, and investigation of muscle parameters. The 3D modeling was performed in the AnyBody Modeling System to retrieve information about muscle length. Musculoskeletal modeling could provide further understanding of the condition and contribute to assessment and treatment evaluation. Five children that received clubfoot treatment as infants, and five typically developing children, serving as a control group, participated in the study. Despite treatment with the Ponseti method, Achilles tenotomy and use of an abduction orthosis, all participants of the clubfoot group showed signs of relapse. In total, seven affected legs were studied. Data from gait analyses of all participants were compiled and interpreted in the AnyBody Modeling System. The Plug-in-Gait Model for lower extremities and the Oxford Foot Model were used as marker protocol for the study. Studied lower leg muscles were Gastrocnemius Lateralis, Gastrocnemius Medialis, Soleus Lateralis and Soleus Medialis. Muscle length, defined as length of contractile element, for each leg and participant were evaluated using the AnyBody model template LowerExtremity. Compared to the control group, the models of the clubfoot group presented shorter mean muscle lengths of all investigated muscles. / Idiopatisk klumpfot orsakar allvarlig deformation av fot och underben. På grund av fotens anatomi och ringa storlek kan tillståndet vara svårt att beskriva och definiera. Denna studie innefattade 3Dmodellering av olika fotpositioner orakade av recidivklumpfot, för att undersöka muskelegenskaper. AnyBody Modeling System användes för att generera 3D-modeller och ta fram information om muskellängd. Muskuloskeletal modellering skulle kunna öka förståelsen för sjukdomen och bidra till förbättringar av initial bedömning och utvärdering av behandling. Fem barn som behandlades för klumpfot efter födseln deltog i studien. Även fem typiskt utvecklade barn medverkade och fungerade som en kontrollgrupp. Trots behandling med Ponseti-metoden, hälseneförlängning och användning av abduktionsortos, uppvisade samtliga barn i klumpfotsgruppen tecken på återfall. Totalt studerades sju ben med recidivklumpfot. Data från gånganalyser av deltagarna sammanställdes och analyserades i AnyBody Modeling System. Plug-in-Gait Model för nedre extremiteter och Oxford Foot Model användes som markörprotokoll. Under studien analyserades underbensmusklerna Gastrocnemius Lateralis, Gastrocnemius Medialis, Soleus Lateralis och Soleus Medialis. Muskellängd (längd av kontraktilelement) för varje patient och ben beräknades med hjälp av modellmallen LowerExtremity i AnyBody Modeling System. Jämfört med kontrollgruppen visade klumpfotsgruppen kortare medelmuskellängder för samtliga av de analyserade musklerna.

A method of estimating subject specific muscle parameters of musculoskeletal models of elite athletes (skiers) was sought. Subject specific models are necessary due to large differences in general anatomy and physical performance of elite athletes relative the general population. Sought muscle parameters concern the force generating capabilities of muscles. The estimation was limited to only include the quadriceps-femoris and hamstring muscle groups due to these muscle having the highest influence on the performance of a skier. A modified interpretation of the method proposed by Heinen et al. [19] was implemented. The method includes experimental strength tests of knee extension and flexion muscles of a test subject, a musculoskeletal model of the experiments coupled with a mathematical optimisation minimisation formulation. The aim of the optimisation was to match the strength of a model to the experimentally obtained strength curve by minimising  error between the model and experimental results. The optimisation minimises the error between the model and the experimental data by varying the operating range and strength of the involved muscles. The musculo-tendon parameters are estimated through transformation equations, explicitly related to the design variables. Three healty and active males were involved in this study. An overall increase of the accuracy of the optimised model relative an unscaled reference model was observed, with the reduction of the objective function in a range of 80.2-92\% and a mean absolute error varying between 6.8 to 16.5 Nm. In the case of quadriceps-femoris muscles, the optimised model struggles with incorrect prediction of the peak torque and peak torque angle due to limitations of the muscle model and the distribution of the moment arm. The model predicts both peak torque and peak torque angle with high accuracy in the case of hamstring muscles. In addition, the model struggles with low precision for both knee extension and flexion for all of the involved test subjects. Although great improvement in the accuracy was observed, the model prediction was deemed to have low clinical significance, due too low accuracy and precision. The clinical significance could be improved, for example by a more detailed musculoskeletal model or by modifying the behaviour of the muscle model. Future work should focus on addressing the current issues presented in this study and a further development, as the method still is relatively new and untested. Parallelly, the researches should try to test the method in clinical studies, in order to evaluate the influence on the results by the implementation of this method of parameter estimation.

