37465 - Computational Biomechanics M

Learning outcomes

The students will master the advanced computational tools for the analysis of the intact musculoskeletal system and in the presence of prosthetic devices. they will learn to integrate image data with biomechanical models. Cross-validation with results obtained from in-vitro and in-vivo experimentation. Acquire theoretical-practical understanding of continuum mechanics and finite element method, as well as numerical methods for finite element modelling of nonlinear problems such as large displacements, contact, plasticity, etc. Familiarise yourself with widely used commercial programs. Develop skills in formulating and solving structural and functional biomechanics problems.

Course contents

• Introduction to the course, can nature be predicted?
• Introduction to in silico medicine
• Notes on the anatomy and physiology of the skeletal system
• Skeletal Mechanobiology
• Fundamentals of solid mechanics
• The finite element method
• Credibility of predictive models
• Digital patient: predicting skeletal strength
• In silico trials: probabilistic design
• In silico trials: reduction of animal experimentation
• In silico trials: reduction of clinical trials

Readings/Bibliography

copy of the slides used by the lecturer

Teaching methods

Frontal teaching and hands-on labs

Assessment methods

Oral exam.

Before the exam, the student must have done all the exercises provided, and produced the relevant evidence, by sending them to the lecturer by e-mail or to present them during the exam.

Teaching tools

High interaction between teacher and students through practical examples and related discussion; participation in real experimental sessions in which students can take an active role in their execution and become familiar with the related instrumentation and calculation processes.

Office hours

See the website of Marco Viceconti