Understanding the correlation between the brain’s activity and the physiological responses of other organs under varying conditions is a crucial area of research that holds significant potential for advancing our knowledge of human physiology. In this study, we focused on investigating the interaction between the heart and brain by employing advanced complexity analysis techniques, specifically examining the fractal dimension and approximate entropy of electroencephalogram (EEG) and R-R interval time series. The analysis was conducted on data collected from 12 subjects who were observed under three distinct conditions: baseline (normal resting state) and two collaborative activities performed both with and without the presence of noise. Our findings revealed that the complexity patterns of EEG and R-R signals showed similar trends in alterations across all conditions, suggesting a strong coupling between the brain’s and heart’s responses. This observed coupling highlights the potential for a coordinated physiological interaction between these two critical systems. Furthermore, our approach, which successfully decoded the heart–brain correlation, offers a promising framework for extending this analysis to explore correlations between the brain and other organs, thereby contributing to a deeper understanding of the complex networks that underlie human health and adaptive physiological responses.
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