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ANALYSIS OF THE CHANGES IN THE BRAIN ACTIVITY BETWEEN REST AND MULTITASKING WORKLOAD BY COMPLEXITY-BASED ANALYSIS OF EEG SIGNALS

Sriram Parthasarathy, Petra Maresova, Karthikeyan Rajagopal and Hamidreza Namazi
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Sriram Parthasarathy: Centre for Computational Modelling, Chennai Institute of Technology, Chennai 600069, Tamil Nadu, India
Petra Maresova: ��Faculty of Informatics and Management, University of Hradec Kralove, Hradec, Kralove, Czechia‡Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia Kuala Lumpur, Jalan Sultan Yahya Petra, Kuala Lumpur 54100, Malaysia
Karthikeyan Rajagopal: �Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai 600069, Tamil Nadu, India
Hamidreza Namazi: ��Faculty of Informatics and Management, University of Hradec Kralove, Hradec, Kralove, Czechia¶School of Engineering, Monash University, Selangor, Malaysia

FRACTALS (fractals), 2023, vol. 31, issue 09, 1-7

Abstract: Analysis of the changes in brain activity between rest and various conditions is an important area of research. We investigated the changes in brain activity among rest and multitask workload (SIMKAP multitasking test) by quantifying the complexity of EEG signals. The results showed that EEG signals have smaller fractal dimensions, sample entropy, and approximate entropy during the SIMKAP multitasking test than the rest. Therefore, the complexity of EEG signals was lower during the SIMKAP multitasking test than the rest. In further research, we can study the changes in brain activity among other conditions, which has great benefits in decoding brain activity in various conditions.

Keywords: Brain; Complexity; Electroencephalogram (EEG) Signals; SIMKAP Multitasking Test; Fractal Dimension; Sample Entropy; Approximate Entropy (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0218348X23501360

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