Graduate Study - Faculty of Engineering and Natural Sciences
PhD Electrical and Electronic Engineering

Code Name Level Year Semester
EEE 603 Special Topics in 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. Abdülhamit Subaşı, Prof. Dr.
[email protected] no email

• 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 Methods
  7. Applications of Spectral Analysis Techniques
  8. Time–Frequency Methods
  9. Applications of Time–Frequency Methods
  10. The Wavelet Transform
  11. Applications of The Wavelet Transform
  12. Multivariate Analyses: Principal Component Analysis, Independent Component Analysis, Multiscale Principal Component Analysis
  13. Analysis of biomedical signals with machine learning techniques
  14. Paper Presentation

  1. 1

    • Lectures
    • Presentation
    • Seminar
    Description (%)
    Method Quantity Percentage (%)
    Term Paper130
    Final Exam140
    Total: 100
    Learning outcomes
    • Demonstrate a systematic and critical understanding of the theories, principles and practices of computing
    • Critically review the role of a “professional computing practitioner” with particular regard to an understanding of legal and ethical issues
    • Creatively apply contemporary theories, processes and tools in the development and evaluation of solutions to problems and product design
    • 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
    • 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 Examination7.50
    Total Workload: 0
    ECTS Credit (Total workload/25): 0