Branje in obdelava signalov eeg - pristop s strojnim učenjem : diplomsko delo

Pavlič, Sašo

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Title:	Branje in obdelava signalov eeg - pristop s strojnim učenjem : diplomsko delo
Authors:	ID Pavlič, Sašo (Author) ID Karakatič, Sašo (Mentor) More about this mentor... ID Bizjak, Boris (Comentor)
Files:	VS_Pavlic_Saso_2019.pdf (1,57 MB) MD5: 672C78F36CC776DC3A82B08357172F26 PID: 20.500.12556/dkum/b22acd52-37a5-4816-b31c-7d1731fbf084
Language:	Slovenian
Work type:	Bachelor thesis/paper
Typology:	2.11 - Undergraduate Thesis
Organization:	FERI - Faculty of Electrical Engineering and Computer Science
Abstract:	Diplomska naloga zajema spoznavanje in predstavitev z osnovami EEG-možganskih valov s pomočjo naprave Emotiv Insight. Zajeti EEG-podatki predstavljajo vhodne podatke v modelu strojnega učenja, s pomočjo katerega se je ugotavljalo, kdaj in kje se pojavljajo iskani vzorci. Eksperiment razvite metode zajema podatkov in uporabe modela se je izvedel tako, da se je testni subjekt izpostavil izmenjujočim izbranim slikam, ob tem pa so se z napravo Emotiv Insight zajeli EEG-možganski valovi. Zajeti EEG-podatki so služili kot zbirka podatkov, iz katere se je učil klasifikacijski model umetne nevronske mreže, ki uspešno razpoznava, kdaj je testni subjekt podvržen eni vrsti slik in kdaj drugi.
Keywords:	EEG, možganski valovi, strojno učenje, BCI-naprava, snemanje podatkov
Place of publishing:	Maribor
Place of performance:	Maribor
Publisher:	[S. Pavlič]
Year of publishing:	2019
Number of pages:	IV, 52 f.
PID:	20.500.12556/DKUM-74428
UDC:	004.383.3:612.82(043.2)
COBISS.SI-ID:	22842134
NUK URN:	URN:SI:UM:DK:KAPX9PN8
Publication date in DKUM:	13.11.2019
Views:	1585
Downloads:	126
Metadata:
Categories:	KTFMB - FERI
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Licences

License:	CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	27.08.2019

Secondary language

Language:	English
Title:	Reading and processing eeg signals - the machine learning approach
Abstract:	The diploma thesis covers cognition and presentation, with the basics of EEG brain waves using the Emotiv Insight device. The captured EEG data represents the input data into a machine learning model, which was used to determine when and where the required patterns appear. The experiment of the developed method of capturing data and model usage was carried out by exposing the test subject to the alternating selected images and capturing the EEG brain waves with the Emotiv Insight device. The captured EEG data served as a database from which the artificial neural network classification model learnt to successfully recognize when a test subject was exposed to one type of image and when to another.
Keywords:	EEG, brainwaves, machine learning, BCI device, recording data

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