Repair of Physiologic Time Series: Replacement of Anomalous Data Points to Preserve Fractal Exponents

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Repair of Physiologic Time Series: Replacement of Anomalous Data Points to Preserve Fractal Exponents

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Title: Repair of Physiologic Time Series: Replacement of Anomalous Data Points to Preserve Fractal Exponents
Author: Shelhamer, Mark; Lowen, Steven B.

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Citation: Shelhamer, Mark, and Steven B. Lowen. 2017. “Repair of Physiologic Time Series: Replacement of Anomalous Data Points to Preserve Fractal Exponents.” Frontiers in Bioengineering and Biotechnology 5 (1): 10. doi:10.3389/fbioe.2017.00010. http://dx.doi.org/10.3389/fbioe.2017.00010.
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Abstract: Extraction of fractal exponents via the slope of the power spectrum is common in the analysis of many physiological time series. The fractal structure thus characterized is a manifestation of long-term correlations, for which the temporal order of the sample values is crucial. However, missing data points due to artifacts and dropouts are common in such data sets, which can seriously disrupt the computation of fractal parameters. We evaluated a number of methods for replacing missing data in time series to enable reliable extraction of the fractal exponent and make recommendations as to the preferred replacement method depending on the proportion of missing values and any a priori estimate of the fractal exponent.
Published Version: doi:10.3389/fbioe.2017.00010
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5318392/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:32072067
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