Key result
Analytical dynamic models coupled with signal processing of real clinical data can be used for real-time computer monitoring of self-organization and chaos degree in pulse propagation.
Theoretical nonlinear reaction-diffusion models may provide a novel method for real-time monitoring of chaos and self-organization in cardiac electrical activity and circulation.
May support model-based cardiac monitoring exploration; leaves open prospective validation before clinical use.
The paper shows that analytical dynamic models coupled with the available signal processing methods could be used for describing the self‐organization and chaos degree in the heartbeats propagation and pressure pulses in ventricular at ejection phase. We proposed a unit analytical approach that could be associated with real ECG and pressure pulses signal processing. Our findings confirm that the real‐time computer monitoring of the main cardiovascular parameters obtained by the use of analytical models and verified by signal processing of real clinical data may be considered as available method for measuring and controlling self‐organization and chaos degree in pulse propagation.
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Kardashov et al. (2006) studied Electrical cardiac activity and cardiovascular circulation. Analytical dynamic models coupled with signal processing methods was evaluated on Self-organization and chaos degree in heartbeat propagation and pressure pulses. Analytical dynamic models coupled with signal processing of real clinical data can be used for real-time computer monitoring of self-organization and chaos degree in pulse propagation.
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