Enhancing Scaling Exponents in Heart Rate by means of Fractional Integration

dc.contributor.author Argentina Leite en
dc.contributor.author Rocha,AP en
dc.contributor.author Silva,ME en
dc.date.accessioned 2018-01-16T17:07:18Z
dc.date.available 2018-01-16T17:07:18Z
dc.date.issued 2013 en
dc.description.abstract The characterization of heart rate variability (HRV) series has become important for clinical diagnosis. These series are non-stationary and exhibit long and short-range correlations. The non-parametric methodology detrended fluctuation analysis (DFA) has become widely used for the detection of these correlations. The standard procedure is to apply DFA to the RR series, estimating the desired scaling exponents. In this work we pursue an alternative approach which consists in applying DFA to the fractionally differenced RR series, Delta(RR)-R-d, where 0 < d < 1 is the long-range correlation parameter. Both methodologies are applied to 24 hour HRV series from the Noltisalis data base. We conclude that changes in HRV are better quantified by DFA scaling exponents calculated over fractionally differenced RR series than by the standard procedure. The results indicate that the scaling exponent corresponding to high frequencies obtained from Delta(RR)-R-d increases the discriminatory power among the groups: from 60% to 87% during the day period and 57% to 77% during the night period. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/6485
dc.language eng en
dc.relation 6245 en
dc.rights info:eu-repo/semantics/embargoedAccess en
dc.title Enhancing Scaling Exponents in Heart Rate by means of Fractional Integration en
dc.type conferenceObject en
dc.type Publication en
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