Abstract
Most methods used to analyze experimental data are based on the assumption that the data is from a Gaussian distribution and uncorrected. We describe methods to analyze data from scaling phenomena that do not have a Gaussian distribution [8.1–8.3] or involve long-range correlations [8.4–8.6]. We then show how those scaling methods have proved useful in characterizing the heart rate data from people who are healthy, from people who have a specific sleep disorder, and from people who have irregular heart rhythms.
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Liebovitch, L.S., Penzel, T., Kantelhardt, J.W. (2002). Physiological Relevance of Scaling of Heart Phenomena. In: The Science of Disasters. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-56257-0_8
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DOI: https://doi.org/10.1007/978-3-642-56257-0_8
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