Multifractal analysis of the day and night characteristics of heart rate variability

Ramchurn, S.K.; Murray, Alan

doi:10.1109/cic.2002.1166799

Cited by 6 publications

(7 citation statements)

References 7 publications

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“…However, employing multifractal technique in healthy individuals, inconsistent findings regarding the changes in circadian rhythm were reported. While Ivanov et al and Makowiec et al have shown that nighttime possesses stronger multifractal organization and stronger anti-correlation as compared to daytime, Ramchurn suggested, that nighttime is less anti-correlated but that it has the same complexity as daytime [7,18,22]. Over recent years several authors have reported on diminished circadian pattern in different cardiac pathologies [1,4,19].…”

Section: Discussionmentioning

confidence: 95%

“…Using multifractal HRV analysis, the majority of authors have implied, that in healthy individuals a higher degree of complexity and stronger anti-correlation with vagal predominance exist during the night (nighttime period), whereas a lesser degree of complexity and a weaker anti-correlation behavior with sympathetic domination occurs during the day (daytime period) [6,16,17,20]. Whether invasive medical or surgical procedures can affect the circadian patterns as assessed my multifractal approach and thus subjecting patients to additional risk by enhancing neurohumoral instability with additionally pronounced transitions between more and less anti-correlated states, remains unveiled [18,21,22].…”

Section: Introductionmentioning

confidence: 97%

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Multifractality in heartbeat dynamics in patients undergoing beating-heart myocardial revascularization

Kšela

Avbelj

Kališnik

2015

Computers in Biology and Medicine

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Section: Discussionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 97%

Multifractality in heartbeat dynamics in patients undergoing beating-heart myocardial revascularization

Kšela

Avbelj

Kališnik

2015

Computers in Biology and Medicine

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“…Multifractal studies have been undertaken in other domains such as DNA sequences [18], turbulence [5], day and night heart rate characteristics [17], alterations with disease and aging [7]. In this study, we have confined our scope to extract only the multifractality present in the pulse waveforms.…”

Section: Discussion and Final Remarksmentioning

confidence: 99%

Multifractality in arterial pulse

Joshi

Chandran

Jayaraman

et al. 2008

2008 19th International Conference on Pattern Recognition

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Extensive research has been done to show that heartbeats are composed of the interaction of many physiological components operating on different time scales, with nonlinear and self-regulating nature. The more direct, and easily accessible manifestation of the heartbeat is the pulse; however, it has not been studied anywhere near as extensively.In this paper, we establish the relevance of the multifractal formalism for the arterial pulse, which has long been used as a fundamental tool for diagnosis in the Traditional Indian Medicine, (Ayurveda). The finding of power-law correlations through detrended fluctuation analysis indicates presence of scale-invariant, fractal structures in the pulse. These fractal structures are then further established by self-affine cascades of beat-tobeat fluctuations revealed by wavelet decomposition at different time scales. Finally, we investigate how these pulse dynamics change with age, and disorder. The analytic tools we discuss may be used on a wide range of physiological signals.

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“…Heart rate analysis has been used in many clinical studies, including for diabetes [1], heart transplant [2,3], Alzheimer's disease and vascular dementia [4], and sleep [5], as well as for studies of multifractal characteristics [6], variation over 24 hours [7], during sleep [8,9] and Zen meditation [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Effects of Meditation on Heart Rate Stability

Hoshiyama

Murray

2018

2018 Computing in Cardiology Conference (CinC)

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Relaxation or meditation is expected to slow the heart rate and produce more stable rate changes. However, there is little information on specific effects of meditation training. In this study we compared heart rate stability during normal and meditation conditions. ECGs were recorded with ethical permission from normal subjects while seated, over 30-minute periods. The first set of control recordings were made with no instruction other than to remain still without talking. The subjects were then given instruction on relaxation and meditation techniques before a second similar 30-minute study period. These two recordings were made on separate days. Twelve subjects were enroled with a mean age of 36 years. Subjects of these ages were more likely to experience heart rate changes than older subjects The mean RR interval across all subjects during the first control recordings was 837±150 ms (mean±SD) and during relaxation and meditation 846±136, with no significant difference. In spite of no difference in mean RR interval, the RR variability (average subject SD) during meditation actually increased from 53±18 ms to 65±24 ms (p<0.05). In addition, it can be noted that when examining the beat-to-beat changes, the SD of beat-to-beat RR interval changes was less than that for the original RR distribution for both the control recordings and meditation recordings (both p<0.001). This effect was more pronounced during meditation. The expected effect of lower heart rates and lower heart rate variability during meditation did not occur, probably due to the slower and deeper breathing during meditation inducing greater changes.

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Multifractal analysis of the day and night characteristics of heart rate variability

Cited by 6 publications

References 7 publications

Multifractality in heartbeat dynamics in patients undergoing beating-heart myocardial revascularization

Multifractality in heartbeat dynamics in patients undergoing beating-heart myocardial revascularization

Multifractality in arterial pulse

Effects of Meditation on Heart Rate Stability

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