Description of heart-rate variability data in accordance with a physiological model for the genesis of heartbeats

Publication guidelines for human heart rate and heart rate variability studies in psychophysiology-Part 1: Physiological underpinnings and foundations of measurement

This Committee Report provides methodological, interpretive, and reporting guidance for researchers who use measures of heart rate (HR) and heart rate variability (HRV) in psychophysiological research. We provide brief summaries of best practices in measuring HR and HRV via electrocardiographic and photoplethysmographic signals in laboratory, field (ambulatory), and brain-imaging contexts to address research questions incorporating measures of HR and HRV. The Report emphasizes evidence for the strengths and weaknesses of different recording and derivation methods for measures of HR and HRV. Along with this guidance, the Report reviews what is known about the origin of the heartbeat and its neural control, including factors that produce and influence HRV metrics. The Report concludes with checklists to guide authors in study design and analysis considerations, as well as guidance on the reporting of key methodological details and characteristics of the samples under study. It is expected that rigorous and transparent recording and reporting of HR and HRV measures will strengthen inferences across the many applications of these metrics in psychophysiology. The prior Committee Reports on HR and HRV are several decades old. Since their appearance, technologies for human cardiac and vascular monitoring in laboratory and daily life (i.e., ambulatory) contexts have greatly expanded. This Committee Report was prepared for the Society for Psychophysiological Research to provide updated methodological and interpretive guidance, as well as to summarize best practices for reporting HR and HRV studies in humans.

Modeling individual differences in cardiovascular response to gravitational stress using a sensitivity analysis

The human cardiovascular (CV) system elicits a physiological response to gravitational environments, with significant variation between different individuals. Computational modeling can predict CV response, however model complexity and variation of physiological parameters in a normal population makes it challenging to capture individual responses. We conducted a sensitivity analysis on an existing 21-compartment lumped-parameter hemodynamic model in a range of gravitational conditions to 1) investigate the influence of model parameters on a tilt test CV response and 2) to determine the subset of those parameters with the most influence on systemic physiological outcomes. A supine virtual subject was tilted to upright under the influence of a constant gravitational field ranging from 0 g to 1 g. The sensitivity analysis was conducted using a Latin hypercube sampling/partial rank correlation coefficient methodology with subsets of model parameters varied across a normal physiological range. Sensitivity was determined by variation in outcome measures including heart rate, stroke volume, central venous pressure, systemic blood pressures, and cardiac output. Results showed that model parameters related to the length, resistance, and compliance of the large veins and parameters related to right ventricular function have the most influence on model outcomes. For most outcome measures considered, parameters related to the heart are dominant. Results highlight which model parameters to accurately value in simulations of individual subjects' CV response to gravitational stress, improving the accuracy of predictions. Influential parameters remain largely similar across gravity levels, highlighting that accurate model fitting in 1 g can increase the accuracy of predictive responses in reduced gravity.NEW & NOTEWORTHY Computational modeling is used to predict cardiovascular responses to altered gravitational environments. However, considerable variation between subjects and model complexity makes accurate parameter assignment for individuals challenging. This computational effort studies sensitivity in cardiovascular model outcomes due to varying parameters across a normal physiological range. This allows determination of which parameters have the largest influence on outcomes, i.e., which parameters must be most carefully selected to give accurate predictions of individual responses.

Computational model of cardiovascular response to centrifugation and lower body cycling exercise

Short-radius centrifugation combined with exercise has been suggested as a potential countermeasure against spaceflight deconditioning. Both the long-term and acute physiological responses to such a combination are incompletely understood. We developed and validated a computational model to study the acute cardiovascular response to centrifugation combined with lower body ergometer exercise. The model consisted of 21 compartments, including the upper body, renal, splanchnic, and leg circulation, as well as a four-chamber heart and pulmonary circulation. It also included the effects of gravity gradient and ergometer exercise. Centrifugation and exercise profiles were simulated and compared with experimental data gathered on 12 subjects exposed to a range of gravitational levels (1 and 1.4G measured at the feet) and workload intensities (25-100 W). The model was capable of reproducing cardiovascular changes (within ± 1 SD from the group-averaged behavior) due to both centrifugation and exercise, including dynamic responses during transitions between the different phases of the protocol. The model was then used to simulate the hemodynamic response of hypovolemic subjects (blood volume reduced by 5-15%) subjected to similar gravitational stress and exercise profiles, providing insights into the physiological responses of experimental conditions not tested before. Hypovolemic results are in agreement with the limited available data and the expected responses based on physiological principles, although additional experimental data are warranted to further validate our predictions, especially during the exercise phases. The model captures the cardiovascular response for a range of centrifugation and exercise profiles, and it shows promise in simulating additional conditions where data collection is difficult, expensive, or infeasible.NEW & NOTEWORTHY Artificial gravity combined with exercise is a potential countermeasure for spaceflight deconditioning, but the long-term and acute cardiovascular response to such gravitational stress is still largely unknown. We provide a novel mathematical model of the cardiovascular system that incorporates gravitational stress generated by centrifugation and lower body cycling exercise, and we validate it with experimental measurements from human subjects. Simulations of experimental conditions not used for model development corroborate the model's predictive capabilities.

