*4.3. Data Acquisition and Preprocessing*

Continuous hemodynamic monitoring of blood pressure (BP), heart rate (HR), and thoracic impedance was carried out with the Task Force Monitor ® (TFM ®; CNSystems, Graz, Austria) throughout the entire test procedure. HR (3-lead electrocardiography; sampling rate = 1 kHz) and thoracic impedance (sampling rate = 50 Hz) were recorded using specific CNSystems electrodes placed at the neck and the thoracic region, the latter specifically at the midclavicular line at the xiphoid process level. Continuous BP (sampling rate = 100 Hz) was derived from the finger using a refined version of the vascular unloading technique and corrected to absolute values with oscillometric BP measurement on the contralateral upper arm [81]. For analyzing the cardiovascular regulation, software-tools developed in MATLAB ® (MathWorks, Natick, MA, USA) were used [29,82].

To obtain R–R intervals (RRI) and blood pressure time series with equidistant time steps, the beat-to-beat values were resampled at 4 Hz, using piecewise cubic spline interpolation after semiautomatic artifact correction. Single artifacts were replaced by interpolation [82]. Furthermore, the respiratory signal was derived from the thoracic impedance and downsampled to 4 Hz to obtain corresponding sampling times as RRI and BP.

The sequence technique was used for the assessment of baroreceptor reflex sensitivity (BRS) [83]. This technique is based on identifying consecutive cardiac beats in which an increase in systolic blood pressure is accompanied by an increase in RRI, or in which a decrease in systolic blood pressure is accompanied by a decrease in RRI. The regression line between the systolic blood pressure and RRI produces an estimate of BRS. We defined an equivalent change in heart rate and systolic blood pressure for at least three consecutive cardiac cycles as a regulatory event if the following criteria were fulfilled: RRI variations >4 ms and systolic blood pressure changes >1 mmHg [31].

### *4.4. Analysis Procedure Using Phase Synchronization*

The analysis of synchronization, e.g., of R–R intervals and systolic blood pressure, is based upon the weak coupling of two di fferent systems, which can be analyzed using the concept of analytic signals [29,35,84]. For this purpose, a phase (but not its amplitude) needs to be defined for a time series that contains oscillations in a narrow frequency band. That is, the adjustments of the rhythms of the R–R intervals, blood pressure, and respiration were partitioned for the sympathetic and the parasympathetic branches of the autonomic nervous system [29]. To permit a clear physical interpretation, we used the Hilbert transform to compute the so-called discrete-time analytic signal *X* D, with *X* D = *X*R + *i*·*X*I such that *X*I is the Hilbert transform of the real vector *X*R, from the band-pass filtered time series. Subsequently, the phase of the resulting signals *X*D1(*t*i) and *X*D2(*t*i) at every time point ti and the di fference between these two given phase vectors for the interpolated bivariate data series, e.g., between heart rate and respiration, was calculated.

The time series are defined as synchronized if the phase di fference Ψ(*t*i) is constant over time. In case of synchronization, the distribution of the phase di fference, quantified by the synchronization index γ = {cos( Ψ(*t*i))}<sup>2</sup> + {sin( Ψ(*t*i))}2, shows a definite maximum. Theoretically, if the synchronization index γ = 1, then both time series are completely synchronized in a statistical sense, while in the case of γ = 0, both time series are completely desynchronized. Thus, the analysis of phase synchronization provides a quantitative indicator of the coordinated behavior of pairs of systems (i.e., in this case, R–R intervals and systolic blood pressure, partitioned for the sympathetic and the parasympathetic branches of the autonomic nervous system).