Bone loss and muscle atrophy are two main physiological conditions affecting astronauts while being in space. In order to counteract the effects, at least two hours of aerobic and resistant countermeasure exercise is scheduled into their working day, seven days a week. Yoyo Technology AB has developed a resistance exercise device based on the flywheel principle, providing a load independent of gravity. However, there is no biomechanical research done on the efficiency of the device in microgravity, from a human movement point of view using simulation software. The aim of this thesis was to evaluate the effects of performing a leg press on the flywheel exercise device in a microgravity environment. Simulations of performing a flywheel leg press in earth gravity, microgravity and performing a conventional squat were done. The evaluated parameters were reaction forces, joint angles, joint moments, joint powers and muscle recruitment in the lower extremities. The simulations were done using a biomechanical simulation software based on a motion capture data collection. From the results two conclusions were proposed. Performing a flywheel leg press in microgravity environment or on earth provides at least as much peak moment as a body weighted squat performed on earth. Furthermore, performing a flywheel leg press in microgravity will induce a higher activity level among hip extensors and knee flexors compared to performing a flywheel leg press on earth.

Motion capture has in recent years grown in interest in many fields from both game industry to sport analysis. The need of reflective markers and expensive multi-camera systems limits the business since they are costly and time-consuming. One solution to this could be a deep neural network trained to extract 3D joint estimations from a 2D video captured with a smartphone. This master thesis project has investigated the accuracy of a trained convolutional neural network, MargiPose, that estimates 25 joint positions in 3D from a 2D video, against a gold standard, multi-camera Vicon-system. The project has also investigated if the data from the deep neural network can be connected to a biomechanical modelling software, AnyBody, for further analysis. The final intention of this project was to analyze how accurate such a combination could be in golf swing analysis. The accuracy of the deep neural network has been evaluated with three parameters: marker position, angular velocity and kinetic energy for different segments of the human body. MargiPose delivers results with high accuracy (Mean Per Joint Position Error (MPJPE) = 1.52 cm) for a simpler movement but for a more advanced motion such as a golf swing, MargiPose achieves less accuracy in marker distance (MPJPE = 3.47 cm). The mean difference in angular velocity shows that MargiPose has difficulties following segments that are occluded or has a greater motion, such as the wrists in a golf swing where they both move fast and are occluded by other body segments. The conclusion of this research is that it is possible to connect data from a trained CNN with a biomechanical modelling software. The accuracy of the network is highly dependent on the intention of the data. For the purpose of golf swing analysis, this could be a great and cost-effective solution which could enable motion analysis for professionals but also for interested beginners. MargiPose shows a high accuracy when evaluating simple movements. However, when using it with the intention of analyzing a golf swing in i biomechanical modelling software, the outcome might be beyond the bounds of reliable results.

