Comparison of heart rate in embryonic,young and adult Achatina fulica

We have studied the embryonic heart in the gastropod Achatina fulica using eggs soon after their deposition. We also followed the development of organs, with the main emphasis on the heart and its physiology. The embryos were examined at different stages by carefully removing egg shell until hatching. In this context the heart rate (HR) was analysed in embryonic snails and compared with that of young (from hatching) and adults. The HR of embryos dissected from newly deposited eggs was irregular, with a mean frequency of 0.42?±?0.14?Hz. The heartbeat during the ontogeny was more rhythmic and HR increased to 0.82?±?0.12?Hz. The intersystolic intervals (ISI) in real time showed a Gaussian distribution for all animals. The peak ISI from Gaussian fit closely matched the cumulative probability for corresponding data. Although the HR increased after hatching, comparisons yield a weak correlation (R?=?0.56?±?0.27) with the total body weight of embryonic, young and adult snails.     

Nonlinear dynamics of heart rate variability during experimental hemorrhage in ketamine-anesthetized rats

Indexes of heart rate variability (HRV) based on linear stochastic models are independent risk factors for arrhythmic death (AD). An index based on a nonlinear deterministic model, a reduction in the point correlation dimension (PD2i), has been shown in both animal and human studies to have a higher sensitivity and specificity for predicting AD. Dimensional reduction subsequent to transient ischemia was examined previously in a simple model system, the intrinsic nervous system of the isolated rabbit heart. The present study presents a new model system in which the higher cerebral centers are blocked chemically (ketamine inhibition of N-methyl-D-aspartate receptors) and the system is perturbed over a longer 15-min interval by continuous hemorrhage. The hypothesis tested was that dimensional reduction would again be evoked, but in association with a more complex relationship between the system variables. The hypothesis was supported, and we interpret the greater response complexity to result from the larger autonomic superstructure attached to the heart. The complexities observed in the nonlinear heartbeat dynamics constitute a new genre of autonomic response, one clearly distinct from a hardwired reflex or a cerebrally determined defensive reaction.     

Continuous wavelet filtering on webcam photoplethysmographic signals to remotely assess the instantaneous heart rate

Photoplethysmographic signals obtained from a webcam are analyzed through a continuous wavelet transform to assess the instantaneous heart rate. The measurements are performed on human faces. Robust image and signal processing are introduced to overcome drawbacks induced by light and motion artifacts. In addition, the respiration signal is recovered using the heart rate series by respiratory sinus arrhythmia, the natural variation in heart rate driven by the respiration. The presented algorithms are implemented on a mid-range computer and the overall method works in real-time. The performance of the proposed heart and breathing rates assessment method was evaluated using approved contact probes on a set of 12 healthy subjects. Results show high degrees of correlation between physiological measurements even in the presence of motion. This paper provides a motion-tolerant method that remotely measures the instantaneous heart and breathing rates. These parameters are particularly used in telemedicine and affective computing, where the heart rate variability analysis can provide an index of the autonomic nervous system.     

Real-time detection of workload changes using heart rate variability

This work presents a novel approach to detecting real-time changes in workload using heart rate variability (HRV). We propose that for a given workload state, the values of HRV vary in a sub-range of a Gaussian distribution. We describe methods to monitor a HRV signal in real-time for change points based upon sub-Gaussian fitting. We tested our method on subjects sitting at a computer performing a low workload surveillance task and a high workload video game task. The proposed algorithm showed superior performance compared to the classic CUSUM method for detecting task changes.     

Heart rate regulation processed through wavelet analysis and change detection: some case studies

Heart rate variability (HRV) is an indicator of the regulation of the heart, see Task Force (Circulation 93(5):1043-1065, 1996). This study compares the regulation of the heart in two cases of healthy subjects within real life situations: Marathon runners and shift workers. After an update on the state of the art on HRV processing, we specify our probabilistic model: We choose modeling heartbeat series by locally stationary Gaussian process (Dahlhaus in Ann Stat 25, 1997). HRV is then processed by the combination of two statistical methods: (1) Continuous wavelet transform for calculating the spectral density energy in the high frequency (HF) and low frequency (LF) bands and (2) Change point analysis to detect changes of heart regulation. Next, we plot the variations of the HF and LF energy in extreme conditions for both populations. This puts in light, that physical activities (rest, moderate sport, marathon race) can be ordered in a logical continuum. This allows to define a new index based on HF and LF energy that is log HF + log LF which appears relevant to measure HR regulation. The results obtained are pertinent but have to be completed by further studies.     

