Alterations of heart rate variability (HRV) are associated with various (patho)physiological conditions; therefore, HRV analysis has the potential to become a useful diagnostic module of wearable/telemedical devices to support remote cardiovascular/autonomic monitoring. Continuous pulse recordings obtained by photoplethysmography (PPG) can yield pulse rate variability (PRV) indices similar to HRV parameters; however, it is debated whether PRV/HRV parameters are interchangeable. In this study, we assessed the PRV analysis module of a digital arterial PPG-based telemedical system (SCN4ALL). We used Bland–Altman analysis to validate the SCN4ALL PRV algorithm to Kubios Premium software and to determine the agreements between PRV/HRV results calculated from 2-min long PPG and ECG captures recorded simultaneously in healthy individuals (n = 33) at rest and during the cold pressor test, and in diabetic patients (n = 12) at rest. We found an ideal agreement between SCN4ALL and Kubios outputs (bias < 2%). PRV and HRV parameters showed good agreements for interbeat intervals, SDNN, and RMSSD time-domain variables, for total spectral and low-frequency power (LF) frequency-domain variables, and for non-linear parameters in healthy subjects at rest and during cold pressor challenge. In diabetics, good agreements were observed for SDNN, LF, and SD2; and moderate agreement was observed for total power. In conclusion, the SCN4ALL PRV analysis module is a good alternative for HRV analysis for numerous conventional HRV parameters.

Telemonitoring systems equipped with photoplethysmography-based contour analysis of the digital arterial volume pulse (DVP) can be optimal tools for remote monitoring of cardiovascular patients; however, the method is known to be sensitive to errors. We aimed to show that DVP analysis is a reliable method to track cardiovascular status. We used our proprietary SCN4ALL telemedicine system and analyzed nine parameters derived from the DVP and its second derivative (SDDVP). First, we assessed the repeatability of system measurements by detecting artificial signals. Then test–retest reliability of human measurements was evaluated in healthy individuals under standardized conditions. The SCN4ALL system analyzed each parameter with high accuracy (coefficients of variation (CVs) < 1%). Test–retest reliability of most parameters (stiffness index, reflection index, left ventricular ejection time index, b/a, heart rate) was satisfactory (CVs < 10%) in healthy individuals. However, aging index and d/a ratio derived from the SDDVP were more variable. Photoplethysmography-based pulse contour analysis is a reliable method to monitor cardiovascular status if measurements are performed with a system of high accuracy. Our results highlighted that SDDVP parameters can be interpreted with limitations due to (patho)physiological variations of the DVP. We recommend the evaluation of these parameters only in measurements where all inflections of SDDVP are detected reliably.

Background Introduction of telemonitoring systems to patient care which provide extensive information about the cardiovascular status of the patient is a promising direction to reduce cardiovascular morbidity and mortality. Our team has developed a telemedical system which is based on the photoplethysmographic detection of the digital arterial pulse wave. The system incorporates a cloud-based automated algorithm which analyses the pulse contour to provide 15 scientifically established parameters for versatile characterization of cardiovascular function. The aim of the current study was to assess the variability of the measurements to test the applicability of the tool before clinical use. We assessed the repeatability of the measurements by detecting stable artificial signals, and also test-retest variability by repeatedly examining the pulse contours of healthy individuals under standardized conditions. Results Most contour parameters (stiffness index, reflection index, left ventricular ejection time index and mean interbeat intervals) are measured with high repeatability (coefficients of variation (CV) < 1% for each parameter), and exhibit acceptable intrapersonal fluctuations (CVs < 10%). However, some parameters derived from the second derivative of the pulse wave seem to be more variable (aging index, d/a ratio). This is explained by the typical alterations of the pulse wave under specific circumstances, which cause the flattening or complete disappearance of c and d inflections on the second derivative. Conclusion Our measurements proved that our telemonitoring system detects and analyses digital pulse contours with high accuracy and highlighted that second derivative parameters should be interpreted cautiously. We recommend the evaluation of these parameters only in those measurements where c and d points are detected reliably. Pulse contour parameters are stable in healthy individuals under standardized conditions, which allows detection of subtle abnormal alterations by the remote surveillance system.