Graduate Study - Faculty of Engineering and Natural Sciences
3+2 Electrical and Electronic Engineering

Code Name Level Year Semester
EEE 501 Biomedical Signal Processing Graduate 1 Fall
Status Number of ECTS Credits Class Hours Per Week Total Hours Per Semester Language
7.5 0 English

Instructor Assistant Coordinator
Abdülhamit Subaşı, Prof. Dr. Murat Yildiz, Lecturer
[email protected] no email

The objective of this course is
• To understand the key concepts of biomedical signals
• To understand basic electric circuits and their usage for amplification and filtering of biological signals
• To learn the origins of biopotentials and their characteristics in time and frequency domain
• To apply modern engineering tools to collect, analyze and interpret biological signals
• To learn the principles of interfacing with the living systems for collection of biomedical signals
• To introduce biomedical signal processing techniques.
• To interpret how to analyze the biomedical signals
• To understand how to analyze biomedical signals with machine learning techniques
• To develop basic application of biomedical signal processing concepts.

  1. Basic Concepts
  2. Principles of Electrocardiography
  3. Principles of Electromyography
  4. Principles of Electroencephalography
  5. Evoked Potential and BCI
  6. Spectral Analysis: Classical Methods
  7. Digital Filters
  8. Spectral Analysis: Modern Techniques
  9. Time–Frequency Methods
  10. The Wavelet Transform
  11. Advanced Signal Processing Techniques
  12. Multivariate Analyses: Principal Component Analysis, Independent Component Analysis, Multiscale Principal Component Analysis
  13. Analysis of biomedical signals with machine learning techniques
  14. Research Presentation


    • Lectures
    • Presentation
    Description (%)
    Method Quantity Percentage (%)
    Midterm Exam(s)130
    Final Exam140
    Total: 100
    Learning outcomes
    • Demonstrate a systematic and critical understanding of the theories, principles and practices of biomedical signal processing;
    • Creatively apply contemporary theories, processes and tools in the development and evaluation of solutions to problems and product design in biomedical engineering;
    • Actively participate in, reflect upon, and take responsibility for, personal learning and development, within a framework of lifelong learning and continued professional development;
    • Present issues and solutions in appropriate form to communicate effectively with peers and clients from specialist and non-specialist backgrounds;
    • Work with minimum supervision, both individually and as a part of a team, demonstrating the interpersonal, organisation and problem-solving skills supported by related attitudes necessary to undertake employment.
    • 1.John L. Semmlow, Biosignal and Biomedical Image Processing MATLAB-Based Applications, Marcel Dekker, Inc., 2004.

    ECTS (Allocated based on student) WORKLOAD
    Activities Quantity Duration (Hour) Total Work Load
    Lecture (14 weeks x Lecture hours per week) 0
    Laboratory / Practice (14 weeks x Laboratory/Practice hours per week) 0
    Midterm Examination (1 week) 0
    Final Examination(1 week) 0
    Preparation for Midterm Examination 0
    Preparation for Final Examination 0
    Total Workload: 0
    ECTS Credit (Total workload/25): 0