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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EEE 5076 BIOMEDICAL SIGNAL PROCESSING ELECTIVE 3 0 0 8

Offered By

Medical Informatics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

Offered to

Medical Informatics

Course Objective

The course aims to provide the students with a detailed knowledge on various signal processing techniques used for the analysis of biological signals.

Learning Outcomes of the Course Unit

1   Understand different kinds of biological signals that originate from the human body. 2   Use the appropriate signal processing tools to analyze these signals.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Characteristics of Biomedical Signals 2 Effects of Windowing 3 Preprocessing of Biomedical Signals 4 Signal Averaging, ERP and LP Applications 5 FIR Filter Design, Biomedical Applications 6 IIR Filter Design, Biomedical Applications 7 Optimal and Adaptive Filtering, Biomedical Applications 8 HRV Analysis I (Frequency Domain) 9 HRV Analysis II (Time Domain) 10 EEG Signal Processing (qEEG, Spike Detection) 11 Time-Frequency Analysis, Biomedical Applications 12 Wavelet Transform, Biomedical Applications 13 ECG Arrhythmia Classification 14 Midterm

Recomended or Required Reading

Biomedical Signal Processing and Signal Modeling, E.N.Bruce, John Wiley and Sons. Inc., 2001. Metin Akay, Biomedical Signal Processing , Academic Press, San Diego, 1994. Joseph D. Bronzino, The Biomedical Engineering Handbook , CRC Press, Hartford, 1995.

Planned Learning Activities and Teaching Methods

Lecture+Exam+Homeworks

Assessment Methods

Successful / Unsuccessful *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Lecture+Exam+Homeworks

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

mehmet.kuntalp@deu.edu.tr

Office Hours

will be posted

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparing assignments 5 12 60 Preparations before/after weekly lectures 12 5 60 Preparation for midterm exam 1 25 25 Midterm 1 4 4 TOTAL WORKLOAD (hours) 188

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 PO.14 PO.15 PO.16 LO.1 5 5 5 5 5 LO.2 5 5 5 5