Information Package
baskent.edu.tr

Program of Biomedical Engineering (English)

BENG429

BIOMEDICAL SIGNAL PROCESSING II

Course Code
BENG429
Semester
-
Theory+Practice
3 + 1
ECTS
5
Course TypeElective Course
Course LevelBachelor's Degree
Year of Study-
Semester-
ECTS5
Name of Lecturer(s) -
Learning Outcomes

At the end of this course, the students;

  1. Can calculate the frequency, amplitude and phase responses of the LTI systems.
  2. Learn to use the LTI system as a frequency selective filters.
  3. Learn the concepts related to physiological signals.
  4. Can do advanced mathematical operations associated with biomedical signals and systems.
  5. Learn concepts related to design and implement digital filters.
  6. Learn the noise filtering and event detection techniques.
  7. Learn technical analysis of frequency characteristics, feature detection and waveform / complexity for biomedical signals and systems.
  8. Can do one-dimensional signal processing and analysis in laboratory experiments by applying the theoretical knowledge learned in the course.
Mode of DeliveryFace to face
PrerequisitesNo
Recommended Optional Programme ComponentsNo
Course DescriptionIn this course, frequency domain analysis of LTI systems, frequency, amplitude and phase responses, use LTI systems as frequency selective filters, bioelectric signals, coupled, concurrent and correlated processes, filtering for removal artifacts, filters used in practice, to determine the important features of biomedical signals, EEG, ECG and PCG parameter detection applications, the waveform and complexity, the approach used in waveform and complexity analysis, frequency characterization, PSD calculation methods and applications issues are handled.
Course Contents
WEEK TOPICS
1st Week Frequency domain analysis of LTI systems
2nd Week Frequency, amplitude and phase response
3rd Week Use the LTI system as a frequency selective filters
4th Week Bioelectric signals
5th Week Coupled, concurrent and correlated processes
6th Week Filter design for artifact removal
7th Week Different filters are used in practice
8th Week Midterm
9th Week Feature detection from biomedical signals
10th Week Feature detection applications for EEG, ECG and PCG
11th Week Approaches used in the waveform and complexity analysis
12th Week Frequency Characterization
13th Week PSD calculation methods and applications
14th Week The time-frequency analysis
Recommended or Required ReadingDigital Sinal Processing, Principles, Algorithms and Applications, 4thEd, J.G.Proakis, D.G.Manolakis, Pearson Education,Inc, Prentice Hall

Biomedical Signal Analysis, R.M.Rangayyan, IEEE Press/ Wiley 2002

Discrete-Time Signal Processing, A.V.Oppenheim, R.W.Schafer, Prentice Hall
Planned Learning Activities and Teaching Methods
  • Lecture
  • Questions/Answers
  • Problem Solving
  • Report Preparation
  • Experiment
Assessment Methods and Criteria
Quantity Percentage (%)
Mid-term 1 30
Quiz 5 15
Practice 1 20
Total(%) 65
Contribution of In-term Studies to Overall Grade(%) 65
Contribution of Final Examination to Overall Grade(%) 35
Total(%) 100
Language of InstructionTurkish
Work Placement(s)No

Programme Qualifications / Learning Outcomes

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K2 X X X X
K3 X X
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K5 X
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