Course detail

Advanced Analysis of Biological Signals

FEKT-MPA-ACSAcad. year: 2023/2024

The course is oriented to multirate signal processing, time-frequency analysis focused particularly on the different types of wavelet transform, parametric methods for power spectrum estimation, principal component analysis (PCA) and data compression.

Language of instruction


Number of ECTS credits


Mode of study

Not applicable.

Offered to foreign students

The home faculty only

Entry knowledge

Students should have knowledge of digital signal processing, be familiar with the ways of describing the linear filters (transfer function, impulse response, difference equations, frequency response). We assume basic knowledge of students about the properties of biosignals (especially ECG, EEG, EMG). The laboratory work is expected knowledge of Matlab programming environment.

Rules for evaluation and completion of the course

- 30 points can be obtained for activity in the laboratory exercises, consisting in solving tasks (for the procedure for the examination must be obtained at least 15 points)
- 70 points can be obtained for the written exam (the written examination is necessary to obtain at least 35 points)

Laboratory is compulsory, missed labs must be properly excused and can be replaced after agreement with the teacher.


Gaining knowledge about multirate signal processing, wavelet transforms for processing and analysis of biosignals, principal component analysis (PCA), applications of PCA for analysis of biosignals and parametric methods for power spectrum estimation. Basic understanding of information theory, getting to know with the methods of lossless and lossy data compression.
The student is able to:
- implement the sampling rate conversion
- explain the principles and advantages of multirate filtering
- implement of the various types of wavelet transforms
- explain the principles of filtering and data compression based on wavelet transform
- explain the principles of lossless data compression (Huffman encoder, arithmetic coder)
- explain the principles and possibilities of the use of PCA

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Proakis,J.G., Manolakis,D.G.: Digital Signal Processing. Principles, Algorithms and Applications. Macmillan, 1992 (EN)

Recommended reading

Not applicable.


Classification of course in study plans

  • Programme MPC-BTB Master's, 1. year of study, winter semester, compulsory
  • Programme MPC-BIO Master's, 2. year of study, winter semester, compulsory
  • Programme MPAD-BIO Master's, 2. year of study, winter semester, compulsory

Type of course unit



26 hours, optionally

Teacher / Lecturer