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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS BMT 5007 WAVELETS IN 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

ASISTANT PROFESSOR GÜLTER GÜLDEN KÖKTÜRK

Offered to

Industrial Ph.D. Program In Advanced Biomedical Technologies Biomedical Tehnologies (English)

Course Objective

This course is designed to give information on the theory and application of wavelets in biomedical processing and applications. Starting at introductory level, the course covers fundamental concepts of wavelet theory including the continuous wavelet transform, and discrete wavelet transform; it then progresses into the algorithms of biomedical signals.

Learning Outcomes of the Course Unit

1   Teach to the student the basis of the wavelet transform 2   Improve analytical abilities of the student 3   Teach to wavelets in biomedical techniques

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to wavelet analysis 2 Continuous and discrete wavelet transform in ECG recognation 3 Wavelet transforms for the analysis of cardiac signals 4 Wavelet models of even related potentials 5 Wavelet future extraction from neuropysiological signals 6 EEG spike detection using wavelets 7 Midterm 8 Speech enhancement using wavelets for hearing aids 9 Analysis of cohlear implants using discrete wavelet transform and wavelet packets 10 Adapted wavelet denoising for medical signals and images 11 Wavelet compression of medical signal and images 12 Wavelets and tomography 13 Analysis of mammogram images with wavelets 14 Hybrid wavelet transform in telemedicine

Recomended or Required Reading

M. Akay, "Time frequency and wavelets in biomedical signal processing", IEEE Press, 1996.

Planned Learning Activities and Teaching Methods

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 PRJ PROJECT 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE *0.25 + PRJ *0.45 +FIN *0.30 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE *0.25 +PRJ *0.45 +RST *0.30

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

gulden.kokturk@deu.edu.tr Tel: 232-3017165

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 1 13 13 Preparations before/after weekly lectures 13 6 78 Preparation for midterm exam 1 10 10 Preparation for final exam 1 12 12 Design Project 13 6 78 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 197

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