Course detail

Advanced Analysis of Biological Signals

FEKT-FACSAcad. year: 2011/2012

The course is oriented to multirate signal processing, wavelet transforms, parametric methods for power spectrum estimation, Karhunen-Loeve transform (KLT) and principal component analysis (PCA).

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

doc. Ing. Jiří Kozumplík, CSc.

Department

Department of Biomedical Engineering (UBMI)

Learning outcomes of the course unit

Practical knowledge of advanced methods of processing and analysis of biosignals.

Prerequisites

The subject knowledge on the Bachelor´s degree level is requested.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

Requirements for completion of a course are specified by a regulation issued by the lecturer responsible for the course and updated for every year.

Course curriculum

Sampling rate conversion, design of multirate filters. Wavelet transforms and their use for processing and analysis of biosignals. Parametric methods for power spectrum estimation. Karhunen-Loeve transform (KLT), principal component analysis (PCA) and applications of KLT and PCA for analysis of biosignals.

Work placements

Not applicable.

Aims

Knowledge of multirate signal processing, wavelet transforms for processing and analysis of biosignals, parametric methods for power spectrum estimation, Karhunen-Loeve transform (KLT) and principal component analysis (PCA), applications of KLT and PCA for analysis of biosignals

Specification of controlled education, way of implementation and compensation for absences

Limitations of controlled teaching and its procedures are specified by a regulation issued by the lecturer responsible for the course and updated for every year.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Kozumplík, J.: Multitaktní systémy. Elektronická skripta FEKT VUT v Brně, 2005 (CS)
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 BTBIO-F Master's

    branch F-BTB , 1. year of study, winter semester, compulsory

  • Programme EEKR-CZV lifelong learning

    branch ET-CZV , 1. year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

doc. Ing. Jiří Kozumplík, CSc.

Syllabus

Sampling rate conversion
Design of multirate filters
Time-frequency analysis, continuous-time wavelet transform (CTWT)
Discrete-time wavelet transform (DTWT), dyadic and packet DTWT
Use of CTWT in analysis of biosignals
Lossy compression of biosignals
Use of DTWT in compression of biosignals
Redundant DTWT for filtering and analysis of biosignals
Spectral analysis of biosignals and parametric methods for power spectrum estimation
Linear prediction and Burg method for power spectrum estimation
Karhunen-Loeve transform (KLT) and principal component analysis (PCA)
Multivariate signal analysis
Applications of KLT and PCA for analysis of biosignals

Exercise in computer lab

26 hours, compulsory

Teacher / Lecturer

Ing. Martin Vítek, Ph.D.

Syllabus

Implementations of sampling rate conversion
Implementations of multirate filters
CTWT with Wavelet toolbox for Matlab
Applications of CTWT
DTWT with Wavelet toolbox for Matlab
Applications of DTWT
Realization of DTWT without the Wavelet toolbox
Redundant DTWT and wavelet filtering
Packet DTWT
Parametric methods for power spectrum estimation
Realization of Karhunen-Loeve transform, principal component analysis
Applications of KLT and PCA for analysis of biosignals
Presentations of projects

The other activities

13 hours, compulsory

Teacher / Lecturer

doc. Ing. Jiří Kozumplík, CSc.

Syllabus

Solution of individual projects:
Design and implementation of systems for sampling rate conversion.
Design and implementation of the multirate digital filters
CTWT for analysis of biosignals
DTWT and lossy compression of biosignals
Wavelet based filtering of biosignals
Estimation of power spectrum of biosignals (parametric methods)