sim_RRi {CardioCurveR} | R Documentation |
Simulated RR Interval (RRi) Data with Ectopic Beats
Description
A data frame containing a simulated RR interval (RRi) signal generated using the dual-logistic model as described by Castillo-Aguilar et al. (2025). The data are produced by first computing a theoretical RRi curve based on specified model parameters, then adding Gaussian noise to mimic natural variability, and finally introducing ectopic beats by modifying 5% of the data points (multiplying by a factor of 0.3 or 1.7). This simulated dataset is intended for demonstrating and testing the preprocessing and modeling functions provided in the CardioCurveR package.
Usage
sim_RRi
Format
A data frame with n
rows and 2 variables:
- time
A numeric vector of time points (in seconds).
- RRi_simulated
A numeric vector of simulated RR interval values (in milliseconds), including added noise and simulated ectopic beats.
Details
The dual-logistic model is defined as:
RRi(t) = \alpha + \frac{\beta}{1 + \exp\{\lambda (t - \tau)\}} + \frac{-c \cdot \beta}{1 + \exp\{\phi (t - \tau - \delta)\}},
where \alpha
is the baseline RRi level, \beta
controls the amplitude of the drop,
\lambda
and \tau
define the drop phase, and c
, \phi
, and \delta
govern the recovery.
Source
Simulated data generated using the dual-logistic model and random noise.
References
Castillo-Aguilar, et al. (2025). Enhancing Cardiovascular Monitoring: A Non-linear Model for Characterizing RR Interval Fluctuations in Exercise and Recovery. Scientific Reports, 15(1), 8628.
Examples
data(sim_RRi)
head(sim_RRi)
# Plot tha data
library(ggplot2)
ggplot(sim_RRi, aes(time, RRi_simulated)) +
geom_line(linewidth = 1/4, col = "purple") +
labs(x = "Time (s)", y = "RRi (ms)",
title = "Simulated RRi Signal with Ectopic Beats") +
theme_minimal()