ANALYSIS OF THE EFFECT OF VARIOUS MENTAL TASKS ON THE EEG SIGNALS' COMPLEXITY

被引：0

作者：

Pakniyat, Najmeh ^{[1
]}

Krejcar, Ondrej ^{[2
,3
]}

Maresova, Petra ^{[2
,3
]}

Abdullah, Jamaluddin ^{[4
]}

Namazi, Hamidreza ^{[2
,4
]}

机构：

[1] 30 Shore Breeze Dr, Toronto, ON M8V 0J1, Canada

[2] Univ Hradec Kralove, Fac Informat & Management, Hradec Kralove, Czech Republic

[3] Univ Teknol Malaysia Kuala Lumpur, Malaysia Japan Int Inst Technol, Jalan Sultan, Kuala Lumpur 54100, Malaysia

[4] Univ Sains Malaysia, Sch Mech Engn, Nibong Tebal 14300, Penang, Malaysia

来源：

FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY | 2024年 / 32卷 / 03期

关键词：

Mental Tasks; Complexity; EEG Signals; Fractal Theory; Sample Entropy; Approximate Entropy; BACKGROUND ACTIVITY; ENTROPY ANALYSIS; SAMPLE ENTROPY; DISEASE;

D O I：

10.1142/S0218348X24500683

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Analysis of the brain activity in different mental tasks is an important area of research. We used complexity-based analysis to study the changes in brain activity in four mental tasks: relaxation, Stroop color-word, mirror image recognition, and arithmetic tasks. We used fractal theory, sample entropy, and approximate entropy to analyze the changes in electroencephalogram (EEG) signals between different tasks. Our analysis showed that by moving from relaxation to the Stroop color-word, arithmetic, and mirror image recognition tasks, the complexity of EEG signals increases, respectively, reflecting rising brain activity between these conditions. Furthermore, only the fractal theory could decode the significant changes in brain activity between different conditions. Similar analyses can be done to decode the brain activity in case of other conditions.

引用

页数：7

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