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 |
| DOI: | 10.32614/CRAN.package.heartbeatr |
| Author: | Rui Seabra [aut, cre], Fernando Lima [aut] |
| Maintainer: | Rui Seabra <ruisea at gmail.com> |
| License: | MIT + fileLICENSE |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | heartbeatr results |
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