We compare the spectral indices of photoplethysmogram variability (PPGV) estimated using photoplethysmograms recorded from the earlobe and the middle fingers of the right and left hand and analyze their correlation with similar indices of heart rate variability (HRV) in 30 healthy subjects (26 men) aged 27 (25, 29) years (median with inter-quartile ranges) at rest and under the head-up tilt test. The following spectral indices of PPGV and HRV were compared: mean heart rate (HR), total spectral power (TP), high-frequency (HF) and low-frequency (LF) ranges of TP in percents (HF% and LF%), LF/HF ratio, and spectral coherence. We assess also the index S of synchronization between the LF oscillations in HRV and PPGV. The constancy of blood pressure (BP) and moderate increase of HR under the tilt test indicate the presence of fast processes of cardiovascular adaptation with the increase of the sympathetic activity in studied healthy subjects. The impact of respiration on the PPGV spectrum (accessed by HF%) is less than on the HRV spectrum. It is shown that the proportion of sympathetic vascular activity (accessed by LF%) is constant in the PPGV of three analyzed PPGs during the tilt test. The PPGV for the ear PPG was less vulnerable to breathing influence accessed by HF% (independently from body position) than for PPGs from fingers. We reveal the increase of index S under the tilt test indicating the activation of interaction between the heart and distal vessels. The PPGV spectra for finger PPGs from different hands are highly coherent, but differ substantially from the PPGV spectrum for the ear PPG. We conclude that joint analysis of frequency components of PPGV (for the earlobe and finger PPGs of both hands) and HRV and assessment of their synchronization provide additional information about cardiovascular autonomic control.

We propose a method for the recovery of coupling architecture and the parameters of elements in networks consisting of coupled oscillators described by delay-differential equations. For each oscillator in the network, we introduce an objective function characterizing the distance between the points of the reconstructed nonlinear function. The proposed method is based on the minimization of this objective function and the separation of the recovered coupling coefficients into significant and insignificant coefficients. The efficiency of the method is shown for chaotic time series generated by model equations of diffusively coupled time-delay systems and for experimental chaotic time series gained from coupled electronic oscillators with time-delayed feedback.

No abstract