BaroWavelet: An R-based tool for dynamic baroreflex evaluation through wavelet analysis techniques

Background and objective: Baroreflex sensitivity constitutes an indicator of the function of the baroreceptor control mechanism of blood pressure levels. It can be computed after estimating heart rate and blood pressure variability. We propose a novel tool for the evaluation of baroreflex sensitivity using wavelet analysis methods. This tool, known as BaroWavelet, incorporates an algorithm proposal based on the analysis methodology of the RHRV software package, as well as other conventional techniques. Our objectives are to develop and evaluate the tool, by testing its ability to detect changes in baroreflex sensitivity in humans.Methods: The code for this tool was designed in the R programming environment and was organized into two analysis routines and a graphical interface. Simulated recordings of blood pressure and inter-beat intervals were employed for an initial evaluation of the tool in a controlled environment. Finally, similar recordings obtained during supine and orthostatic postural evaluations, from patients that belonged to the open-access EUROBAVAR data set, were analyzed.Results: BaroWavelet identified the scripted changes of the baroreflex sensitivity in the simulated data. The al-gorithm proposal was also able to better retain additional information regarding the dynamics of the baroreflex. In the EUROBAVAR subjects, baroreflex sensitivity components were significantly smaller during orthostatism when compared with the supine position.Conclusions: BaroWavelet managed to characterize baroreflex dynamics from the recordings, which were consistent with the findings reported in the literature. This demonstrates its effectiveness to perform these an-alyses. We suggest that this tool may be of use in research and for the evaluation of baroreflex sensitivity with clinical and therapeutic purposes. The new tool is available at the official GitHub repository of the Autonomic Nervous System Unit of the University of M ' alaga (https://github.com/CIMES-USNA-UMA/BaroWavelet).

Automated summary

This study proposes a new tool called BaroWavelet for evaluating baroreflex sensitivity using wavelet analysis methods. The effectiveness of the tool was validated through analysis of simulated data and recordings from actual patients. Results demonstrated that BaroWavelet accurately detected changes in baroreflex sensitivity and provided additional information about baroreflex dynamics.