COMPLEXITY-BASED ANALYSIS OF THE CORRELATION OF BRAIN AND HEART ACTIVITY IN YOUNGER AND OLDER SUBJECTS

Najmeh Pakniyat, Gayathri Vivekanandhan, Norazryana Mat Dawi, Ondrej Krejcar, Robert Frischer and Hamidreza Namazi
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Najmeh Pakniyat: 30 Shore Breeze Drive, Toronto, ON M8V 0J1, Canada
Gayathri Vivekanandhan: ��Centre for Artificial Intelligence, Chennai Institute of Technology, Chennai 600069, Tamil Nadu, India
Norazryana Mat Dawi: ��525 West 8th Avenue, Vancouver, Canada
Ondrej Krejcar: �Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Kralove, 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: �Institute of Technology and Business in Ceske Budejovice, Ceske Budejovice, Czechia**Department of Biomedical Engineering, Faculty of Engineering, Universiti Malaya, Malaysia

FRACTALS (fractals), 2024, vol. 32, issue 01, 1-7

Abstract: Studying the activity of organs during aging is a very important research area. On the other hand, simultaneous analysis of the activities of various organs is important to understand how their activities are correlated. For the first time, this research analyzes the brain-heart correlation in younger and older subjects. We analyzed the sample entropy (SampEn) and approximate entropy (ApEn) of EEG and R-R signals (as heart rate variability (HRV)) of younger and older participants while they sat comfortably in an armchair with their eyes open. The results indicated that older subjects’ EEG and R-R signals have greater values of sample and approximate entropies than younger subjects. Therefore, as subjects age, their EEG and R-R signals become more complex. This analysis can be extended to investigate the correlation between other physiological signals among different age groups.

Keywords: EEG Signals; R-R Signals; Correlation; Complexity; SampEn; Approximate Entropy (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0218348X24500142

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