A Workflow to Process Data Collected with PULSE Systems R package heartbeatr version 1.0.0 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>). Software 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) Rui Seabra <ruisea@gmail.com> Comprehensive R Archive Network (CRAN) Rui Seabra [aut, cre] (ORCID: <https://orcid.org/0000-0002-0240-3992>), Fernando Lima [aut] (ORCID: <https://orcid.org/0000-0001-9575-9834>) MIT + file LICENSE (https://CRAN.R-project.org/package=heartbeatr/LICENSE) 2025-09-18 application/tgz https://CRAN.R-project.org/package=heartbeatr doi:10.32614/CRAN.package.heartbeatr