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heartbeatr: A Workflow to Process Data Collected with PULSE Systems
Given one or multiple paths to files produced by a PULSE multi-channel or a PULSE one-channel system (<https://electricblue.eu/pulse>) from a single experiment: [1] check pulse files for inconsistencies and read/merge all data, [2] split across time windows, [3] interpolate and smooth to optimize the dataset, [4] compute the heart rate frequency for each channel/window, and [5] facilitate quality control, summarising and plotting.
Heart rate frequency is calculated using the Automatic Multi-scale Peak Detection algorithm proposed by Felix Scholkmann and team. For more details see Scholkmann et al (2012) <doi:10.3390/a5040588>. Check original code at <https://github.com/ig248/pyampd>.
ElectricBlue is a non-profit technology transfer startup creating research-oriented solutions for the scientific community (<https://electricblue.eu>).
| Version: |
1.0.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
av, cli, dplyr, ggplot2, lubridate, magrittr, purrr, readr, stringr, tibble, tidyr, transformr |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2025-09-18 |
| Author: |
Rui Seabra  [aut,
cre],
Fernando Lima
[aut] |
| Maintainer: |
Rui Seabra <ruisea at gmail.com> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
heartbeatr 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.