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EEG Laboratory

General data

Course ID:	1100-3BN20
Erasmus code / ISCED:	13.2 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0533) Physics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	EEG Laboratory
Name in Polish:	Laboratorium EEG
Organizational unit:	Faculty of Physics
Course groups:	APBM - Neuroinformatics; 3rd year courses
Course homepage:	https://brain.fuw.edu.pl/edu/index.php/Laboratorium_EEG
ECTS credit allocation (and other scores):	8.00 Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	Polish
Prerequisites (description):	Prior to this course a student should complete the following courses: 1. EEG Workshop
Mode:	Classroom
Short description:	Introduction to Matlab Svarog-Matlab file converter EEGLAB package basics The blind sources separation method Time-frequency methods Event-related synchronization/desynchronization Brain-computer interfaces: SSVEP paradigm P300 paradigm
Learning outcomes:	After having completed the course a student should: KNOWLEDGE 1. Know the advanced methods of analysis of brain electrical activity. 2. Know the basics of construction of brain-computer interfaces. ABILITIES 1. Be able to perform advanced EEG signal analysis using Matlab and EEGLAB packages. 2. Be able to design brain-computer interface using Open BCI system. BASICS 1. Recognize the importance of signal analysis in description, characterization and practical application of recordings of brain electrical activity
Assessment methods and assessment criteria:	The assessment takes into account the presentation of individual exercises and the whole student's work during the classes. Two excused absences are permitted.

Classes in period "Summer semester 2023/24" (in progress)

Time span:	2024-02-19 - 2024-06-16	Selected timetable range: weekly course term Navigate to timetable MO TU LAB W LAB TH FR
Type of class:	Lab, 90 hours, 24 places more information
Coordinators:	Maciej Kamiński, Jarosław Żygierewicz
Group instructors:	Maciej Kamiński, Jarosław Żygierewicz
Students list:	(inaccessible to you)
Examination:	Course - Grading Lab - Grading

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