Teacher(s)
Kalidindi Hari Teja (compensates Lefèvre Philippe); Lefèvre Philippe; Opsomer Laurent (compensates Lefèvre Philippe);
Language
English
> French-friendly
> French-friendly
Prerequisites
Students need to master the common core skills described in the civil Engineering Bachelor's programme
Main themes
Vision and other sensory systems, the oculomotor and other motor systems and their mathematical modeling.
Learning outcomes
At the end of this learning unit, the student is able to : | |
1 |
With respect to the AA referring system defined for the Master in Biomedical Engineering, the course contributes to the development, mastery and assessment of the following skills :
Disciplinary Learning Outcomes
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Content
In the field of modeling of sensory and motor physiological systems, this course will present how a mathematical model is built in the biomedical field, starting from the laws of nature. It will describe how its elaboration is always closely linked to experiment work aiming at obtaining data on which the model will be based. The model will be presented as a tool that allows explaining basic mechanisms of biological systems and making predictions of the responses of the system in new experimental conditions. The different steps of the model development will be presented: initial observations, hypotheses, model testing and validation. Different types of models will be described and illustrated, for instance: deterministic versus stochastic, static versus dynamic or chaotic, parametric versus non-parametric, lumped versus distributed. These notions will be illustrated by mathematical models in the biomedical field as for instance physiological models of eye movements and the coordination between different body segments (with a particular focus on clinical applications and the comparison across different species).
Teaching methods
The course is made of lectures given by the teachers. The course is also made of practical exercises of mathematical modelling (data analysis and modelling) leading to homeworks as well as the critical analysis and presentation of scientific publications dedicated to mathematical models of biological systems.
Evaluation methods
The evaluation of the students will be based on two parts: 30% of the final mark will be based on the evaluation of homeworks done in small groups of students during the semester and 70% of the final mark will be based on the individual exam during the session (written or oral).
Continuous assessment comprises a number of assignments, which will result together in a single overall mark, communicated after the correction of all assignments. Failure to comply with the methodological guidelines set out on Moodle, particularly with regard to the use of online resources or collaboration between students, for any part of the project, will result in an overall mark of 0 for the continuous assessment. The use of generative AI software such as chatGPT is authorized for assistance in writing the documents requested as part of this project. However, it must be clearly and completely indicated in the document(s) concerned.
Continuous assessment comprises a number of assignments, which will result together in a single overall mark, communicated after the correction of all assignments. Failure to comply with the methodological guidelines set out on Moodle, particularly with regard to the use of online resources or collaboration between students, for any part of the project, will result in an overall mark of 0 for the continuous assessment. The use of generative AI software such as chatGPT is authorized for assistance in writing the documents requested as part of this project. However, it must be clearly and completely indicated in the document(s) concerned.
Online resources
Bibliography
Les documents du cours sont disponibles sur Moodle.
Faculty or entity
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Biomedical Engineering
Master [120] in Chemistry and Bioindustries
Master [120] in Computer Science and Engineering
Master [120] in Computer Science
Master [120] in Electro-mechanical Engineering
Master [120] in Mathematical Engineering
Master [120] in Energy Engineering