Multiscale analysis of heart rate variability in nonstationary environments
Heart rate variability (HRV) is highly nonstationary, even if no perturbing influences can be identified during the recording of the data. The nonstationarity becomes more profound when HRV data are measured in intrinsically nonstationary environments, such as social stress. In general, HRV data me...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2013-05-01
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| Series: | Frontiers in Physiology |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fphys.2013.00119/full |
| _version_ | 1818986370685730816 |
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| author | Jianbo eGao Jianbo eGao Brian M. Gurbaxani Jing eHu Keri J. Heilman Vincent A. Emauele Gregory F. Lewis Gregory F. Lewis Maria eDavila Elizabeth R. Unger Jin-Mann S. Lin |
| author_facet | Jianbo eGao Jianbo eGao Brian M. Gurbaxani Jing eHu Keri J. Heilman Vincent A. Emauele Gregory F. Lewis Gregory F. Lewis Maria eDavila Elizabeth R. Unger Jin-Mann S. Lin |
| author_sort | Jianbo eGao |
| collection | DOAJ |
| description | Heart rate variability (HRV) is highly nonstationary, even if no perturbing influences can be identified during the recording of the data. The nonstationarity becomes more profound when HRV data are measured in intrinsically nonstationary environments, such as social stress. In general, HRV data measured in such situations are more difficult to analyze than those measured in constant environments. In this paper, we analyze HRV data measured during a social stress test using two multiscale approaches, the adaptive fractal analysis (AFA) and scale-dependent Lyapunov exponent (SDLE), for the purpose of uncovering differences in HRV between chronic fatigue syndrome (CFS) patients and their matched-controls. CFS is a debilitating, heterogeneous illness with no known biomarker. HRV has shown some promise recently as a non-invasive measure of subtle physiological disturbances and trauma that are otherwise difficult to assess. If the HRV in persons with CFS are significantly different from their healthy controls, then certain cardiac irregularities may constitute good candidate biomarkers for CFS. Our multiscale analyses show that there are notable differences in HRV between CFS and their matched controls before a social stress test, but these differences seem to diminish during the test. These analyses illustrate that the two employed multiscale approaches could be useful for the analysis of HRV measured in various environments, both stationary and nonstationary. |
| first_indexed | 2024-12-20T18:49:43Z |
| format | Article |
| id | doaj.art-520c5917b495497fb99f3af70c6f498d |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-12-20T18:49:43Z |
| publishDate | 2013-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-520c5917b495497fb99f3af70c6f498d2022-12-21T19:29:37ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2013-05-01410.3389/fphys.2013.0011943695Multiscale analysis of heart rate variability in nonstationary environmentsJianbo eGao0Jianbo eGao1Brian M. Gurbaxani2Jing eHu3Keri J. Heilman4Vincent A. Emauele5Gregory F. Lewis6Gregory F. Lewis7Maria eDavila8Elizabeth R. Unger9Jin-Mann S. Lin10PMB Intelligence LLCWright State UniversityCenters for Disease Control and PreventionPMB Intelligence LLCUniversity of IllinoisCenters for Disease Control and PreventionUniversity of IllinoisResearch Triangle InstituteUniversity of IllinoisCenters for Disease Control and PreventionCenters for Disease Control and PreventionHeart rate variability (HRV) is highly nonstationary, even if no perturbing influences can be identified during the recording of the data. The nonstationarity becomes more profound when HRV data are measured in intrinsically nonstationary environments, such as social stress. In general, HRV data measured in such situations are more difficult to analyze than those measured in constant environments. In this paper, we analyze HRV data measured during a social stress test using two multiscale approaches, the adaptive fractal analysis (AFA) and scale-dependent Lyapunov exponent (SDLE), for the purpose of uncovering differences in HRV between chronic fatigue syndrome (CFS) patients and their matched-controls. CFS is a debilitating, heterogeneous illness with no known biomarker. HRV has shown some promise recently as a non-invasive measure of subtle physiological disturbances and trauma that are otherwise difficult to assess. If the HRV in persons with CFS are significantly different from their healthy controls, then certain cardiac irregularities may constitute good candidate biomarkers for CFS. Our multiscale analyses show that there are notable differences in HRV between CFS and their matched controls before a social stress test, but these differences seem to diminish during the test. These analyses illustrate that the two employed multiscale approaches could be useful for the analysis of HRV measured in various environments, both stationary and nonstationary.http://journal.frontiersin.org/Journal/10.3389/fphys.2013.00119/fullHeart rate variabilityfractalChaoschronic fatigue syndromescale-dependent Lyapunov exponentadaptive fractal analysis |
| spellingShingle | Jianbo eGao Jianbo eGao Brian M. Gurbaxani Jing eHu Keri J. Heilman Vincent A. Emauele Gregory F. Lewis Gregory F. Lewis Maria eDavila Elizabeth R. Unger Jin-Mann S. Lin Multiscale analysis of heart rate variability in nonstationary environments Frontiers in Physiology Heart rate variability fractal Chaos chronic fatigue syndrome scale-dependent Lyapunov exponent adaptive fractal analysis |
| title | Multiscale analysis of heart rate variability in nonstationary environments |
| title_full | Multiscale analysis of heart rate variability in nonstationary environments |
| title_fullStr | Multiscale analysis of heart rate variability in nonstationary environments |
| title_full_unstemmed | Multiscale analysis of heart rate variability in nonstationary environments |
| title_short | Multiscale analysis of heart rate variability in nonstationary environments |
| title_sort | multiscale analysis of heart rate variability in nonstationary environments |
| topic | Heart rate variability fractal Chaos chronic fatigue syndrome scale-dependent Lyapunov exponent adaptive fractal analysis |
| url | http://journal.frontiersin.org/Journal/10.3389/fphys.2013.00119/full |
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