Noninvasive technique for measurement of heartbeat regularity in zebrafish (Danio rerio) embryos

Background  

Zebrafish (Danio rerio), due to its optical accessibility and similarity to human, has emerged as model organism for cardiac research. Although various methods have been developed to assess cardiac functions in zebrafish embryos, there lacks a method to assess heartbeat regularity in blood vessels. Heartbeat regularity is an important parameter for cardiac function and is associated with cardiotoxicity in human being. Using stereomicroscope and digital video camera, we have developed a simple, noninvasive method to measure the heart rate and heartbeat regularity in peripheral blood vessels. Anesthetized embryos were mounted laterally in agarose on a slide and the caudal blood circulation of zebrafish embryo was video-recorded under stereomicroscope and the data was analyzed by custom-made software. The heart rate was determined by digital motion analysis and power spectral analysis through extraction of frequency characteristics of the cardiac rhythm. The heartbeat regularity, defined as the rhythmicity index, was determined by short-time Fourier Transform analysis.     

Comparison of higher order spectra in heart rate signals during two techniques of meditation: Chi and Kundalini meditation

The human heartbeat is one of the important examples of complex physiologic fluctuations. For the first time in this study higher order spectra of heart rate signals during meditation have explored. Specifically, the aim of this study was to analysis and compares the contribution of quadratic phase coupling of human heart rate variability during two forms of meditation: (1) Chinese Chi (or Qigong) meditation and (2) Kundalini Yoga meditation. For this purpose, Bispectrum was estimated by using biased, parametric and the direct (FFT) method. The results show that the mean Bispectrum magnitude of heart rate signals increased during Kundalini Yoga meditation, but it decreased significantly during Chi meditation. However, in both meditation techniques phase-coupled harmonics are shifted to the higher frequencies during meditation. In addition, it has shown that not only there are significant differences between rest and meditation states, but also heart rate patterns appear to be influenced by different types of meditation.     

Modeling baroreflex regulation of heart rate during orthostatic stress

During orthostatic stress, arterial and cardiopulmonary baroreflexes play a key role in maintaining arterial pressure by regulating heart rate. This study presents a mathematical model that can predict the dynamics of heart rate regulation in response to postural change from sitting to standing. The model uses blood pressure measured in the finger as an input to model heart rate dynamics in response to changes in baroreceptor nerve firing rate, sympathetic and parasympathetic responses, vestibulo-sympathetic reflex, and concentrations of norepinephrine and acetylcholine. We formulate an inverse least squares problem for parameter estimation and successfully demonstrate that our mathematical model can accurately predict heart rate dynamics observed in data obtained from healthy young, healthy elderly, and hypertensive elderly subjects. One of our key findings indicates that, to successfully validate our model against clinical data, it is necessary to include the vestibulo-sympathetic reflex. Furthermore, our model reveals that the transfer between the nerve firing and blood pressure is nonlinear and follows a hysteresis curve. In healthy young people, the hysteresis loop is wide, whereas, in healthy and hypertensive elderly people, the hysteresis loop shifts to higher blood pressure values, and its area is diminished. Finally, for hypertensive elderly people, the hysteresis loop is generally not closed, indicating that, during postural change from sitting to standing, baroreflex modulation does not return to steady state during the first minute of standing.     

Wavelet transform to quantify heart rate variability and to assess its instantaneous changes.

Heart rate variability is a recognized parameter for assessing autonomous nervous system activity. Fourier transform, the most commonly used method to analyze variability, does not offer an easy assessment of its dynamics because of limitations inherent in its stationary hypothesis. Conversely, wavelet transform allows analysis of nonstationary signals. We compared the respective yields of Fourier and wavelet transforms in analyzing heart rate variability during dynamic changes in autonomous nervous system balance induced by atropine and propranolol. Fourier and wavelet transforms were applied to sequences of heart rate intervals in six subjects receiving increasing doses of atropine and propranolol. At the lowest doses of atropine administered, heart rate variability increased, followed by a progressive decrease with higher doses. With the first dose of propranolol, there was a significant increase in heart rate variability, which progressively disappeared after the last dose. Wavelet transform gave significantly better quantitative analysis of heart rate variability than did Fourier transform during autonomous nervous system adaptations induced by both agents and provided novel temporally localized information.     

