MODELING & MIXED REALITY IN HEALTH

SYLLABUS

There will be an introduction to basic concepts of physics, dynamical systems, state space representation, control, numerical integration and transformations. Basic robotics concepts will be used to model and derive the equation of motion of the skeletal system, which will be the basis for understanding and modeling the motion of the human neuromusculoskeletal system. Finally, different simulation algorithms will be studied (forward and inverse), that are constantly used and applied by the biomechanical community.

As part of the lectures there will be an extensive discussion on classical work in the area and the student will be entrusted with the study of selected publications. The laboratories are consistent with the understanding of the material, while solving practical applications. Intermediate assignments will be presented at the end of the courses to help in understanding the material.Theoretical classes: There will be an introduction to basic concepts of physics, dynamical systems, state space representation, control, numerical integration and transformations. Basic robotics concepts will be used to model and derive the equation of motion of the skeletal system, which will be the basis for understanding and modeling the motion of the human neuromusculoskeletal system.

Finally, different simulation algorithms will be studied (forward and inverse), that are constantly used and applied by the biomechanical community. As part of the lectures there will be an extensive discussion on classical work in the area and the student will be entrusted with the study of selected publications.

Practical classes: The laboratories are consistent with the understanding of the material, while solving practical applications. Intermediate assignments will be presented at the end of the theoretical class to help in understanding the material

Learning outcomes

• Demonstrate a comprehensive understanding of the fundamental concepts of physics, dynamical systems, and state space representation.
• Apply advanced principles of control theory proficiently to analyze and model complex human neuromusculoskeletal systems.
• Exhibit a high level of proficiency in employing numerical integration techniques to simulate intricate human movement.
• Articulate the significance of robotics in the modeling and derivation of equations of motion for skeletal systems.
• Skillfully utilize simulation algorithms, including forward and inverse methods, widely employed within the biomechanics research community.
• Conduct in-depth analysis of selected publications in the field, displaying critical evaluation skills regarding their contributions to the study of human movement.
• Demonstrate the ability to proficiently solve practical applications pertaining to the modeling and simulation of human neuromusculoskeletal systems.

General Competences

• Critical Thinking: The ability to analyze and evaluate complex concepts, theories, and research findings related to the modeling and simulation of human neuromusculoskeletal systems.
• Problem Solving: The capacity to apply knowledge and skills to solve practical applications and address biomedical problems in the study of human movement.
• Numerical and Analytical Skills: Proficiency in using numerical integration techniques, mathematical modeling, and data analysis to simulate and analyze human movement.
• Technical Competence: Mastery of relevant software tools, programming languages, and simulation algorithms commonly used in the field of biomechanics and human movement modeling.
• Research Skills: The capability to locate, critically evaluate, and synthesize scientific literature and research findings in the field, contributing to the advancement of knowledge.