COMPLEXITY-BASED DECODING OF THE BRAIN REACTIONS TO VISUAL STIMULI WITH DIFFERENT FREQUENCIES

Sriram Parthasarathy, Karthikeyan Rajagopal, Ondrej Krejcar, Robert Frischer and Hamidreza Namazi
Additional contact information
Sriram Parthasarathy: Centre for Computational Modelling, Chennai Institute of Technology, Chennai 600069, Tamil Nadu, India
Karthikeyan Rajagopal: ��Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai 600069, Tamil Nadu, India
Ondrej Krejcar: ��Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, 50003 Hradec Kralove, Czechia§Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czechia¶Department of Biomedical Engineering and Measurement, Faculty of Mechanical Engineering, Technical University of Kosice, Slovakia
Robert Frischer: �Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czechia
Hamidreza Namazi: ��Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, 50003 Hradec Kralove, Czechia∥School of Engineering, Monash University, Selangor, Malaysia

FRACTALS (fractals), 2023, vol. 31, issue 03, 1-8

Abstract: Analysis of the brain activity to external stimulation is an important area of research in biomedical engineering. In this paper, for the first time, we analyzed the brain reaction to visual stimuli with different frequencies using three complexity methods. For this purpose, we utilized fractal theory, sample entropy, and approximate entropy to study the variations of the complexity EEG signals while subjects received visual stimuli at 7, 9, 11, and 13 Hz. The results showed that, in general, by moving from 9 Hz to 13 Hz stimuli, the complexity of EEG signals increases, except in the case of 11 Hz stimulus. The statistical analysis also supported the results of the analysis. The conducted analysis in this research can be performed in the case of other types of external stimuli to study how the brain reacts in different conditions.

Keywords: Complexity; Brain; Visual Stimuli; Fractal Theory; Sample Entropy; Approximate Entropy (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0218348X2350055X
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:fracta:v:31:y:2023:i:03:n:s0218348x2350055x

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0218348X2350055X

Access Statistics for this article

FRACTALS (fractals) is currently edited by Tara Taylor

More articles in FRACTALS (fractals) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().