Agreement analysis of heart rate variability indices at two different sampling rates for monitoring applications.

Beat-to-beat variations in heart rate lead to heart rate variability (HRV), analysed from electrocardiogram or photoplethysmography signals, forming a non-equispaced time series of beats, which requires a resampling of 3 Hz or 4 Hz, for analysis in the frequency domain. HRV is considered a biomarker, predictor of the evolution of diseases in intensive care units (ICU). To enhance these HRV studies, it is necessary to monitor the patients health using portable devices, from admission to the ICU until discharge from it and subsequently at home. This requires monitoring devices that can minimise energy consumption and data storage. Reducing the sampling frequency in HRV can reduce energy consumption, computing power and to limite data storage. Therefore, the objective of this work is to prove that a series resampled at 1 Hz allows obtaining HRV indices, equivalent to a 3 Hz. Through concordance analysis, using a database of subjects with pharmacological autonomic blockade and postural changes. The results show equivalences between the indices, standard deviation (SDNN), total spectral power (PT), low frequency (LF) and long-term variability (SD2) and agree with those reported as predictors. This study has limitations, since only a small number of young men participated. Future studies should consider this. The reduction of SDNN, PT, LF values would be predictors of mortality in hospitals, so the equivalence found from series with 1Hz resampling, would allow the use of portable devices with optimized performance, to monitor the evolution of the disease in patients in ICUs.