THE IMPLEMENTATION OF TORQUE GENERATORS ON A HUMAN RIGID BODY MODEL

Abstract

Simulations of human movements are widely used in many fields such as sports biomechanics, robotics, clinical studies, and entertainment (film / video game) industry. To simulate different scenarios and answer ‘what if’ questions the model would use forward dynamics principles. The actuator elements such as individual muscles or torque generators supply input to the system whereas motion of the model is the output. In the literature, torque generators are used in simulations of sports movements where information on muscle group level is generally sufficient. Torque generators are hypothetical elements attached to the joints and generate torque around that joint. The amount of torque generated represents the torque created by the muscles passing through that joint. Maximum possible torque values are estimated in torque generators. Therefore, these values are multiplied by muscle activation which has values between 0 (no activation) and 1 (full activation). In this study, torque generators were implemented on a human rigid body model which was presented in the literature. The kinematic model was developed for platform diving and consists of six rigid segments. The actual performance was a forward two and a half somersault dive from 10 m above. The performance was recorded and joint angles in the sagittal plane were calculated, previously. 5 torque generators (shoulder, elbow, hip, knee, ankle) are added to the model. At each torque generator, torque values are calculated using the joint angle at that instant. The equation of motion is solved with the torque value estimated in the torque generator and joint angle for the next instant is calculated. Then, it is sent to the torque generator to estimate new torque value. This process repeats during the entire simulation. Once the matching of the actual performance is achieved the model with the torque generator can be used to simulate different scenarios. For example, the effect of the change in the muscle activation levels/timings on the performance can be analyzed or an optimum technique can be sought to increase the performance and reduce the risk of injury. The same methodology can be applied to other models developed for different sports movement

Keywords

• Torque Generator
• Simulation
• Human Rigid Body Model
• Forward Dynamics
• Sports Biomechanics

THE IMPLEMENTATION OF TORQUE GENERATORS ON A HUMAN RIGID BODY MODEL

Abstract

Simulations of human movements are widely used in many fields such as sports biomechanics, robotics, clinical studies, and entertainment (film / video game) industry. To simulate different scenarios and answer 'what if' questions the model would use forward dynamics principles. The actuator elements such as individual muscles or torque generators supply input to the system whereas motion of the model is the output. In the literature, torque generators are used in simulations of sports movements where information on muscle group level is generally sufficient. Torque generators are hypothetical elements attached to the joints and generate torque around that joint. The amount of torque generated represents the torque created by the muscles passing through that joint. Maximum possible torque values are estimated in torque generators. Therefore, these values are multiplied by muscle activation which has values between 0 (no activation) and 1 (full activation). In this study, torque generators were implemented on a human rigid body model which was presented in the literature. The kinematic model was developed for platform diving and consists of six rigid segments. The actual performance was a forward two and a half somersault dive from 10 m above. The performance was recorded and joint angles in the sagittal plane were calculated, previously. 5 torque generators (shoulder, elbow, hip, knee, ankle) are added to the model. At each torque generator, torque values are calculated using the joint angle at that instant. The equation of motion is solved with the torque value estimated in the torque generator and joint angle for the next instant is calculated. Then, it is sent to the torque generator to estimate new torque value. This process repeats during the entire simulation. Once the matching of the actual performance is achieved the model with the torque generator can be used to simulate different scenarios. For example, the effect of the change in the muscle activation levels/timings on the performance can be analyzed or an optimum technique can be sought to increase the performance and reduce the risk of injury. The same methodology can be applied to other models developed for different sports movement.

Keywords

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