Circadian and ultradian rhythms in heart rate variability
Aim: Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian...
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Published in | Biomedizinische Technik Vol. 51; no. 4; pp. 155 - 158 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Germany
Walter de Gruyter
01.10.2006
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Subjects | |
Online Access | Get full text |
ISSN | 0013-5585 1862-278X |
DOI | 10.1515/BMT.2006.026 |
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Abstract | Aim: Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV. Materials and methods: HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58±10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency. Results: Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons. Conclusion: Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology. |
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AbstractList | Aim: Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV. Materials and methods: HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58±10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency. Results: Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons. Conclusion: Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology. Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV.AIMHeart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV.HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58+/-10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency.MATERIALS AND METHODSHR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58+/-10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency.Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons.RESULTSUltradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons.Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology.CONCLUSIONEach HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology. Aim: Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV.Materials and methods: HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58A-10ANByears (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency.Results: Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons.Conclusion: Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology. Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV. HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58+/-10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency. Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons. Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology. |
Author | Duntley, Stephen P. Domitrovich, Peter P. Stein, Phyllis K. Freedland, Kenneth E. Carney, Robert M. Lundequam, Eric J. |
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Cites_doi | 10.1146/annurev.med.50.1.249 10.1016/0013-4694(92)90009-7 |
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SubjectTerms | Age Factors Arrhythmias, Cardiac - physiopathology Biological Clocks Circadian Rhythm Computer Simulation Electrocardiography - methods Female Heart Conduction System - physiopathology Heart Rate heart rate variability Humans Male Middle Aged Models, Cardiovascular Oscillometry - methods Sex Factors Sleep Apnea Syndromes - physiopathology ultradian rhythms |
Title | Circadian and ultradian rhythms in heart rate variability |
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