Measurements and Analysis of Biomedical Signals

5 ECTS credits
150 h study time

Offer 1 with catalog number 1022199BNR 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

Johan Stiens (course titular)
Jeroen Van Schependom

Activities and contact hours

30 contact hours Lecture
30 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:
Oral Exam determines 75% of the final mark.
Practical Exam determines 25% of the final mark.

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

Oral assessment with a relative weight of 1 which comprises 75% of the final mark.

Note: Oral exam with written preparation (closed book)

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

Assesment of practicals with a relative weight of 1 which comprises 25% of the final mark.

Note: Evaluation of the practical exercises

Additional info regarding evaluation

The analysis part (prof Van Schependom) counts for 12 points out of 20 (60%), the measurements part (prof Stiens) for 8 out of 20 (40%) of the total mark.

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