Thesis Details
Psaní na počítači pomocí mozkových signálů
This bachelor thesis focusses on the implementation of a brain-computer interface, programmed in Python language, that would enable to communicate using EEG. The thesis investigates and evaluates existing brain-computer interface technologies for this purpose. The thesis also explores the use of machine learning applied to the technology, in particular neural networks, which have proven to be one of the most accurate methods of EEG signal processing. Following that, 3 different systems are proposed and implemented, each on different paradigm of visually evoking EEG potential changes. These systems were tested with different signal classification approaches. Unfortunately, none of the systems proved to be useful in communication.
BCI, EEG, brain-computer, brain, electroencephalograph, VEP, SSVEP, f-VEP, P300, c-VEP, visually evoked, Python, OpenBCI, speller, CNN, convolutional neural network
Hradiš Michal, Ing., Ph.D. (DCGM FIT BUT), člen
Jaroš Jiří, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Křivka Zbyněk, Ing., Ph.D. (DIFS FIT BUT), člen
@bachelorsthesis{FITBT23566,
author = "Luk\'{a}\v{s} Wagner",
type = "Bachelor's thesis",
title = "Psan\'{i} na po\v{c}\'{i}ta\v{c}i pomoc\'{i} mozkov\'{y}ch sign\'{a}l\r{u}",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2021,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/23566/"
}