
pmid: 23446924
Abstract The analysis of effects from coupling in and between systems is important in data-driven investigations as practiced in many scientific fields. It allows deeper insights into the mechanisms of interaction emerging among individual smaller systems when forming complex systems as in the human circulatory system. For systems featuring various regimes, usually only the epochs before and after a transition between different regimes are analyzed, although relevant information might be hidden within these transitions. Transient behavior of cardiovascular variables may emerge, on the one hand, from the recovery of the system after a severe disturbance or, on the other hand, from adaptive behavior throughout changes of states. It contains important information about the processes involved and the relations between state variables such as heart rate, blood pressure, and respiration. Therefore, we apply an ensemble approach to extend the method of symbolic coupling traces to time-variant coupling analysis. These new ensemble symbolic coupling traces are capable of determining coupling direction, strength, and time offset τ from transient dynamics in multivariate cardiovascular data. We use this method to analyze data recorded during an orthostatic test to reveal a transient structure that cannot be detected by classic methods.
Male, Models, Cardiovascular, Blood Pressure, Blood Pressure Determination, Signal Processing, Computer-Assisted, Electrocardiography, Heart Rate, Tilt-Table Test, Humans, Computer Simulation, Female, Sleep, Algorithms
Male, Models, Cardiovascular, Blood Pressure, Blood Pressure Determination, Signal Processing, Computer-Assisted, Electrocardiography, Heart Rate, Tilt-Table Test, Humans, Computer Simulation, Female, Sleep, Algorithms
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