Biomedical signal processing
Summary
The goal of this course is to introduce the techniques most commonly used for the analysis of biomedical signals, and to present concrete examples of their application for diagnosis purposes.
Content
1. Generalities on biomedical signal processing
2. Digital signal processing - basics
- sampling
- Fourier transform
- filtering
- stochastic signals correlation, and pwoer spectral density
3. Time-frequency analysis
- short-term Fourier transform
- time-frequency distributions, Cohen's class
- wavelet transform
4. Linear modeling
- autoregressive models
- linear prediction
- parametric spectral estimation
- criteria for model selection
5. Adaptive filtering
- adaptive prediction
- adaptive estimation of transfert functions
- adaptive interference cancellation
6. Miscellaneous
- polynomial models
- singular value decomposition
- principal component analysis
Keywords
signal processing, biomedical engineering, signal modeling, spectral analysis, adaptive filtering
Learning Prerequisites
Recommended courses
Signal processing for telecommunications COM-303
Signal processing EE-350
Important concepts to start the course
basics of discrete-time signal analysis
Teaching methods
lectures, lab sessions using Matlab
Assessment methods
1 point for lab/exercise sessions reports
2 exams: end of November 2points - final exam 3 points
Supervision
| Office hours | Yes |
| Assistants | Yes |
In the programs
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Semester: Fall
- Exam form: Written (winter session)
- Subject examined: Biomedical signal processing
- Lecture: 4 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
Reference week
| Mo | Tu | We | Th | Fr | |
| 8-9 | |||||
| 9-10 | |||||
| 10-11 | |||||
| 11-12 | |||||
| 12-13 | |||||
| 13-14 | |||||
| 14-15 | |||||
| 15-16 | |||||
| 16-17 | |||||
| 17-18 | |||||
| 18-19 | |||||
| 19-20 | |||||
| 20-21 | |||||
| 21-22 |
Légendes:
Lecture
Exercise, TP
Project, other