## 4 Discussion  
Home monitoring of cardiovascular patients is a promising approach in patient care which is expected to gain ground in the upcoming decades and may constitute a relevant breakthrough in primary and secondary prevention of cardiovascular diseases. Implementation of noninvasive simple measurements, which give a deep insight into the momentary cardiovascular condition of the patient and thus allow extensive evaluation, and reliable fast data analysis are basic requirements for such telemedical systems. Incorporation of photoplethysmography-based analysis of the digital pulse wave in telemedical systems may be an optimal solution for cardiovascular telecare; however, its reliability is debated [21; 33; 34]. Our main purpose was to address the controversies related to the reliability of PPG-based cardiovascular evaluation. We showed that measurement and evaluation of most pulse contour parameters are reliable when analyzed with the SCN4 ALL automated system, which is able to track stable signals with high repeatability. This was confirmed by low test-retest variability of repeated measurements performed under apparently constant cardiovascular conditions. Our study also showed that otherwise valuable pulse contour parameters derived from the second derivative of the DVP curve can only be evaluated with limitations. The detection of c and d deflections on this curve is prone to errors, which interferes with the reliable interpretation of the aging index and d/a parameter, which are indices of arterial stiffening and aging [14; 24; 25; 26; 27; 28]. These limitations are related to typical alterations of pulse wave morphology rather than inaccuracies in analysis, as the automated algorithm used in this study was proven to detect c and d points reliably on normal stable \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Left Index Finger** & **Left Ring Finger** & **Right Index Finger** & **Right Ring Finger** & **ICC** \\ \hline
**Pulse contour** & \(n=25\) & \(n=25\) & \(n=25\) & \(n=25\) & \\
**variables** & _Mean [CI]_ & _Mean [CI]_ & _Mean [CI]_ & _Mean [CI]_ & \\ \hline Aging index & \(-1.29\)\([-1.46;-1.13]\) & \(-1.30\)\([-1.47;-1.13]\) & \(-1.34\)\([-1.15;-1.12]\) & \(-1.47\)\([-1.17;-1.25]\) & \(0.81\) \\ \hline b/a & \(-1.21\)\([-1.26;-1.152]\) & \(-1.22\)\([-1.29;-1.16]\) & \(-1.25\)\([-1.312;-1.20]\) & \(-1.24\)\([-1.30;-1.17]\) & \(0.83\) \\ \hline c-d point detection ratio (\%) & \(33.8\)\([25;3;42.4]\) & \(31.3\)\([23.1;39.5]\) & \(31.9\)\([22;9;40.8]\) & \(32.3\)\([23.9;40.78]\) & \(0.90\) \\ \hline d/a & \(-0.15\)\([-0.24;-0.06]\) & \(-0.16\)\([-0.26;-0.07]\) & \(-0.17\)\([-0.29;-0.06]\) & \(-0.10\)\([-0.21;-0.01]\) & \(0.82\) \\ \hline Left ventricular ejection time index (ms) & \(148\)\([56;240]\) & \(148\)\([57;240]\) & \(147\)\([56;238]\) & \(147\)\([56;237]\) & \(>0.99\) \\ \hline Heart rate (l/min) & \(70.6\)\([67;1;74.2]\) & \(71.0\)\([67;57;42.]\) & \(70.9\)\([67;47;44.]\) & \(71.0\)\([67;47.45]\) & \(>0.99\) \\ \hline Interbeat interval (ms) & \(862\)\([817;906]\) & \(862\)\([818;908]\) & \(862\)\([816;907]\) & \(861\)\([817;907]\) & \(>0.99\) \\ \hline Reflection index (\%) & \(62.2\)\([99;2;65.1]\) & \(60.8\)\([57;64.6]\) & \(61.5\)\([58.4;64.5]\) & \(61.3\)\([57.6;65.0]\) & \(0.81\) \\ \hline Stiffness index (ms) & \(7.74\)\([7.37;8.10]\) & \(7.71\)\([7.32;8.10]\) & \(7.58\)\([7.20;7.97]\) & \(7.59\)\([7.13;8.05]\) & \(0.90\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Results of measurements performed in parallel on 4 separate fingers on 25 healthy individuals. For each individual, 2 consecutive 4-finger measurements were taken, and the average of the 2 was used for further calculations. The results of the 25 subjects were averaged for each finger separately and are presented in the table with bracketed confidence intervals (CIs). Intraclass coefficients (ICC) were calculated to assess the correlation of results within the same individuals. curves.