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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

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR MEHMET KUNTALP

Offered to

Ph.D. in Biotechnology Industrial Ph.D. Program In Advanced Biomedical Technologies Industrial Ph.D. Program In Advanced Biomedical Technologies ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH) Biomedical Tehnologies (English) Ph.D. in Biotechnology ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH) BIOTECHNOLOGY ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)

Course Objective

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

Learning Outcomes of the Course Unit

1   Learn different kinds of biomedical signals that originate from the human body. 2   Understand how the preprocessing of these signals is done 3   Use the appropriate signal processing tools to analyze and process these signals.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Biomedical Signals, Databases and Open Sources 2 Preprocessing of Biomedical Signals 3 Signal Detection & Signal Averaging 4 Statistical, Spectral & Noninear Analysis Techniques (HRV) 5 Basics of Pattern Recognition 6 Feature Extraction & Postprocessing 7 Feature Selection & Feature Projection 8 Supervised Classification 9 Unsupervised Classification & Clustering 10 Ensemble of Classifiers 11 Deep Learning 12 Midterm 13 Project Work 14 Project Work

Recomended or Required Reading

to be announced

Planned Learning Activities and Teaching Methods

Research Homework Presentation Report

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 ASG ASSIGNMENT 2 PRS PRESENTATION 3 FCG FINAL COURSE GRADE ASG * 0.50 + PRS * 0.50 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Homework, Midterm, and Term Project

Language of Instruction

English

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 LO.1 2 2 3 2 2 2 LO.2 2 2 4 2 4 1 LO.3 1 1 1 1 1 1