DECODING OF HEART–BRAIN RELATION BY COMPLEXITY-BASED ANALYSIS OF HEART RATE VARIABILITY (HRV) AND ELECTROENCEPHALOGRAM (EEG) SIGNALS

Mohammad Hossein Babini, Vladimir V. Kulish, Ondrej Krejcar and Hamidreza Namazi
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Mohammad Hossein Babini: School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor Darul Ehsan, Malaysia
Vladimir V. Kulish: ��Faculty of Mechanical Engineering, Czech Technical University in Prague, Jugoslávských Partyzánů 1580/3, 16000 Prague 6, Czech Republic
Ondrej Krejcar: ��Institute of Technology and Business in Ceske Budejovice, Okruznı 517/10, 37001 Ceske Budejovi, Czech Republic§Center for Basic and Applied Research, Faculty of Informatics and Management, Univerzita Hradec Kralove, Rokitanskeho 62 50003, Hradec Kralove III, Czech Republic¶Malaysia-Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100 Kuala Lumpur, Malaysia
Hamidreza Namazi: School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor Darul Ehsan, Malaysia§Center for Basic and Applied Research, Faculty of Informatics and Management, Univerzita Hradec Kralove, Rokitanskeho 62 50003, Hradec Kralove III, Czech Republic

FRACTALS (fractals), 2022, vol. 30, issue 07, 1-11

Abstract: Since the brain controls heart activations, there should be a correlation between their activities in different conditions. This study investigates the correlation between heart and brain responses to olfactory stimulation. We employed fractal theory and sample entropy to evaluate the complexity of EEG signals and Heart Rate Variability (HRV) in the form of R–R time series. We applied four different pleasant odors with different molecular complexities to 13 participants and analyzed their EEG and ECG signals. The results demonstrated that the complexities of HRV and EEG signals are strongly correlated; a bigger alteration in the complexity of olfactory stimuli is mapped to a bigger alteration in the complexity of HRV and EEG signals. This investigation can be similarly done to examine the correlation between various organs and the brain by quantifying the complexity of their signals versus brain signals.

Keywords: Heart; Brain; Electroencephalogram (EEG) Signals; Fractal Theory; Sample Entropy; R–R Time Series; Complexity (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0218348X22501900

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