Key result
Markovian analysis of cardiorespiratory data demonstrates that respiratory frequency strongly influences cardiac frequency.
Observational (n=18)
Markovian analysis provides a novel mathematical model to understand the strength and direction of cardiorespiratory phase coupling and synchronization.
May advance cardiorespiratory modeling; hypothesis-generating and should not yet change practice.
Markovian analysis is applied to derive nonlinear stochastic equations for the reconstruction of heart rate and respiration rate variability data. A model of their 'phase' interactions is obtained for the first time, thereby gaining new insights into the strength and direction of the cardiorespiratory phase coupling. The reconstructed model can reproduce synchronisation phenomena between the cardiac and the respiratory systems, including switches in synchronisation ratio. The technique is equally applicable to the extraction of the multi-dimensional couplings between many interacting subsystems.
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Bahraminasab et al. (2008) conducted an observational in Healthy (n=18). Cardiorespiratory phase coupling was evaluated on Synchronization behavior of original and reconstructed pairs of HRV and RRV signals. Markovian analysis of cardiorespiratory data successfully reconstructed a model that reproduces synchronization phenomena and demonstrates that respiratory frequency strongly influences cardiac frequency.
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