Gaussian mixture model of heart rate variability

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters.     

Synthesis of HRV signals characterized by predetermined time-frequency structure by means of time-varying ARMA models

In this paper we present two methodologies to generate heart rate variability (HRV) signals characterized by controlled and real-like time-frequency (TF) structure to be used to assess different methods of non-stationary HRV analysis. The synthesized signals are stochastic processes whose TF structure is predetermined by choosing either the time-course of the instantaneous frequencies and powers or the shape of the TF model function. They consist of three steps: (a) choice of the desired TF structure of the signals by choosing a set of design parameters; (b) automatic identification of the parameters of the corresponding models via simple closed-form expressions; (c) synthesis of the desired stochastic signals. Two measures to evaluate the goodness of the simulated signals are also given. Using this framework we were able to model the wide range of non-stationarities observed in heart rate modulation during exercise stress testing and experiments of music-induced emotions. We used the proposed methodology to assess the capability of the smoothed pseudo Wigner–Ville distribution (SPWVD) to quantify HRV patterns. We observed that the SPWVD followed the temporal evolution of the spectral components even when sudden and sharp transitions occur.     

Respiratory sinus arrhythmia from two coupled pacemakers.

We reproduce global features of respiratory sinus arrhythmia (RSA), a prominent source of heart rate variability, from two signals coupled in alternate fashion so dominance periodically switches back and forth between them. We consider two different possibilities for this coupling and illustrate our method with numerical simulations that we contrast with the corresponding results from real data. We interpret our findings within the context of the two-pacemaker model of the heartbeat, an alternative to the single-pacemaker mechanism of pulse generation in the orthodox conduction model.     

A mathematical model of human heart including the effects of heart contractility varying with heart rate changes

Incorporating the intrinsic variability of heart contractility varying with heart rate into the mathematical model of human heart would be useful for addressing the dynamical behaviors of human cardiovascular system, but models with such features were rarely reported. This study focused on the development and evaluation of a mathematical model of the whole heart, including the effects of heart contractility varying with heart rate changes. This model was developed based on a paradigm and model presented by Ottesen and Densielsen, which was used to model ventricular contraction. A piece-wise function together with expressions for time-related parameters were constructed for modeling atrial contraction. Atrial and ventricular parts of the whole heart model were evaluated by comparing with models from literature, and then the whole heart model were assessed through coupling with a simple model of the systemic circulation system and the pulmonary circulation system. The results indicated that both atrial and ventricular parts of the whole heart model could reasonably reflect their contractility varying with heart rate changes, and the whole heart model could exhibit major features of human heart. Results of the parameters variation studies revealed the correlations between the parameters in the whole heart model and performances (including the maximum pressure and the stroke volume) of every chamber. These results would be useful for helping users to adjust parameters in special applications.     

Blood pressure and heart rate variability in workers of 8-hour shifts

This study examined the effects of shiftwork on the cardiovascular system. The blood pressure (BP) and heart rate variability (HRV) of 134 male workers, who worked 8-hour shifts with rapid rotation of shifts at 3-day intervals, were examined for all the three shifts. In addition, the job stress was measured by Karasek's JCQ 49-item questionnaire and the circadian type was assessed by the morningness-eveningness questionnaire. The smoking and alcohol drinking habits, marital status and past medical history were also obtained. The method of analyzing the measured data based on a mixed model was used to illustrate the association between the shiftwork duration and the BP or HRV. The average age of workers was 29 years (between 25-44). Among them, 77.9% were current smokers, 50% showed the passive type of job strain in Karasek's model. The mean shiftwork duration was 5.21 years (range 5.4 months--10 years). In the circadian type, none of them belonged to a definitely morning type or a definitely evening type. In the multivariate analysis adjusted by age, job strain, shift, circadian rhythm and smoking, the blood pressure showed significantly increasing trends according to shiftwork duration in both the systolic and diastolic BP. The heart rate variability also showed a significantly decreasing trend according to the shiftwork duration in both the parasympathetic and sympathetic functions (p < 0.05). These results suggests that there are negative health effects arising from shiftwork on the cardiovascular system.     

