Course : Applied Biomedical Signal Processing

Teachers: Dr. Mathieu Lemay (responsible), Dr. Philippe Renevey, Dr. João Jorge, Dr. Martin Proença, Dr. Adrian Luca, Dr. Guillaume Bonnier, Dr. Fabian Braun, Dr. Ramin Soltani, Ms. Clémentine Aguet

Assistants: Cristina Sainz Martínez, Loïc Jeanningros, Pierre-Louis Gaudillière, Yamane El-Zein

Course description
The goal of this course is twofold: (1) to introduce physiological basis, signal acquisition solutions (sensors) and state-of-the-art signal processing techniques, and (2) to propose concrete examples of applications for vital sign monitoring and diagnosis purposes.

The main signal processing topics presented will be:

  • Basics on continuous and discrete time Fourier transform
  • Linear filter deisgn
  • Stochastic signals and filtering
  • Power spectral density
  • Autoregressive, Moving average and ARMA signal modeling
  • Basic concpets of time frequency analysis
  • Time frequency distributions
  • Instantaneous frequency
  • Adaptive filter frequency tracking
  • Singular value decomposition
  • Principal component analysis
  • Linear/non-linear regression
  • Classification and feature selection
  • Perceptron, MLP & activation function
  • Gradient descent and backpropagation
  • CNN & RNN

As the course content may evolve over time, the agenda is on a short-term basis.

This course comprises weekly exercise or computer lab sessions. All courses and exercise sessions take place in room INF213, including lab sessions from 17h to 19h. The lab sessions will be computer lab ones, during which experimental biomedical signals will be investigated, with groups of two-to-three students allowed. Students should handle them 7 days after the session at the latest. The corrections will be handled back one week later.

N.B. The date, time and location of the final exam need to be confirmed. All printed/written documents will be allowed, laptops and phones prohibited.