BIOSIGNAL ANALYSIS- BIOINFORMATICS

Course Information
TitleΑΝΑΛΥΣΗ ΒΙΟΣΗΜΑΤΩΝ-ΒΙΟΠΛΗΡΟΦΟΡΙΚΗ / BIOSIGNAL ANALYSIS- BIOINFORMATICS
CodeNDM03
FacultySciences
SchoolInformatics
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter
CoordinatorNikolaos Laskaris
CommonNo
StatusActive
Course ID40003485

Class Information
Academic Year2017 – 2018
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Class ID
600110526
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Good knowledge of signal processing techniques and basics of pattern analysis and computational intelligence
Learning Outcomes
To familiarize with digital techniques of processing, analyzing and handling the information in biosignals and get introduced to their applications in contemporary digital media paradigms.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Be critical and self-critical
Course Content (Syllabus)
Biosignals (recording techniques, signal processing principles, analysis and modeling, monitoring in clinical settings). Introduction to Electrophysiology. Basic Principles of Cognitive Neurophysiology and Neuroinformatics (modern techniques in neuroscience research, functional mapping techniques, handling and analyzing the experimental data). Theoretical models for sensory systems and higher brain functions. Information processing in the brain. Applications in Digital Media. Computer perception for intelligent interfaces. Brain - computer interfaces. Affective computation. Foundamental concepts of Bioinformatics. Analyzing DNA, RNA and protein sequences in databases. Protein analysis and proteomics. Digital techniques for analyzing gene expression
Keywords
biosignal analysis, neuroinformatics
Educational Material Types
  • Notes
  • Slide presentations
  • Multimedia
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
Description
software demos related to the analysis of particular types of biosignals
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures301
Laboratory Work451.5
Reading Assigment602
Project903
Total2257.5
Student Assessment
Description
The final mark reflects the performance in written exams (30%), oral presentation of a recent paper(30%) and implementation of a project (40%)
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Exam with Short Answer Questions (Summative)
  • Performance / Staging (Summative)
  • Report (Summative)
Bibliography
Course Bibliography (Eudoxus)
1) J. Semmlow. Biosignal and biomedical image processing: MATLAB-based applications. Marcel Dekker (ed). 2004 2) D.E. Krane and M.L Raymer. ' Fundamental concepts of Bioinformatics'. Benjamin Cummings(ed). 2002 3) Selected review papers
Additional bibliography for study
U. Windhorst & H. Johansson. Modern Techniques in Neuroscience Research. Springer (ed.).1999
Last Update
30-06-2018