Measurement and processing of biomedical signals

Course description

Advanced overview of selected signals of biological origin encountered in research or in medical clinical environment. Physiological origin and typical properties of these signals. Physical background and application of methods for acquisition and measurement of these signals. Electrodes and probes for acquisition of non-electrical quantities. Signal processing methods in time and frequency domain for extraction of clinically or experimentally relevant information about the biological system. Concrete examples of application.

The signals of these origins are to be discussed: electrophysiological signals (electrocardiography, electromyography of skeletal and smooth muscles, electroencephalography, nerve conduction); blood flow (ultrasound, laser Doppler); oxygenation (near infrared spectroscopy and methods for oximetry); measurement of biological cell properties (microscopy and spectroscopy).

Course is carried out on study programme

Objectives and competences

To gain knowledge and understanding of the methods for acquisition and processing of different physiological signals from the practical point of view of extracting relevant information (for clinical or reserch use) about properties and function of a biological system. By working on a project students can apply this knowledge to solving a concrete problem on a selected topic.

Learning and teaching methods

Lectures in case of sufficient number of students, otherwise independent study with regular individual consultations.

Every student is presented with a concrete applicative project on a selected topic from biomedical signal measurement and processing and is expected to find a solution to the problem based on literature search and practical work.

Intended learning outcomes

To learn about different biomedical signals, including their sources (cell, tissue, organ), physiological mechanisms of appearance, properties and relevance for clinical or research work. To understand physical principles of methods for measurement of biomedical signals.

To learn about methodology of signal processing to obtain required information, using typical examples from the biomedical field. To gain skills for solving a concrete problem from this field.

Reference nosilca

  1. Mali B, Gorjup V, Edhemovic I, Brecelj E, Cemažar M, Sersa G, Strazisar B, Miklavcic D, Jarm T (2015). Electrochemotherapy of colorectal liver metastases – an observational study of its effects on the electrocardiogram. Biomed Eng Online 14(suppl. 3):1-17 (http://www.biomedical-engineering-online.com/content/14/S3/S5)
  2. Mali B, Zulj S, Magijarevic R, Miklavcic D, Jarm T (2014) Matlab-based tool for ECG and HRV analysis. Biomed Signal Proc Control 10:108-116
  3. Mali B, Jarm T, Snoj M, Sersa G, Miklavcic D (2013) Antitumor effectiveness of electrochemotherapy : a systematic review and meta-analysis. Eur J Surg Oncol 39(1):4-16
  4. Stirn I, Jarm T, Kapus V, Strojnik V (2011) Evaluation of muscle fatigue during 100-m front crawl. Eur J Appl Physiol 111(1):101-113
  5. Jarm T, Cemazar M, Miklavcic D, Sersa G (2010) Antivascular effects of electrochemotherapy : implications in treatment of bleeding metastases. Exp Rev Anticancer Ther 10(5):729-746

Study materials

L. Soernmo, P. Laguna: Bioelectrical signal processing in cardiac and neurological applications. Academic Press, 2005.

R.M. Rangayyan: Biomedical signal analysis: a case-study approach. Wiley-IEEE Press, 2002.

Electromyography

J.D. Bronzino (ed.): The Biomedical Engineering Handbook, (3rd ed.), Vol. 2: Medical Devices and Systems. CRC Press, 2006.

R. Merletti, P. Parker: Electromyography. IEEE Press/Wiley, 2004.

T. Tagawa, T. Tamura, P. Ake Oberg: Biomedical Sensors and Instruments (2nd ed.). CRC Press, 2011.

T. G. Leighton: The Acoustic Bubble. Elsevier, 1994.

Izbrani članki iz znanstvenih revij/Selected papers from scientific journals

Bodi na tekočem

Univerza v Ljubljani, Fakulteta za elektrotehniko, Tržaška cesta 25, 1000 Ljubljana

E:  dekanat@fe.uni-lj.si T:  01 4768 411