93927 - Musculo-Skeletal Modeling and Control

Academic Year 2021/2022

Learning outcomes

The aim of the course is to provide the student the fundamental knowledge for the analysis and characterisation of motor control of the musculoskeletal system in-silico and in-vivo. The student will understand the complex structure of motor control and become familiar with the different experimental methods and analysis approaches proposed for its characterisation in-vivo, as hell as its simulation and analysis using multi-scale muscle-skelethal models.

Course contents

The course contents integrate, through coordination with the responsible teachers, those of the SPORT BIOMECHANICS and AGEING AND REHABILITATION ENGINEERING courses

Introductory notions:
- Review of anatomy and physiology of the neuro-musculoskeletal system
- Fundamentals of Motor Control: variability, complexity and automaticity in typical development and in pathological conditions

Modeling for in-silico simulation of motor control:
- Review of mechanics of multilink systems
- Parametric muscle model and optimization criteria
- Computational musculoskeletal models for the simulation of motor control
- Laboratory exercises: Simulation of the effect of functional and anatomical alterations; Influence of modeling criteria on simulation

Experimental methods for the in-vivo evaluation of motor control:
- Review of instrumentation and methods for the quantification of movement in the laboratory and in ecological conditions (living environments; clinical contexts)
- Fundamentals for the analysis of motor control dynamics: parameters for the characterization of motor development and performance; non-linear metrics for the quantitative characterization of motor function
- Laboratory exercises for the quantification of motor control

Readings/Bibliography

Teaching materials and articles provided on-line by the professor

Nonlinear Analysis for Human Movement Variability, Nicholas Stergiou, CRC Press.

Teaching methods

Frontal teaching in the classroom.
Laboratory exercises.
Supervised group projects.

Assessment methods

Group projects, the presentation will be scheduled at the end of the course in June.
Final exam, consisting of 20 multiple choice questions, 2 oral questions.
The presentation of the project will contribute 40% and the final exam 60% to the final evaluation.

Teaching tools

• Power Point slide
• 1 Stereo-photogrammetric system (6 TC)
• 2 power platforms
• 1 multi-channel wireless EMG system
• 1 multi-channel EMG system for electrode arrays and arrays
• Wearable Inertial Sensors (IMUs)

Office hours

See the website of Rita Stagni