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Musculoskeletal Modeling of Ballet
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.
Musculoskeletal Modeling of Ballet
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.
Musculoskeletal Modeling of Ballet
Hungenahalli Shivanna, Bharath (author)
2020-01-01
Theses
Electronic Resource
English
Multi Body Dynamics , AnyBody Modeling System , Motion Capture , Qualisys Marker Protocol , Center of Pressure , Center of Mass , Teknisk mekanik , Topple angle , Parameter Identification , Kinematic Modeling , Pirouette , ; Applied Mechanics , Modeling , Scaling Human Body Model , Human Body Model , Extra Drivers , Ballet , Arabesque , Musculoskeletal , Joint Reaction Forces , Muscle Activations , Force plates , Inverse dynamics
DDC:
690
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