Thesis Details
Analýza a klasifikace dat ze snímače mozkové aktivity
This thesis describes recording, processing and classifying brain activity which is being captured by a brain-computer interface (BCI) device manufactured by OpenBCI company. Possibility of use of such a device for controlling an application with brain activity, specifically with thinking of left or right hand movement, is discussed. To solve this task methods of signal processing and machine learning are used. As a result a program that is capable of recording, processing and classifying brain activity using an artificial neural network is created. An average accuracy of classification of synthetic data is 99.156%. An average accuracy of classification of real data is 73.71%.
elektroencefalography, EEG, brain-computer interface, BCI, OpenBCI, machine learning, neural network, classification
Čadík Martin, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Lengál Ondřej, Ing., Ph.D. (DITS FIT BUT), člen
Malinka Kamil, Mgr., Ph.D. (DITS FIT BUT), člen
Polčák Libor, Ing., Ph.D. (DIFS FIT BUT), člen
Veselý Vladimír, Ing., Ph.D. (DIFS FIT BUT), člen
@mastersthesis{FITMT22257, author = "Alexandr Persich", type = "Master's thesis", title = "Anal\'{y}za a klasifikace dat ze sn\'{i}ma\v{c}e mozkov\'{e} aktivity", school = "Brno University of Technology, Faculty of Information Technology", year = 2020, location = "Brno, CZ", language = "czech", url = "https://www.fit.vut.cz/study/thesis/22257/" }