8/13/2019 86227

1/3

DIGITAL PROCESSING OF BIOMEDICAL SIGNALS Code: 86227Telecommunications T.E. Plan: 119 Type: Elective 2nd Term

Total: 4.5 (3 Theoretical Credits y 1.5 Practical Credits) ECTS: 4 Year: 3

Teacher Area of Knowledge Department

Ral Alcaraz Martnez Tecnologa ElectrnicaIngeniera Elctrica, Electrnica,

Automtica y Comunicaciones

Raquel Cervign Abad Tecnologa ElectrnicaIngeniera Elctrica, Electrnica,

Automtica y Comunicaciones

Carlos Vay Salort Teora de la Seal y ComunicacionesIngeniera Elctrica, Electrnica,

Automtica y Comunicaciones

Aims / Skills

The teaching aims to be achieved along this course are:

-To introduce the student into the processing of biomedical signals.

-To know the main characteristics time-frequency of the most widely used bioelectrical signals at present for the

medical diagnosis.

-To know and understand the fundamentals of the electroencephalographic signals and the main techniques

used for their processing.

-To study and learn the fundamentals of the electrocardiographic signals and the main techniques for the noise

reduction they are affected by.

-To analyse and understand the advanced processing techniques of the electrocardiographic signals used to

obtain tools to make the clinical diagnosis easier.

-To know and understand the main processing techniques that exist to obtain the separation of the auricular

activity from the ventricular one, which are registered together in the electrocardiographic signals, necessary forthe study of disorders on the cardiac rhythm.

In addition, other transversal aims included are:

-Team work.

-Responsibility of the own academic training and formation.

-Development of the skill to deal with and solve a specific engineering problem.

Necessary Previous Knowledge

The knowledge acquired through these subjects:-Fourier\'s series and Analysis.

-System analysis.

-Audiovisual signal processing.

In addition, it is necessary to master the MATLAB and it is highly advisable to study the subject

INTRODUCTION TO THE ELECTROMEDICINE.

Syllabus

The theoretical syllabus to be studied is:

1/3

8/13/2019 86227

2/3

-Unit 1: Introduction to the processing of bioelectrical signals.

-Unit 2: The electroencephalogram (EEG). Description and processing.

-Unit 3. The electrocardiogram (ECG). Basics and pre- processing techniques.

-Unit 4. Advanced processing of the ECG. Application of the Wavelet Transformed.

-Unit 5. Separation of the ventricular activity from the auricular one, present in the ECG. Algorithms TMS and

BSS.

The syllabus of practical activities is:

-Practice 1. Use of MATLAB for the processing of biomedical signals.

-Practice 2. Processing of the electroencephalogram. Techniques of spectral analysis.

-Practice 3. Visualization and noise reduction in cardiac signals.

-Practice 4. Identification of the complex QRS, obtaining of the HRV and noise reduction through the signal

averaging.

-Practice 5. Use of the Wavelet Transformed for the noise compression and reduction in ECGs.

-Practice 6. Separation of the auricular activity from the ventricular one present in the ECG.

-Final project. Challenge.

The final project, in which the students will employ most time devoted to laboratory work has been named

Challenge since it intends to be introduce the students in a competition to solve a specific problem, so that they

not only have to show their learning from the theoretical classes and the 6 former practical activities, but also, to

state their skill acquired along the degree years to deal with a specific problem, being this a fundamental aspect

which they will be asked in their immediate insertion in the working market. The students will make groups of 2

to 4 people so that they will be able to get coordinated and to cooperate efficiently the same way they will

probably have to do it in their role to be developed in their work career.

The Challenge will start with the professor\'s explanation of a problem with a special relevance in the world ofcurrent bio engineering, which can be approached and thoroughly solved using the processing techniques

described during the theory and developed and implemented along the former practical activities. Therefore,

students will have to apply conveniently the work previously done in order to reach some successful results.

Once the time provided for this activity is finished, that is, six weeks, students will have to give in the obtained

results. The Challenge\'s winners will be the team that achieve the most successful results, that is, that most

closely approach the problem\'s solution, if they cannot solve it.

Before publishing the winners\' names, all the teams will present the methodology and the techniques used to

deal with the proposed problem in an open session for all the members of the EUPC. The winner team will be

announced in this session.

Time Analysis

This subject has 4 ECTS credits, which means in hours a range of between 100-120 hours of the student's

effective work. The proposal which appears below has 110 hours distributed in this way:

15 h of class attendance for theoretical contents.

30 h of laboratory attendance for practical contents, which will be divided into 18 h for the 6 guided practices

proposed and 12 h to carry out the final project or challenge which will be mainly used to assess the student.

65 h of student's personal work:

15 h for guided practices' preparation5 h for tutorship

25 h for preparation of the final project and oral presentation of their proposal.

2/3

8/13/2019 86227

3/3

20 h for personal study

Teaching Methods

This subject\'s teaching is based on the following methodological resources:

Participative lectures for the theory explanation classes.

Laboratory guided practical activities.

Tutorials.

Final project, which includes the solving of a problem with a special relevance in the world of the bioengineering.

Assessment Methods and Criteria

The final marks in this subject will be calculated out of ten points weighted according to the following criterion:

Laboratory guided practice...25%

Final project...65%

Work done and obtained results...50%

Oral presentation...10%

Class attendance...10%

Team coordination...5%

Laboratory attendance for all the practical activities, guided and the final ones, is COMPULSORY to pass the

subject. The final project will be used to assess the students\' skills for team work to deal with and solve a very

specific engineering problem, together with the theoretical contents they have learned and their project\'s oral

presentation.

Bibliography

Library Availability Reference

NO "Biomedical Signal Processing in Cardiac & Neurological Applications", L. Srnmo,

P. Laguna, Edt. Academic Press, Elsevier.

NO "Biosignal and Biomedical Image Processing: MATLAB-Based Applications", J. L.

Semmlow, Edt. Marcel Dekker.NO "Biomedical Digital Signal Processing: C-language Examples and Laboratory

Experiments for the IBM PC", W. J. Tompkins,

http://ecow.engr.wisc.edu/cgi-bin/get/ece/463/tompkins/biomedical

NO "Digital Biosignal Processing", R. Weitkunat, Edit. Elsevier Publishing Company.

NO "Detection and Estimation of Biomedical Signals", M. Akay, Edt. Academic Press

Inc.

YES "Tratamiento de Seales en Tiempo Discreto", A. V. Oppenheim, R. W. Schafer,

Edt. Prentice-Hall.

YES "Tratamiento digital de seales. Principios, algoritmos y aplicaciones". J. G.

Proakis, D. G. Manolakis, Edt. Prentice Hall.

3/3