Biological Signals

Lecturer:

Tutor:

Supervisor:

Department of Circuit Theory

Synopsis:

The native and evoked biosignals are covered within this course. There are explained methods of their processing and evaluating (especially in time domain). Explanation of more important biosignals is complemented by their origin and physical and mathematical models. A few lectures is devoted to reography, polygraphic methods and biosignal compression.

Requirements:

Syllabus of lectures:

1. Biopotentials, stimulated and evoked, types, properties, recording, noise

2. Electroneurography, muscle origin signals, EMG, MMG, tendon jerks

3. Cardiac depolarization vector, electrodes, elctrode systems

4. ECG signals in time and frequency domains, vectorcardiography, isopot. maps

5. Phonocardiography, sphygmography, apexcardiography, MCG, polymethods

6. EEG signals origin, electrode systems, EEG signal properties, EEG rhythms

7. EEG systems, EEG signals in time and frequency domains, evoked EEG, MEG

8. Signals in opthalmology, origins, electroretinogram, other signals

9. Otic signals, origin, audiometry types, evoked signals

10. Nystagmography, biosignals in obstetrics, rheography methods

11. Mathematical methods of biosignal analysis, cepstrum analysis, Hilbert transform

12. Digital filtering of biosignals, supression of interference, adaptive filtering

13. Compression of biosignals, recording and transmitting

14. Experimental sensing, modern methods of biosignal analysis

Syllabus of tutorials:

1. Mathematical background for biosignal processing, cepstrum analysis

2. Mathematical background for biosignal processing, Hilbert transform

3. Preprocessing of ECG signal - rejection of supply mains interference

4. Preprocessing of ECG signal - rejection of fluctuation of pedestal

5. Processing of ECG signal in time domain

6. Processing of ECG signal in frequency domain

7. Processing of EEG signal in time domain

8. Processing of EEG signal in frequency domain

9. Digital filtering of biosignals

10. Digital filtering of biosignals

11. Adaptive filtering of biosignals

12. Adaptive filtering of biosignals

13. Adaptive filtering of biosignals

14. Example of computation of alveolar pressure

Study Objective:

Study materials:

[1] Akay, M.: Biomedical Signal Processing. Academic Press, New York 1994

[2] Akay, M.: Detection and Estimation Methods for Biomedical Signals. Academic Press, New York 1996

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Elektronika a sdělovací technika-bakalářský blok (compulsory elective course)
• Kybernetika a měření-bakalářský blok (compulsory elective course)
• Kybernetika a měření-bakalářský blok (compulsory elective course)
• Elektronika a sdělovací technika-bakalářský blok (compulsory elective course)