Identification of development and autonomic nerve activity from heart rate variability in preterm infants

Heartbeat intervals, which are determined basically by regular excitations of the sinoatrial node, show significant fluctuation referred to as the heart rate variability (HRV). The HRV is mostly due to nerve activities through the sympathetic and parasympathetic branches of the autonomic nervous system (ANS). In recent years, it has been recognized that the HRV shows a greater complexity than ever expected, suggesting that it includes much information about ANS activities. In this study, we investigated relationship between HRV and development in preterm infants. To this end, heartbeat intervals were continuously recorded from 11 preterm infants in NICU. The recording periods were ranging from several days to weeks depending on the individuals. The HRV at various ages was then characterized by several indices. They include power spectrum as well as the mean and standard deviation of the series. For the power spectrum, the low-frequency band power (LF), high-frequency band power (HF), LF/HF (the ratio between LF and HF), beta (scaling exponent of the spectrum) were estimated. The detrended fluctuation analysis (DFA) was also employed to obtain short- and long-range scaling exponents. Each of these indices showed a correlation with the age. We showed that the long-range scaling exponent, derived from the DFA, was most significantly correlated with the age, suggesting that it could be a robust index to characterize the development of preterm infants.     

Estimation of Instantaneous Complex Dynamics through Lyapunov Exponents: A Study on Heartbeat Dynamics

Measures of nonlinearity and complexity, and in particular the study of Lyapunov exponents, have been increasingly used to characterize dynamical properties of a wide range of biological nonlinear systems, including cardiovascular control. In this work, we present a novel methodology able to effectively estimate the Lyapunov spectrum of a series of stochastic events in an instantaneous fashion. The paradigm relies on a novel point-process high-order nonlinear model of the event series dynamics. The long-term information is taken into account by expanding the linear, quadratic, and cubic Wiener-Volterra kernels with the orthonormal Laguerre basis functions. Applications to synthetic data such as the Hénon map and Rössler attractor, as well as two experimental heartbeat interval datasets (i.e., healthy subjects undergoing postural changes and patients with severe cardiac heart failure), focus on estimation and tracking of the Instantaneous Dominant Lyapunov Exponent (IDLE). The novel cardiovascular assessment demonstrates that our method is able to effectively and instantaneously track the nonlinear autonomic control dynamics, allowing for complexity variability estimations.     

Resting heart rate,heart rate variability and functional decline in old age

Background:

Heart rate and heart rate variability, markers of cardiac autonomic function, have been linked with cardiovascular disease. We investigated whether heart rate and heart rate variability are associated with functional status in older adults, independent of cardiovascular disease.

Methods:

We obtained data from the Prospective Study of Pravastatin in the Elderly at Risk (PROSPER). A total of 5042 participants were included in the present study, and mean follow-up was 3.2 years. Heart rate and heart rate variability were derived from baseline 10-second electrocardiograms. Heart rate variability was defined as the standard deviation of normal-to-normal RR intervals (SDNN). Functional status in basic (ADL) and instrumental (IADL) activities of daily living was measured using Barthel and Lawton scales, at baseline and during follow-up.

Results:

The mean age of the study population was 75.3 years. At baseline, higher heart rate was associated with worse ADL and IADL, and lower SDNN was related to worse IADL (all p values < 0.05). Participants in the highest tertile of heart rate (range 71–117 beats/min) had a 1.79-fold (95% confidence interval [CI] 1.45–2.22) and 1.35-fold (95% CI 1.12–1.63) higher risk of decline in ADL and IADL, respectively (p for trend < 0.001 and 0.001, respectively). Participants in the lowest tertile of SDNN (range 1.70–13.30 ms) had 1.21-fold (95% CI 1.00–1.46) and 1.25-fold (95% CI 1.05–1.48) higher risk of decline in ADL and IADL, respectively (both p for trends < 0.05). All associations were independent of sex, medications, cardiovascular risk factors and comorbidities.

