Recently there has been great interest in photoplethysmogram signal processing. However, its minimally necessary sampling frequency for accurate heart rate variability parameters is ambiguous. In the present paper frequency-modulated 1.067 Hz cosine wave modelled the variable PPG in silico. The five-minute-long, 1 ms resolution master-signals were decimated (D) at 2-500 ms, then cubic spline interpolated (I) back to 1 ms resolution. The mean pulse rate, standard deviation, root mean square of successive pulse rate differences (RMSSD), and spectral components were computed by Varian 2.3 and compared to the master-series via relative accuracy error. Also Poincaré-plot morphology was assessed. Mean pulse rate is accurate down to 303 ms (D) and 400 ms (I). In low-variability series standard deviation required at least 5 ms (D) and 100 ms (I). RMSSD needed 10 ms (D), and 303 ms (I) in normal, whereas 2 ms (D) and 100 ms (I) in low- variability series. In the frequency domain 5 ms (D) and 100 ms (I) are required. 2 ms (D) and 100 ms (I) preserved the Poincaré-plot morphology. The minimal sampling frequency of PPG for accurate HRV analysis is higher than expected from the signal bandwidth and sampling theorem. Interpolation improves accuracy. The ratio of sampling error and expected variability should be considered besides the inherent sensitivity of the given parameter, the interpolation technique, and the pulse rate detection method.

Background: Mobile phones may have harmful health effects and clinical examinations report ambiguous results of exposure concerning neurophysiological and cardiovascular actions. Materials and Methods: This study investigated heart rate asymmetry (HRA) and heart rate variability (HRV) parameters with 1:2 and 1:1 metronome-paced inspiration/expiration ratios during short-term 1,800MHz GSM cellular phone exposure in 20 healthy volunteers. Results: Significant HRA changes by Porta and Guzik indices were not found on exposure compared to sham exposure. Time-domain HRV parameters on exposure showed significant differences at 1:1 paced, but not at 1:2 paced breathing compared to sham exposure. A mild post-exposure effect was observed regarding root mean square of successive RR-differences. Conclusion: The findings reflect persisting acute effects of GSM handset emission on the autonomic nervous system. Exploring its influences on health status and survival needs further studies. Symmetrical breathing can be used as a sensitizing factor in other HRV/HRA analysis studies.

Background: The aim of this study was to investigate the effects of carbon-dioxide treatment on heart rate variability (HRV) parameters: mean RR interval (RRI), standard deviation of RR intervals (SDNN), root mean square of successive RR differences (RMSSD); and Porta and Guzik indices, as measures of heart rate asymmetry. Materials and Methods: Twenty patients were enrolled (mean±SD, age=59±7.8 years). Measurements were performed before CO₂ treatment, at the beginning of treatment, at 15 min of treatment, immediately after and 1 h after the treatment. Results: Significant increase in SDNN was found 1 h after the treatment when compared to that before it (p=0.011). There were no significant changes in other parameters. Conclusion: CO₂ treatment can influence the autonomic nervous system identified by SDNN changes. However, larger studies are required to confirm these results.

Accurate pulse rate detection is essential for reliable pulse rate variability analysis. On the other hand, minimizing the sampling frequency is essential to reduce the amount of data and computational needs, and consequently the power consumption of mobile/wearable devices, extending their operating hours. Determining the variability of physiological parameters needs a new paradigm since there is a limited possibility of calculating an average eliminating random error of measurement. Finding the optimal sampling rate depends on the actual investigation, the expected variability and variability-changes of the study-population in order to get valid HRV parameters.

Precise beat-to-beat fiducial point detection in the photoplethysmogram signal is essential for reliable pulse rate variability (PRV) analysis, which is considered an integral part of health monitoring devices in the evolving era of mobile health. Several studies have aimed to compare PRV to the well-investigated, gold standard heart rate variability (HRV) analysis, to see if they are interchangeable. The agreement between PRV and HRV is not unequivocal, as we learn from the commented metaanalysis. Technical factors like low sampling rate of photoplethysmography (PPG) or imprecise fiducial point detection are more important in this difference than physiological factors corresponding to pulse arrival time. Standardization of the PPG acquisition and reference point detection is necessary for comparable studies and correct measurement.