Objectives of Programme's Learning Outcomes

• Work effectively in teams, develop leadership, and make decisions in multidisciplinary, multicultural and international contexts.
• Interact effectively with others to carry out common projects in various contexts (multidisciplinary, multicultural, and international).
• Mobilise a structured set of scientific knowledge and skills and specialised techniques in order to carry out electrical engineering missions, with a focus on signals and systems, using their expertise and adaptability.
• Master and appropriately mobilise knowledge, models, methods and techniques related to the basics of electricity, electronics, automatic control, signal processing and analysis, telecommunications, hardware and software instrumentation, mathematical modelling and analysis of dynamic systems, control methods, more specific applications related to signal processing, and control of biomedical and biological systems.
• Analyse and model a problem by critically selecting theories and methodological approaches (modelling, calculations), and taking into account multidisciplinary aspects.
• Identify and discuss possible applications of new and emerging technologies in the field of electrical engineering.
• Work effectively in teams, develop leadership, and make decisions in multidisciplinary, multicultural and international contexts.
• Interact effectively with others to carry out common projects in various contexts (multidisciplinary, multicultural, and international).

Learning Outcomes of UE

understand the sequencing of modules in a complete biomedical signal acquisition and processing system, for various signals (electroencephalogram, electrocardiogram, electromyogram, etc.), from sensor to feature extraction (except for classification, which is by a previous course on "Statistical Pattern Recognition");understand brain signals and be ready to analyse them.

Content of UE

biomedical signals (origins, bioelectrical phenomena, acquisition and sensors, amplifiers, filters); biomedical signal processing techniques (filtering and artefact elimination, event detection, feature extraction); Introduction to brain signals; BIOPAC tools, PYTHON, Labview.

Prior Experience

Basic knowledge of signal processing; notions of pattern recognition (but a separate course on pattern recognition is required as a complement to this course, to have a complete view of complete biomedical signal processing systems, from sensors to classification).

Type of Assessment for UE in Q1

• Oral examination

Q1 UE Assessment Comments

Oral exam with identical questions for all students, prepared on paper. The oral exam is based on the whole curriculum, including practical sessions.

Type of Assessment for UE in Q3

• Oral examination

Q3 UE Assessment Comments

Oral exam with identical questions for all students, prepared on paper. The oral exam is based on the whole curriculum, including practical sessions.

Type of Resit Assessment for UE in Q1 (BAB1)

• Oral examination

Q1 UE Resit Assessment Comments (BAB1)

Not applicable