FACULTY OF ENGINEERING

Department of Biomedical Engineering

BME 403 | Course Introduction and Application Information

Course Name
Biomedical Signal Processing
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
BME 403
Fall/Spring
2
2
3
5

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives The objective of this course is to teach students the concept of random biological processes, modeling of random processes, the concept of correlation and power spectral density, time and frequency domain methods used for processing random signals produced by biological processes. It also covers the concepts of statistical signal processing, estimation and filtering.
Learning Outcomes The students who succeeded in this course;
  • Recognize analog and digital random biological signals
  • Explain the concepts of random variable, signal and process
  • Interpret the modeling and spectral analysis of random signals
  • Describe the concepts of self and cross correlation, statistical mean and moment
  • Familiarize with processing and filtering of random signals with linear systems.
  • Understand stationary and ergodic biological processes.
Course Description This course explains the time and frequency time domain analysis of random biological signals, the concepts of time and group mean and high degree moment, modeling of random signals, the concept of estimation, filtering, stationary random processes.

 



Course Category

Core Courses
Major Area Courses
X
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Biomedical and random signal concept Chap 0. Luis Chaparro, Aydin Akan, Signals and Systems using MATLAB 3rd Ed. Academic Press, 2019, ISBN: 9780128142042.
2 Discrete time random biological signals and systems Chap 9. Luis Chaparro, Aydin Akan, Signals and Systems using MATLAB 3rd Ed. Academic Press, 2019, ISBN: 9780128142042.
3 Frequency analysis for discrete time biological signals, DTFT Chap 11. Luis Chaparro, Aydin Akan, Signals and Systems using MATLAB 3rd Ed. Academic Press, 2019, ISBN: 9780128142042.
4 Discrete Fourier transform (DFT), Circular and periodic convolution Chap 11. Luis Chaparro, Aydin Akan, Signals and Systems using MATLAB 3rd Ed. Academic Press, 2019, ISBN: 9780128142042.
5 The Z-Transform Chap 10. Luis Chaparro, Aydin Akan, Signals and Systems using MATLAB 3rd Ed. Academic Press, 2019, ISBN: 9780128142042.
6 Statistical analysis of random biological signals, correlation function, moments Chap 4. Stark and Woods, Probability and Random Processes with Applications to Signal Processing, 4/E Pearson, 2012 ISBN: 9780273752288
7 Power spectrum analysis for biological signals Chap 8. Stark and Woods, Probability and Random Processes with Applications to Signal Processing, 4/E Pearson, 2012 ISBN: 9780273752288
8 Midterm
9 Processing of random signals with LTI systems Chap 9. Stark and Woods, Probability and Random Processes with Applications to Signal Processing, 4/E Pearson, 2012 ISBN: 9780273752288
10 Modeling of random signals (AR, MA, ARMA models) Lecture Notes 1
11 Estimation concept, statistical filtering methods Chap 9. Stark and Woods, Probability and Random Processes with, Applications to Signal Processing, 4/E Pearson, 2012 ISBN: 9780273752288
12 Random processes Chap 9. Stark and Woods, Probability and Random Processes with Applications to Signal Processing, 4/E Pearson, 2012 ISBN: 9780273752288
13 Stationary and non-stationary random processes Chap 9. Stark and Woods, Probability and Random Processes with Applications to Signal Processing, 4/E Pearson, 2012 ISBN: 9780273752288
14 Time-Frequency analysis methods for non-stationary signals Lecture Notes 2
15 Review of the course
16 Final Exam

 

Course Notes/Textbooks
  • Stark and Woods, Probability and Random Processes with Applications to Signal Processing, 4/E Pearson, 2012 ISBN: 9780273752288
Suggested Readings/Materials
  • Luis Chaparro, Aydin Akan, Signals and Systems using MATLAB 3rd Ed. Academic Press, 2019, ISBN: 9780128142042.
  • Alberto Leon-Garcia, Probability, Statistics, and Random Processes for Electrical Engineering, 3/E, Pearson, 2008. ISBN: 9780131471221

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
6
30
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
7
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
2
32
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
2
32
Study Hours Out of Class
16
2
32
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
6
4
24
Presentation / Jury
0
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
12
12
Final Exam
1
18
18
    Total
150

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Biomedical Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

X
2

To be able to identify, define, formulate, and solve complex Biomedical Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Biomedical Engineering applications.

X
5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Biomedical Engineering research topics.

6

To be able to work efficiently in Biomedical Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

8

To have knowledge about global and social impact of Biomedical Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of engineering solutions.

X
9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.

10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Biomedical Engineering, and to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Biomedical Engineering.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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