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Publikationstyp: Beitrag in wissenschaftlicher Zeitschrift
Art der Begutachtung: Peer review (Publikation)
Titel: Filtering heart rates using data densities : the boxfilter R package
Autor/-in: Ruf, Thomas
Signer, Claudio
Arnold, Walter
Vetter, Sebastian G.
Bieber, Claudia
et. al: No
DOI: 10.1111/2041-210X.14301
10.21256/zhaw-30568
Erschienen in: Methods in Ecology and Evolution
Band(Heft): 15
Heft: 6
Seite(n): 1016
Seiten bis: 1023
Erscheinungsdatum: 2024
Verlag / Hrsg. Institution: Wiley
ISSN: 2041-210X
Sprache: Englisch
Schlagwörter: Extreme value; Filter; Heart rate; Outliers; R-package; Physiological variable; Measurement; Noise; Human; Animal
Fachgebiet (DDC): 005: Computerprogrammierung, Programme und Daten
571: Physiologie und verwandte Themen
Zusammenfassung: 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
Volltext Version: Publizierte Version
Lizenz (gemäss Verlagsvertrag): CC BY 4.0: Namensnennung 4.0 International
Departement: Life Sciences und Facility Management
Organisationseinheit: Institut für Umwelt und Natürliche Ressourcen (IUNR)
Enthalten in den Sammlungen:Publikationen Life Sciences und Facility Management

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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.


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