Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-30568
Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Filtering heart rates using data densities : the boxfilter R package
Authors: Ruf, Thomas
Signer, Claudio
Arnold, Walter
Vetter, Sebastian G.
Bieber, Claudia
et. al: No
DOI: 10.1111/2041-210X.14301
10.21256/zhaw-30568
Published in: Methods in Ecology and Evolution
Volume(Issue): 15
Issue: 6
Page(s): 1016
Pages to: 1023
Issue Date: 2024
Publisher / Ed. Institution: Wiley
ISSN: 2041-210X
Language: English
Subjects: Extreme value; Filter; Heart rate; Outliers; R-package; Physiological variable; Measurement; Noise; Human; Animal
Subject (DDC): 005: Computer programming, programs and data
571: Physiology and related subjects
Abstract: Over the past decades, there has been a growing interest in long-term heart rate records, especially from free-living animals. Largely, this increase is because most of the metabolic activity of tissues is based on oxygen delivery by the heart. Therefore, heart rate has served as a proxy for energy expenditure in animals. However, heart rates or other physiological variables recorded in humans and animals using loggers often contain noise. False measurements are sometimes eliminated by hand or by filters that reject variables based on the shape or frequency of the signal. Occasionally, outliers are rejected because they occur a long distance from genuine data. We introduce an R package, boxfilter, which enables users to eliminate noise based on counting the number of close neighbours inside a gliding window. Depending on the cut-off value chosen, a focal point with a low proportion of neighbours will be rejected as noise. All three parameters, namely window width and height, as well as the cut-off value, can be computed automatically. The choice of the clip-off value beyond which data points are discarded is crucial. The package boxfilter cannot, of course, solve problems caused by completely erroneous measurements. Like the human eye, this filter prefers points that are part of a pattern, such as a dense band, and rejects isolated values. The boxfilter may also be applied to other measures than heart rate that do not change instantaneously, such as body temperature, blood pressure or sleep parameters.
URI: https://digitalcollection.zhaw.ch/handle/11475/30568
Fulltext version: Published version
License (according to publishing contract): CC BY 4.0: Attribution 4.0 International
Departement: Life Sciences and Facility Management
Organisational Unit: Institute of Natural Resource Sciences (IUNR)
Appears in collections:Publikationen Life Sciences und Facility Management

Files in This Item:
File Description SizeFormat 
2024_Ruf-etal_Filtering-heart-rates-data-densities-boxfilter-R_mee.pdf3.16 MBAdobe PDFThumbnail
View/Open
Show full item record
Ruf, T., Signer, C., Arnold, W., Vetter, S. G., & Bieber, C. (2024). Filtering heart rates using data densities : the boxfilter R package. Methods in Ecology and Evolution, 15(6), 1016–1023. https://doi.org/10.1111/2041-210X.14301
Ruf, T. et al. (2024) ‘Filtering heart rates using data densities : the boxfilter R package’, Methods in Ecology and Evolution, 15(6), pp. 1016–1023. Available at: https://doi.org/10.1111/2041-210X.14301.
T. Ruf, C. Signer, W. Arnold, S. G. Vetter, and C. Bieber, “Filtering heart rates using data densities : the boxfilter R package,” Methods in Ecology and Evolution, vol. 15, no. 6, pp. 1016–1023, 2024, doi: 10.1111/2041-210X.14301.
RUF, Thomas, Claudio SIGNER, Walter ARNOLD, Sebastian G. VETTER und Claudia BIEBER, 2024. Filtering heart rates using data densities : the boxfilter R package. Methods in Ecology and Evolution. 2024. Bd. 15, Nr. 6, S. 1016–1023. DOI 10.1111/2041-210X.14301
Ruf, Thomas, Claudio Signer, Walter Arnold, Sebastian G. Vetter, and Claudia Bieber. 2024. “Filtering Heart Rates Using Data Densities : The Boxfilter R Package.” Methods in Ecology and Evolution 15 (6): 1016–23. https://doi.org/10.1111/2041-210X.14301.
Ruf, Thomas, et al. “Filtering Heart Rates Using Data Densities : The Boxfilter R Package.” Methods in Ecology and Evolution, vol. 15, no. 6, 2024, pp. 1016–23, https://doi.org/10.1111/2041-210X.14301.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.