dorsal/arxiv
View SchemaInterpretation of heart rate variability via detrended fluctuation analysis and alpha-beta filter
| Authors | J. C. Echeverria, M. S. Woolfson, J. A. Crowe, B. R. Hayes-Gill, G. D. H. Croaker, H. Vyas |
|---|---|
| Categories | |
| ArXiv ID | physics/0306181 |
| URL | https://arxiv.org/abs/physics/0306181 |
| DOI | 10.1063/1.1562051 |
| Journal | Chaos 13 (2003) 467-475 |
Abstract
Detrended fluctuation analysis (DFA), suitable for the analysis of nonstationary time series, has confirmed the existence of persistent long-range correlations in healthy heart rate variability data. In this paper, we present the incorporation of the alpha-beta filter to DFA to determine patterns in the power-law behaviour that can be found in these correlations. Well-known simulated scenarios and real data involving normal and pathological circumstances were used to evaluate this process. The results presented here suggest the existence of evolving patterns, not always following a uniform power-law behaviour, that cannot be described by scaling exponents estimated using a linear procedure over two predefined ranges. Instead, the power law is observed to have a continuous variation with segment length. We also show that the study of these patterns, avoiding initial assumptions about the nature of the data, may confer advantages to DFA by revealing more clearly abnormal physiological conditions detected in congestive heart failure patients related to the existence of dominant characteristic scales.
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"abstract": "Detrended fluctuation analysis (DFA), suitable for the analysis of\nnonstationary time series, has confirmed the existence of persistent long-range\ncorrelations in healthy heart rate variability data. In this paper, we present\nthe incorporation of the alpha-beta filter to DFA to determine patterns in the\npower-law behaviour that can be found in these correlations. Well-known\nsimulated scenarios and real data involving normal and pathological\ncircumstances were used to evaluate this process. The results presented here\nsuggest the existence of evolving patterns, not always following a uniform\npower-law behaviour, that cannot be described by scaling exponents estimated\nusing a linear procedure over two predefined ranges. Instead, the power law is\nobserved to have a continuous variation with segment length. We also show that\nthe study of these patterns, avoiding initial assumptions about the nature of\nthe data, may confer advantages to DFA by revealing more clearly abnormal\nphysiological conditions detected in congestive heart failure patients related\nto the existence of dominant characteristic scales.",
"arxiv_id": "physics/0306181",
"authors": [
"J. C. Echeverria",
"M. S. Woolfson",
"J. A. Crowe",
"B. R. Hayes-Gill",
"G. D. H. Croaker",
"H. Vyas"
],
"categories": [
"physics.med-ph",
"physics.data-an",
"q-bio.QM"
],
"doi": "10.1063/1.1562051",
"journal_ref": "Chaos 13 (2003) 467-475",
"title": "Interpretation of heart rate variability via detrended fluctuation analysis and alpha-beta filter",
"url": "https://arxiv.org/abs/physics/0306181"
},
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