Η διενέργεια εμβιομηχανικών μελετών σε μοντέλο με τη βοήθεια ηλεκτρονικών υπολογιστών βρίσκεται σήμερα σε προχωρημένο στάδιο εξέλιξης. Σε αυτή την εξέλιξη κεντρική θέση κατέχουν λογισμικά δύο κατηγοριών. Στην πρώτη κατηγορία κατατάσσονται τα λογισμικά εμβιομηχανικής προσομοίωσης του ανθρωπίνου σώματος και στη δεύτερη κατηγορία τα λογισμικά ανάλυσης πεπερασμένων στοιχείων. Σε αυτή τη Μεταπτυχιακή Εργασία έγινε μία προσπάθεια διερεύνηση της συνεργασίας των δύο αυτών κατηγοριών λογισμικού με την κινηματική μελέτη ενός οσφυϊκού σπονδύλου και την ανάλυση φορτίσεών του με την μέθοδο των πεπερασμένων στοιχείων. Για αυτό το λόγο επιλέχτηκαν δύο λογισμικά εμπορικά διαθέσιμα. Το λογισμικό εμβιομηχανικής προσομοίωσης Anybody modeling system και το λογισμικό ανάλυσης πεπερασμένων στοιχείων Ansys multiphysics. Στο Πρώτο κεφάλαιο γίνεται παρουσίαση του λογισμικού Anybody. Πιο συγκεκριμένα. αναφέρονται τα στοιχεία εκείνα που υλοποιούν ένα μοντέλο του ανθρώπινου σώματος (τμήματα, αρθρώσεις, μύες, σύνδεσμοι) καθώς και οι μελέτες που μπορούν να εκτελεστούν δηλαδή η κινηματική και η δυναμική. Κύρια θέση κατέχει η αντιστροφή δυναμική μελέτη που χαρακτηρίζεται από την εξαγωγή συμπερασμάτων για τις δυνάμεις και τις ροπές που αναπτύσσονται σε ένα σώμα αφού έχει περιγραφεί εκ των προτέρων η κίνησή του. Στο Δεύτερο κεφάλαιο γίνεται μια λεπτομερής περιγραφή της ανατομίας της σπονδυλικής στήλης στην οποία αναφέρονται τα επιμέρους κοινά στοιχεία που έχουν οι σπόνδυλοι καθώς κου οι διαφορές στις διαφορετικές μοίρες της σπονδυλικής στήλης. Μετά την ανατομική περιγραφή παρατίθεται η εμβιομηχανική θεώρηση της κατασκευής της οσφυϊκής μοίρας της σπονδυλικής στήλης, αναλύοντας τα επιμέρους δομικά στοιχεία από μηχανική άποψη και η λειτουργικότητά τους. Στο Τρίτο κεφάλαιο περιγράφεται η κατασκευή ενός μοντέλου της σπονδυλικής στήλης στο λογισμικό Anybody το οποίο υποβάλλεται σε κινήσεις κάμψης, έκτασης, πλάγιας κάμψης και στροφής και επιχειρείται ο σχολιασμός των ευρημάτων. Τέλος, στο τέταρτο κεφάλαιο τα δεδομένα τα οποία παράγει η αντίστροφή μελέτη και συγκεκριμένα οι φορτίσεις που δέχεται ο Ο5 σπόνδυλος κατά τις κινήσεις στις οποίες υποβάλλεται η οσφυϊκή μοίρα χρησιμοποιούνται ως δεδομένα εισόδου για την ανάλυση του Ο5 σπόνδυλο με το λογισμικό μηχανικής ανάλυσης πεπερασμένων στοιχείων ANSYS. Συνοψίζοντας, η συνεργασία των δύο λογισμικών αποδείχθηκε εφικτή και πρόσφορη. Στην παρούσα μεταπτυχιακή εργασία αναπτύχθηκε η βασική τεχνογνωσία ως προς την χρήση του λογισμικού Anybody Modeling System και την συστηματοποίηση της διασύνδεσης του με το λογισμικό Ansys με αποτέλεσμά να αποτελεί την βάση για περαιτέρω εργασίες. / The conduction of biomechanical studies on models with the aid of computers is currently at an advanced stage. In this essay, the central position is hold by two software categories. In the first category are classified various software of biomechanical simulation of the human body and in the second category are classified the software for the finite element analysis. In this Master Thesis was made an attempt to explore the cooperation of these two kinds of software. For this reason, two commercially available softwares were selected. The biomechanical simulation was performed using the Anybody Modeling System software and the finite element analysis was performed using the Ansys Multiphysics software. In the first chapter the use of the Anybody software was presented. More specifically, those elements that implement a model of the human body (segments, joints, muscles, ligaments) as well as studies that can be performed i.e. the kinematics and dynamics studies were discussed in details. The inverse dynamics study has been characterized as the main feature of the software allowing to explore the resulting forces and torques developed in a body during the in advance described movement. The second chapter includes a detailed description of the anatomy of the spine. After the anatomical description the biomechanical approach is presented, analyzing each individual component from engineering point of view as well as their functionality. The third chapter describes the construction of a model of the spine in the Anybody software that is subjected to flexion, extension, lateral bending and rotation along with the results. Finally, in the fourth chapter the data that produces the inverse study namely the loads applied to the L5 vertebra during each movement performed by the lumbar spine are used as input data for the mechanical analysis of L5 vertebra with the finite element analysis software ANSYS. As a conclusion, the collaboration of these two software programmes proved to be feasible and appropriate. In this master thesis the basic knowledge in the use of software Anybody Modeling System has been developed and an interface with the software Ansys has been built thus forming the basis for further work.

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This thesis work comprises the working and simulation procedures being involved in simulating motion capture data in AnyBody Modeling System. The motion capture data used in this thesis are ballet movements from dancers of Östgöta ballet and dance academy. The ballet movements taken into consideration are the arabesque on demi-pointe and pirouette. The arabesque on demi-pointe was performed by two dancers but the pirouette is performed by only one dancer. The method involved recording ballet movements by placing markers on the dancer's body and using this motion capture data as input to AnyBody Modeling System to create a musculoskeletal simulation. The musculoskeletal modeling involved creating a very own Qualisys marker protocol for the markers placed on the ballet dancers. Then implementing the marker protocol onto a human model in AnyBody Modeling System by making use of the AnyBody Managed Modeling Repository (TM) and obtain the kinematics from the motion capture. To best fit the human model to the dancer's anthropometry, scaling of the human model is done, environmental conditions such as the force plates are provided. An optimization algorithm is conducted for the marker positions to best fit the dancer's anthropometry by running parameter identification. From the kinematics of the motion capture data, we simulate the inverse dynamics in AnyBody Modeling System. The simulations explain a lot of parameters that describe the ballet dancers. Results such as the center of mass, the center of pressure, muscle activation, topple angle are presented and discussed. Moreover, we compare the models of the dancers and draw conclusions about body balance, effort level, and muscles activated during the ballet movements.