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.

Version:	1.0.0
Depends:	R (≥ 3.5)
Imports:	signal (≥ 1.8.1), ggplot2 (≥ 3.5.1), gridExtra (≥ 2.3), data.table (≥ 1.16.4)
Suggests:	testthat (≥ 3.0.0)
Published:	2025-04-07
DOI:	10.32614/CRAN.package.CardioCurveR
Author:	Matías Castillo-Aguilar [aut, cre, cph]
Maintainer:	Matías Castillo-Aguilar <m99castillo at gmail.com>
BugReports:	https://github.com/matcasti/CardioCurveR/issues
License:	MIT + file LICENSE
URL:	https://github.com/matcasti/CardioCurveR, https://matcasti.github.io/CardioCurveR/
NeedsCompilation:	no
Citation:	CardioCurveR citation info
Materials:	README NEWS
CRAN checks:	CardioCurveR results

Documentation:

Reference manual:

CardioCurveR.pdf

Downloads:

Package source:	CardioCurveR_1.0.0.tar.gz
Windows binaries:	r-devel: CardioCurveR_1.0.0.zip, r-release: CardioCurveR_1.0.0.zip, r-oldrel: CardioCurveR_1.0.0.zip
macOS binaries:	r-devel (arm64): CardioCurveR_1.0.0.tgz, r-release (arm64): CardioCurveR_1.0.0.tgz, r-oldrel (arm64): CardioCurveR_1.0.0.tgz, r-devel (x86_64): CardioCurveR_1.0.0.tgz, r-release (x86_64): CardioCurveR_1.0.0.tgz, r-oldrel (x86_64): CardioCurveR_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=CardioCurveR to link to this page.