Interpretation:

Higher resting heart rate and lower heart rate variability were associated with worse functional status and with higher risk of future functional decline in older adults, independent of cardiovascular disease. This study provides insight into the role of cardiac autonomic function in the development of functional decline.Elevated heart rate and reduced heart rate variability — the beat-to-beat variation in heart rate intervals — both reflect an altered balance of the autonomic nervous system tone characterized by increased sympathetic and/or decreased parasympathetic activity.^1–3 Sympathetic overactivity has been linked to a procoagulant state and also to risk factors for atherosclerosis, including metabolic syndrome, obesity and subclinical inflammation.^2–4 Moreover, increased heart rate is related to atherosclerosis, not only as an epiphenomenon of sympathetic overactivity, but also through hemodynamic mechanisms, such as high pulsatile shear stress, which leads to endothelial dysfunction.⁵Atherosclerosis has been linked to increased risk of functional decline in older people via cardiovascular events.⁶ As the world population is aging, the burden of functional disability is expected to increase.⁶ It has been hypothesized that heart rate and heart rate variability are markers of frailty, an increased vulnerability to stressors and functional decline.⁷ However, the direct link between these 2 parameters and risk of functional decline has not been fully established, and it is uncertain whether this association is independent of cardiovascular comorbidities.In this study, we examined whether heart rate and heart rate variability were cross-sectionally and longitudinally associated with functional status in older adults at high risk of cardiovascular disease, independent of cardiovascular risk factors and comorbidities.     

Differences between heart rate and blood pressure variability in schizophrenia.

Heart rate and blood pressure variability parameters were assessed to determine the risk of cardiac mortality in schizophrenia. We investigated 21 acute, unmedicated patients with paranoid schizophrenia and 21 matched controls. Cardiovascular parameters obtained included heart rate variability, blood pressure variability, cardiac output and left ventricular work index. All parameters investigated were analyzed using linear and non-linear techniques. These investigations revealed increased left ventricular work index and reduced heart rate variability. Furthermore, blood pressure was significantly higher compared to controls, whereas its variability was unchanged. We conclude that our results reflect autonomic cardiovascular dysregulation in acute schizophrenia.     

Nonlinear dynamics of heart rate variability in cocaine-exposed neonates during sleep

The aim of this study was to determine the effects of prenatal cocaine exposure (PCE) on the dynamics of heart rate variability in full-term neonates during sleep. R-R interval (RRI) time series from 9 infants with PCE and 12 controls during periods of stable quiet sleep and active sleep were analyzed using autoregressive modeling and nonlinear dynamics. There were no differences between the two groups in spectral power distribution, approximate entropy, correlation dimension, and nonlinear predictability. However, application of surrogate data analysis to these measures revealed a significant degree of nonlinear RRI dynamics in all subjects. A parametric model, consisting of a nonlinear delayed-feedback system with stochastic noise as the perturbing input, was employed to estimate the relative contributions of linear and nonlinear deterministic dynamics in the data. Both infant groups showed similar proportional contributions in linear, nonlinear, and stochastic dynamics. However, approximate entropy, correlation dimension, and nonlinear prediction error were all decreased in active versus quiet sleep; in addition, the parametric model revealed a doubling of the linear component and a halving of the nonlinear contribution to overall heart rate variability. Spectral analysis indicated a shift in relative power toward lower frequencies. We conclude that 1) RRI dynamics in infants with PCE and normal controls are similar; and 2) in both groups, sympathetic dominance during active sleep produces primarily periodic low-frequency oscillations in RRI, whereas in quiet sleep vagal modulation leads to RRI fluctuations that are broadband and dynamically more complex.     

Effects of deuterium oxide and temperature on heart rate in Drosophila melanogaster

A non-intrusive optical technique has been developed to monitor heartbeat in late third-instar Drosophila larvae. Heartbeat in this insect is an oscillation that is not temperature compensated. Deuterium oxide lengthens the period of a number of high and low frequency oscillators and clocks in a variety of organisms. To determine whether deuterium affects heart rate, flies were raised on proteated and deuterated media and their heartbeat was monitored at four temperatures ranging from 18 to 33 degrees C. The rate of heartbeat increased linearly with increasing temperature, and decreased with increasing concentrations of deuterium. There was a significant interaction between temperature and deuterium: the higher the concentration of deuterium oxide the less temperature-sensitive was the heart rate. Raising temperatures also increased the amount of "noise" in the rhythm: signal-to-noise ratio, which characterizes the amount of power in a rhythmic signal, decreased with increasing temperatures. Deuterium oxide had no effect on signal-to-noise ratio.