Information and memory-based analysis for decoding of the human learning between normal and virtual reality (vr) conditions

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F21%3A50018049" target="_blank" >RIV/62690094:18450/21:50018049 - isvavai.cz</a>

Result on the web

<a href="https://www.worldscientific.com/doi/abs/10.1142/S0218348X21501632" target="_blank" >https://www.worldscientific.com/doi/abs/10.1142/S0218348X21501632</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1142/S0218348X21501632" target="_blank" >10.1142/S0218348X21501632</a>

Result language

angličtina

Original language name

Information and memory-based analysis for decoding of the human learning between normal and virtual reality (vr) conditions

Original language description

In this paper, we investigated the learning ability of students in normal versus virtual reality (VR) watching of videos by mathematical analysis of electroencephalogram (EEG) signals. We played six videos in the 2D and 3D modes for nine subjects and calculated the Shannon entropy of recorded EEG signals to investigate how much their embedded information changes between these modes. We also calculated the Hurst exponent of EEG signals to compare the changes in the memory of signals. The analysis results showed that watching the videos in a VR condition causes greater information and memory in EEG signals. A strong correlation was obtained between the increment of information and memory of EEG signals. These increments also have been verified based on the answers that subjects gave to the questions about the content of videos. Therefore, we can say that when subjects watch a video in a VR condition, more information is transferred to their brains that cause increments in their memory. © 2021 Cambridge University Press. All rights reserved.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10103 - Statistics and probability

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Fractals

ISSN

0218-348X

e-ISSN

—

Volume of the periodical

29

Issue of the periodical within the volume

3

Country of publishing house

SG - SINGAPORE

Number of pages

8

Pages from-to

"Article number 2150163"

UT code for WoS article

000644726400009

EID of the result in the Scopus database

2-s2.0-85104956415