CardioCurveR: Nonlinear Modeling of R-R Interval Dynamics

Automated and robust framework for analyzing R-R interval (RRi) signals using advanced nonlinear modeling and preprocessing techniques. The package implements a dual-logistic model to capture the rapid drop and subsequent recovery of RRi during exercise, as described by Castillo-Aguilar et al. (2025) <doi:10.1038/s41598-025-93654-6>. In addition, 'CardioCurveR' includes tools for filtering RRi signals using zero-phase Butterworth low-pass filtering and for cleaning ectopic beats via adaptive outlier replacement using local regression and robust statistics. These integrated methods preserve the dynamic features of RRi signals and facilitate accurate cardiovascular monitoring and clinical research.

Package details

AuthorMatías Castillo-Aguilar [aut, cre, cph] (<https://orcid.org/0000-0001-7291-247X>)
MaintainerMatías Castillo-Aguilar <m99castillo@gmail.com>
LicenseMIT + file LICENSE
Version1.0.0
URL https://github.com/matcasti/CardioCurveR https://matcasti.github.io/CardioCurveR/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("CardioCurveR")

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CardioCurveR documentation built on April 11, 2025, 5:50 p.m.