COURSE SYLLABUS

BIOMEDICAL SIGNAL PROCESSING

1	Course Title:	BIOMEDICAL SIGNAL PROCESSING
2	Course Code:	EEM4429
3	Type of Course:	Optional
4	Level of Course:	First Cycle
5	Year of Study:	4
6	Semester:	7
7	ECTS Credits Allocated:	4
8	Theoretical (hour/week):	3
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	0
11	Prerequisites:
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Doç. Dr. ERSEN YILMAZ
16	Course Lecturers:
17	Contactinformation of the Course Coordinator:	Doç.Dr. ERSEN YILMAZ
18	Website:
19	Objective of the Course:	Purpose of this course is to inform the students about biological signal actuation, characteristics and processing methods.
20	Contribution of the Course to Professional Development	To be able to follow innovations and apply them in the field by using the competence of collecting information, researching and analyzing them.

Learning Outcomes:

1	To gain sufficient knowledge on Biomedical to be able to identify, model, formulate and solve complex biomedical signal processing problems.;;
2	To gain the ability to design partly or fully a complex biomedical signal processing systems meeting specific requirements under realistic constraints and conditions and to be able apply modern design methods in this context.;;
3	To be able to design and conduct complex experiments and to collect, analyze and interpret data for Biomedical signal processing.;;
4	To Gain the ability to apply teorical and practical knowledge for analysis and modelling methods of the Biomedical signal processing problems.;;
5	To be able to use information technologies in an efficient way to develop, select, and use modern techniques and tools necessary for the Biomedical signal processing.;;

22	Course Content:

Week	Theoretical	Practical
1	Action potentials,electrical activities and evoked potentials of biological systems.
2	Biomedical signals: EOG, ERG, EMG, PCG, BPS, MEG, MCG.
3	EEG, EKG signals, frequency, frequency-time properties.
4	Active denoising, Adaptive filters, Wiener filters.
5	Stochastic signal modelling, AR, ARMA models for EEG signals.
6	Infarction diagnoisis from ECG with wavelet and frequency analysis.
7	Epilepsy diagnoisis from ECG with wavelet and frequency analysis.
8	Midterm Exam and Course Review
9	Statistical and linear discrimination functions in classification of biomedical signals.
10	Stochastic, chaotic and deterministic signals,chaotic properties of the biomedical signals.
11	Foundations of chaos in cardiovascular activity, chaotic structure of ECG signals.
12	Phase spatial for biomedical signals, Lyapunov exponentials and computational methods.
13	ECG and EEG signals chaotic structure analysis with Lyapunov exponentials.
14	Lyapunov and fractal dimensions for chaotic biomedical signals.

23	Textbooks, References and/or Other Materials:	1. Arnon Cohen, Biomedical Signal Processing, CRC Press., 2002. 2. Rangaraj M. Rangayyan, Metin Akay (Editor), Biomedical Signal Analysis : A case study approach, John Wiley & Sons, 2001. 3. Suresh R. Devasahayam, Signals and Systems in Biomedical Engineering: Signal Processing and Physiological Systems Modelling, Plenum Pub. Kluwer Academic, 2000 4. M. Akay, Biomedical Signal Processing, Academic Press, 1994.
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	1	40
Quiz	0	0
Homeworks, Performances	0	0
Final Exam	1	60
Total	2	100
Contribution of Term (Year) Learning Activities to Success Grade		40
Contribution of Final Exam to Success Grade		60
Total		100
Measurement and Evaluation Techniques Used in the Course	Measurement and evaluation is carried out according to the priciples of Bursa Uludag University Associate and Undergraduate Education Regulation.
Information	The relative evoluation system is applied. 1 Midterm and 1 Final exams are held.

ECTS / WORK LOAD TABLE

CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High