3 ECTS credits
90 h study time

Offer 1 with catalog number 1023316BNR for all students in the 2nd semester at a (B) Bachelor - advanced level.

Semester
2nd semester
Enrollment based on exam contract
Impossible
Grading method
Grading (scale from 0 to 20)
Can retake in second session
Yes
Taught in
English
Faculty
Faculteit Ingenieurswetenschappen
Department
Electronics and Informatics
Educational team
Jeroen Van Schependom
Jef Vandemeulebroucke (course titular)
Activities and contact hours

18 contact hours Lecture
18 contact hours Seminar, Exercises or Practicals
Course Content

The course aims to cover important techniques frequently used in the biomedical domain and corresponding master courses, including biomedical signal processing, bootstrapping/permutation, numerical statistics, filtering and noise reduction, independent component analysis, Python/MATLAB programming.

1. Theoretical basis

  • Filtering and artefact rejection
  • Frequency domain analysis techniques: Fourier and spectral density
  • Wavelet decomposition
  • Linear regression and significance testing using numerical methods
  • Pattern recognition and clustering
  • PCA, ICA, and complex PCA
  • Classification

2. Application Oriented

  • Programming biomedical signal processing in Python/MATLAB
  • Numerical statistical techniques in Python/MATLAB.
  • Hands‐on experience with common biomedical signals.

3. Biomedical instrumentation and measurement techniques

  • Specific measurement techniques in the biomedical domain
  • Electrical measurements on cells
  • ECG, EMG, EEG, measurements
  • Electrical characteristics of tissues: impedance and permittivity measurements and tomography
  • Plethysmography (electrical and optical)
Additional info

PowerPoint slides discussed during the lectures. Exercises and cases available through Canvas.

Learning Outcomes

Leerresultaten

After completion of this course, the student should be able to

1. Understand how practical numerical statistical and biomedical signal processing techniques work.

2. Be able to identify which signal processing and statistical methods are suitable for the biomedical dataset at hand.

3. Apply Python/MATLAB programming and implement biomedical signal processing and statistics.

4. Search for and evaluate more advanced biomedical signal processing techniques required in MSc courses.

5. Summarize the main instrumentation, measurement techniques and analysis methods for the determination of electrical signals of biological origin and the characterization of biological material, and explain which instrumentation, measurement technique and analysis method is appropriate for a given case.

Grading

The final grade is composed based on the following categories:
Other Exam determines 100% of the final mark.

Within the Other Exam category, the following assignments need to be completed:

  • Oral assessment with a relative weight of 1 which comprises 100% of the final mark.

Additional info regarding evaluation

NA

Allowed unsatisfactory mark
The supplementary Teaching and Examination Regulations of your faculty stipulate whether an allowed unsatisfactory mark for this programme unit is permitted.

Academic context

This offer is part of the following study plans:
Bachelor of Mathematics and Data Science: Standaard traject (only offered in Dutch)