Biosignal Analysis- Neuroinformatics

Course Information
TitleΑνάλυση Βιοσημάτων- Νευροπληροφορική / Biosignal Analysis- Neuroinformatics
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter
CoordinatorNikolaos Laskaris
Course ID600016141

Programme of Study: PMS PSĪFIAKA MESA - YPOLOGISTIKĪ NOĪMOSYNĪ (2018 eōs sīmera) MF

Registered students: 2
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses belonging to the selected specialization117.5

Programme of Study: PMS PSĪFIAKA MESA - YPOLOGISTIKĪ NOĪMOSYNĪ (2018 éōs sīmera) PF

Registered students: 12
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses belonging to the selected specialization117.5

Class Information
Academic Year2020 – 2021
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Class ID
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
General Prerequisites
Good knowledge of signal processing techniques and basics of pattern analysis and computational intelligence
Learning Outcomes
Cognitive: To familiarize with digital techniques of processing, analyzing and handling the information in biosignals and get introduced to their modern applications in contemporary digitalized life. Skills: Computational Techniques for analyzing biosignals and neuroscientific data.
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 (recoding, digital processing, analysis, modelling, inspection and automated monitoring). Basic principles of Electrophysiology. Elements from Neurophysiology and Cognitive Neuroscience. NeuroInformatics : contemporary neuroimaging techniques and the extraction-management-scrutiny of information from the experimental data. Introduction to computational neuroscience and the neural modelling of various brain processes and mental faculties. The Brain as a complex system.
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
software demos related to the analysis of particular types of biosignals
Course Organization
Laboratory Work45
Reading Assigment60
Student Assessment
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)
Additional bibliography for study
1. U. Windhorst & H. Johansson. Modern Techniques in Neuroscience Research. Springer (ed.).1999 2. M.Cohen. Analyzing Neural Time Series Data: Theory and Practice (MIT Press).2014 3. A Fornito, A. Zalesky, E Bullmore. Fundamentals of Brain Network Analysis. (Academic Press).2016 & Selected articles from the recent literature.
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