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CardiacDP: Automated Cardiac Data Processing via ACF, GA & Tracking Index
An algorithm developed to efficiently and accurately process complex and variable cardiac data with three key features: 1. employing autocorrelation to identify recurrent heartbeats and use their periods to compute heart rates; 2. incorporating a genetic algorithm framework to minimize data loss due to noise interference and accommodate within-sequence variations; and 3. introducing a tracking index as a moving reference to reduce errors. Lau, Wong, & Gu (2026) <https://ssrn.com/abstract=5153081>.
| Version: |
0.4.2 |
| Depends: |
R (≥ 4.3.0) |
| Imports: |
data.table, doParallel, dplyr, foreach, ggplot2, purrr, RColorBrewer, stringr |
| Suggests: |
testthat (≥ 3.0.0) |
| Published: |
2026-02-12 |
| DOI: |
10.32614/CRAN.package.CardiacDP |
| Author: |
Sarah Lau  [aut,
ctb],
Adrian Wong [aut, ctb],
Yi-Fei Gu [aut,
cre] |
| Maintainer: |
Yi-Fei Gu <guyf0601 at connect.hku.hk> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
CardiacDP results |
Documentation:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.