Signal Processing for Brain Interfaces

Course Information
TitleΕπεξεργασία Σήματος για Εγκεφαλικές Διεπαφές / Signal Processing for Brain Interfaces
CodeDMCI204
FacultySciences
SchoolInformatics
Cycle / Level2nd / Postgraduate
Teaching PeriodSpring
CoordinatorNikolaos Laskaris
CommonNo
StatusActive
Course ID600016148

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

Registered students: 1
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses belonging to the selected specialization217.5

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

Registered students: 20
OrientationAttendance TypeSemesterYearECTS
KORMOSElective Courses belonging to the selected specialization217.5

Class Information
Academic Year2018 – 2019
Class PeriodSpring
Faculty Instructors
Weekly Hours3
Class ID
600132008
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Language of Instruction
  • Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Digital Signal Processing. Pattern recognition. Computational Intelligence. MATLAB
Learning Outcomes
Gaining a deeper understanding of signal processing techniques. Exposition to current trends in BCI research and applications. Acquaintance with brain activity decoding techniques.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
  • Generate new research ideas
  • Be critical and self-critical
Course Content (Syllabus)
Basic principles of Neurophysiology. Evoking and recording brain activity. Digital techniques in brain signal analysis (spike-sorting, spectral and wavelet analysis, nonlinear dynamics, etc.). Spatial filtering and multivariate techniques for multichannel signal processing. Brainwaves decoding in BCI. Applications in clinical rehabilitation and modern paradigms of human-machine interaction.
Keywords
signal analysis, brain activity decoding
Educational Material Types
  • Notes
  • Slide presentations
  • Book
  • matlab software
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures30
Laboratory Work45
Reading Assigment60
Project90
Total225
Student Assessment
Description
In the final mark contibute : 1) the deliverable of a student-specific project (50%) 2) the performance in the analysis and presentation of a journal-article from the recent bibliography (30%) 3) written exams (20%)
Student Assessment methods
  • Written Exam with Short Answer Questions (Summative)
  • Performance / Staging (Summative)
  • Report (Summative)
Bibliography
Additional bibliography for study
Rao R. Brain-Computer Interfacing: An Introduction. Cambridge University Press. 2013 and a collection of tutorial articles.
Last Update
28-01-2020