Analysis of lagged Poincaré plots in heart rate signals during meditation

Goshvarpour, Atefeh; Rahati, Saeed

doi:10.1016/j.dsp.2010.06.015

Cited by 47 publications

(41 citation statements)

References 8 publications

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“…Goshvarpour et al [39] examined the influence of different lags on the Poincaré plot indices of heart rate signals in a group of healthy subjects before and during meditation. The Poincaré plot indices were calculated using lags 1 and 6 heartbeats.…”

Section: Discussionmentioning

confidence: 99%

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Informative Nature and Nonlinearity of Lagged Poincaré Plots Indices in Analysis of Heart Rate Variability

Койчубеков

Риклефс

Sorokina

et al. 2017

Entropy

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Lagged Poincaré plots have been successful in characterizing abnormal cardiac function. However, the current research practices do not favour any specific lag of Poincaré plots, thus complicating the comparison of results of different researchers in their analysis of heart rate of healthy subjects and patients. We researched the informative nature of lagged Poincaré plots in different states of the autonomic nervous system. It was tested in three models: different age groups, groups with different balance of autonomous regulation, and in hypertensive patients. Correlation analysis shows that for lag l = 6, SD1/SD2 has weak (r = 0.33) correlation with linear parameters of heart rate variability (HRV). For l more than 6 it displays even less correlation with linear parameters, but the changes in SD1/SD2 become statistically insignificant. Secondly, surrogate data tests show that the real SD1/SD2 is statistically different from its surrogate value and the conclusion could be made that the heart rhythm has nonlinear properties. Thirdly, the three models showed that for different functional states of the autonomic nervous system (ANS), SD1/SD2 ratio varied only for lags l = 5 and 6. All of this allow to us to give cautious recommendation to use SD1/SD2 with lags 5 and 6 as a nonlinear characteristic of HRV. The received data could be used as the basis for continuing the research in standardisation of nonlinear analytic methods.

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Section: Discussionmentioning

confidence: 99%

“…The authors showed that the Poincaré plots built with time lags of four heart beats reflects the changes in HRV after haemodialysis. In other papers, Poincaré plot indices were informative at all lags from 1 to 10 [39,40].…”

Section: Introductionmentioning

confidence: 99%

Informative Nature and Nonlinearity of Lagged Poincaré Plots Indices in Analysis of Heart Rate Variability

Койчубеков

Риклефс

Sorokina

et al. 2017

Entropy

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show abstract

“…Several methods have been proposed: Lyapunov exponents [13], Poincare plots [14], 1/f slope [15], approximate entropy (ApEn) [16] and detrended fluctuation analysis (DFA) [17].…”

Section: Introductionmentioning

confidence: 99%

“…It is now generally recognized that these nonlinear techniques are able to describe the processes generated by biological systems in a more effective way, but a few studies have investigated the nonlinear dynamics of heart rate signals during meditation [14,[18][19].…”

Section: Introductionmentioning

confidence: 99%

Chaotic Behavior of Heart Rate Signals during Chi and Kundalini Meditation

Goshvarpour¹,

Goshvarpour²

2012

IJIGSP

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Abstract-Nonlinear dynamics has been introduced to the analysis of biological data and increasingly recognized to be functionally relevant. The aim of this study is to quantify and compare the contribution of nonlinear and chaotic dynamics of human heart rate variability during two forms of meditation: (i) Chinese Chi (or Qigong) meditation and (ii) Kundalini Yoga meditation. For this purpose, Poincare plots, Lyapunov exponents and Hurst exponents of heart rate variability signals were analyzed. In this study, we examined the different behavior of heart rate signals during two specific meditation techniques. The results show that heart rate signals became more periodic and their chaotic behavior was decreased in both techniques of meditation. Therefore, nonlinear chaotic indices may serve as a quantitative measure for psychophysiological states such as meditation. In addition, different forms of meditation appear to differentially alter specific components of heart rate signals.

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“…A large number of studies aimed at studying observed effects of meditation on heart rate signals [3][4][5][6][7]. Heart rate variability (HRV) can be described as variation of R-R intervals with respect to the time or beat number.…”

Section: Introductionmentioning

confidence: 99%

Spectral and Time Based Assessment of Meditative Heart Rate Signals

Goshvarpour¹,

Shamsi²,

Goshvarpour³

2013

IJIGSP

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Abstract-The objective of this article was to study the effects of Chi meditation on heart rate variability (HRV). For this purpose, the statistical and spectral measures of HRV from the RR intervals were analyzed. In addition, it is concerned with finding adequate Auto-Regressive Moving Average (ARMA) model orders for spectral analysis of the time series formed from RR intervals. Therefore, Akaike's Final Prediction Error (FPE) was taken as the base for choosing the model order. The results showed that overall the model order chosen most frequently for FPE was p = 8 for before meditation and p = 5 for during meditation. The results suggested that variety of orders in HRV models upon different psychological states could be due to some differences in intrinsic properties of the system.

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Analysis of lagged Poincaré plots in heart rate signals during meditation

Cited by 47 publications

References 8 publications

Informative Nature and Nonlinearity of Lagged Poincaré Plots Indices in Analysis of Heart Rate Variability

Informative Nature and Nonlinearity of Lagged Poincaré Plots Indices in Analysis of Heart Rate Variability

Chaotic Behavior of Heart Rate Signals during Chi and Kundalini Meditation

Spectral and Time Based Assessment of Meditative Heart Rate Signals

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