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Information And Memory-Based Analysis For Decoding Of The Human Learning Between Normal And Virtual Reality (Vr) Conditions

Author

Listed:
  • HAMIDREZA NAMAZI

    (College of Engineering and Science, Victoria University, Melbourne, Australia†Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czechia)

  • MOHAMMAD HOSSEIN BABINI

    (College of Engineering and Science, Victoria University, Melbourne, Australia)

  • KAMIL KUCA

    (��Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czechia)

  • ONDREJ KREJCAR

    (��Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, Hradec Kralove, Czechia)

Abstract

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.

Suggested Citation

  • Hamidreza Namazi & Mohammad Hossein Babini & Kamil Kuca & Ondrej Krejcar, 2021. "Information And Memory-Based Analysis For Decoding Of The Human Learning Between Normal And Virtual Reality (Vr) Conditions," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 29(03), pages 1-8, May.
    • Handle: RePEc:wsi:fracta:v:29:y:2021:i:03:n:s0218348x21501632
    DOI: 10.1142/S0218348X21501632
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