###### Abstract
The reason behind this is that there are controversies about the applicability of this method in clinical diagnostics and the lack of large-population studies that could establish the guidelines for follow-up and those patient groups in which it would have the highest benefit. One reason why the applicability of the method is debated that the parameters computed from DVP are sensitive to errors and cannot be detected reliably as they fluctuate from one measurement to another even if the cardiovascular status of the patient is stable [20; 21; 22; 23]. However, this controversy is fostered in part by the fact that no data are available in the scientific literature about the reliability of the measurements. This issue is particularly emphasized in the case of those parameters which are derived from the second derivative of the DVP. The second derivative of the DVP (often referred to as acceleration plethysmogram) has several distinguished points from which valuable cardiovascular indices can be calculated (Figure 1). Among these, c and d points have been introduced as characteristics that may facilitate our understanding of the dynamics of wave reflection and the pulse wave analysis based evaluation of the severity of arterial aging [14; 24; 25; 26; 27; 28]. However, the detection of these points has become a challenge for mathematical algorithms to identify [8; 29; 30]. This study was designed to address these controversies in order to show that the detection and computation of DVP contour parameters is a reliable method. We postulated that fluctuations in measured values most probably reflect real changes in cardiovascular functioning and are not caused by poor reliability of DVP analysis. To answer our specific questions, we used a PPG-based telemedicine system which has been developed with the participation of our research team (SCN4 ALL ver.1.0, E-Med4 All Europe Ltd., Budapest, Hungary) (Figure 2), and we analyzed nine pulse contour parameters, the medical significance of which has been proposed by various studies (Figure 1). Our specific questions addressed not only the reliability of DVP analysis in general, but also the measurement reliability of our system. Figure 1: Pulse contour parameters calculated by the SCN4 ALL system. Representative pulse wave recording (panel **A**), and its first (panel **B**) and second derivative curves (panel **C**). ET represents ejection time measured as the duration between the foot of the pulse wave and the dicrotic notch. ET was normalized for heart rate to calculate left ventricular ejection time index (LVETI) using the formulae LVETI = 1.7 \(\times\) heart rate + ET and LVETI = 1.6 \(\times\) heart rate + ET in males and females, respectively. Pulse transit time (PTT) is the duration measured between the systolic and diastolic peaks of the curve. PTT was used to calculate stiffness index as the height of the subject over PT. IBI represents interbeat interval, which is the pulse duration measured from peak to peak. Here, x and y are amplitudes of the systolic and diastolic peaks, respectively, and are used for calculation of the reflection index as x/y. Points a–e represent notable inflection points of the second derivative curve. Second derivative inflection points were used to calculate b/a, d/a, aging index (calculated as (b – c – d – e)/a), and c–d point detection ratio (the percentage of pulse cycles in the 2-min recording in which c and d points were successfully identified by the algorithm). Figure 2: Outline of the SCN4 ALL telemedicine system. Peripheral arterial pulse wave is detected by a transmission pulse oximeter. The device (Berry Pulse Oximeter, Shanghai Berry Electronic Tech Co., Ltd., Shanghai, China) communicates via Bluetooth connection with a mobile application (SCN4 ALL) which initiates and terminates the 2-min-long data acquisition and transmits the recording to a cloud database.