Non-invasive assessment of integrated cardiorespiratory network dynamics after physiological stress in humans

Background Physiological variables provide critical insights into the integrated control of the cardiorespiratory system, reflecting the body’s real-time responses to internal and external perturbations. Visualizing the exchange of information between different components of the cardiorespiratory system is beneficial for monitoring individuals in various clinical settings and extreme environments. This study aimed to develop a non-invasive method, using principles of information theory, to visualize the flow of information between physiological variables, with a focus on the integrated cardiorespiratory responses to different physiological stressors. Methods Heart rate, respiratory rate, minute ventilation, respiratory frequency, tidal volume, capillary oxygen saturation (SpO 2 ), end-tidal oxygen, and end-tidal carbon dioxide concentrations were recorded from 22 healthy participants. Transfer entropy, which reflects measures of causal relationships between parallel time-series, was used to compute the flow of information between cardiorespiratory signals into network maps. Network mapping was performed after rest in a control condition and following exposure to the isolated and combined effects of normobaric hypoxia (FIO 2 : 0.12), moderate intensity cycling exercise (100W), and overnight sleep deprivation. For each intervention, 10-minute segments of physiological signals (from minutes 5 to 15 after the commencement of hypoxia and/or exercise) were used for analysis. Results Each physiological stressor was associated with a distinctive pattern of information flow between physiological variables. Hypoxia led to the engagement of SpO 2 a hub in the network, facilitating the exchange of information with end-tidal oxygen concentration and heart rate. Sleep deprivation was associated with a shift in the flow of information from SpO 2 to other nodes, such as respiratory rate, during hypoxia. During exercise, heart rate emerged as the central node for receiving information, while SpO 2 acted as the primary node disseminating information to other nodes. Increased connectivity within the networks was observed during exercise alone or when combined with other stressors. Conclusion This non-invasive network mapping technique visualizes the interaction of various cardiorespiratory variables following exposure to physiological stressors. By mapping normative responses, this approach may help identify outliers associated with various disease states.