Effect of measurement duration on accuracy of pulse-counting

In this study, the relation between the measurement duration and accuracy of pulse-counting was quantitatively examined with special reference to low-frequency fluctuations in heart rate variability. The interbeat intervals of 70 healthy male subjects were measured in standing, sitting and supine positions. Pulse rates for various durations were calculated by objective-scoring simulation based on the heartbeat recordings of the subjects. The duration of pulse-counting continuously varied from 6 to 60 s in the simulation. Simulated pulse rates were compared with the rate calculated from the 60 s that includes the given duration, and the absolute difference between the two rates was defined as the error. Average errors of pulse-counting for 15 s were 1.89, 1.89 and 1.80 bpm for standing, sitting and supine positions, respectively. No difference in error was observed between standing and sitting positions; however, smaller errors were observed in the supine position.

A real-time automated point-process method for the detection and correction of erroneous and ectopic heartbeats

The presence of recurring arrhythmic events (also known as cardiac dysrhythmia or irregular heartbeats), as well as erroneous beat detection due to low signal quality, significantly affects estimation of both time and frequency domain indices of heart rate variability (HRV). A reliable, real-time classification and correction of ECG-derived heartbeats is a necessary prerequisite for an accurate online monitoring of HRV and cardiovascular control. We have developed a novel point-process-based method for real-time R-R interval error detection and correction. Given an R-wave event, we assume that the length of the next R-R interval follows a physiologically motivated, time-varying inverse Gaussian probability distribution. We then devise an instantaneous automated detection and correction procedure for erroneous and arrhythmic beats by using the information on the probability of occurrence of the observed beat provided by the model. We test our algorithm over two datasets from the PhysioNet archive. The Fantasia normal rhythm database is artificially corrupted with known erroneous beats to test both the detection procedure and correction procedure. The benchmark MIT-BIH Arrhythmia database is further considered to test the detection procedure of real arrhythmic events and compare it with results from previously published algorithms. Our automated algorithm represents an improvement over previous procedures, with best specificity for the detection of correct beats, as well as highest sensitivity to missed and extra beats, artificially misplaced beats, and for real arrhythmic events. A near-optimal heartbeat classification and correction, together with the ability to adapt to time-varying changes of heartbeat dynamics in an online fashion, may provide a solid base for building a more reliable real-time HRV monitoring device.

Nonlinear statistical modeling and model discovery for cardiorespiratory data

We present a Bayesian dynamical inference method for characterizing cardiorespiratory (CR) dynamics in humans by inverse modeling from blood pressure time-series data. The technique is applicable to a broad range of stochastic dynamical models and can be implemented without severe computational demands. A simple nonlinear dynamical model is found that describes a measured blood pressure time series in the primary frequency band of the CR dynamics. The accuracy of the method is investigated using model-generated data with parameters close to the parameters inferred in the experiment. The connection of the inferred model to a well-known beat-to-beat model of the baroreflex is discussed.

Distortion properties of the interval spectrum of IPFM generated heartbeats for heart rate variability analysis

The integral pulse frequency modulation (IPFM) model converts a continuous-time signal into a modulated series of event times, often represented as a pulse train. The IPFM process is important to the field of heart rate variability (HRV) as a simple model of the sinus modulation of heart rate. In this paper, we discuss the distortion properties associated with employing the interval spectrum for the recovery of the input signal from an IPFM process's output pulse train. The results state, in particular for HRV, how precisely the interval spectrum can be used to infer the modulation signal responsible for a series of heartbeats. We have developed a detailed analytical approximation of the interval spectrum of an IPFM process with multiple sinusoids as the input signal. Employing this result, we describe the structure and the distortion of the interval spectrum. The distortion properties of the interval spectrum are investigated systematically for a pair of frequency components. The effects of linear and nonlinear distortion of the fundamentals, the overall contribution of harmonic components to the total power, the relative contribution of "folded back" power due to aliasing and the total distortion of the input spectrum are investigated. We also provide detailed comparisons between the interval spectrum and the spectrum of counts (SOC). The spectral distortion is significant enough that caution should be taken when interpreting the interval spectrum, especially for high frequencies or large modulation amplitudes. Nevertheless, the distortion levels are not significantly larger than those of the SOC. Therefore, the spectrum of intervals may be considered a viable technique that suffers more distortion than the SOC.

The cardiovascular system as coupled oscillators?

Based on physiological knowledge, and on an analysis of signals related to its dynamics, we propose a model of the cardiovascular system. It consists of coupled oscillators. Each of them describes one of the subsystems involved in the regulation of one passage of blood through the circulatory system. The flow of blood through the system of closed tubes-the blood vessels-is described by wave equations.

Spectral components of heart rate variability determined by wavelet analysis

Spectral components of heart rate variability (HRV) are determined in the time-frequency domain using a wavelet transform. Based on the finer estimation of low-frequency content enabled by the logarithmic resolution of the wavelet transform, corrections of spectral intervals, already defined by Fourier and model based methods, are proposed. The characteristic peaks between 0.0095 and 0.6 Hz are traced in time and four spectral intervals are defined, I (0.0095-0.021 Hz), II (0.021-0.052 Hz), III (0.052-0.145 Hz) and IV (0.145-0.6 Hz), within which peaks are located for all subjects included. These intervals are shown to be invariant regardless of the age and the state of the system. We also show that the frequency and power of the spectral components are related to age, AMI and particularly to type II diabetes mellitus.

Heart rate and blood pressure power spectral analysis during calcium channel blocker induced hypotension

PURPOSE

To observe heart rate (HRV) and blood pressure variability (BPV) as indices of neurocirculatory responses to induced hypotension with diltiazem and/or nicardipine for hip surgery.

METHODS

Thirty-six ASA I-II patients received diltiazem (group D, n = 12), nicardipine (group N, n = 12) or combination of diltiazem/nicardipine (group DN, n = 12). The intensity of HRV and BPV, was determined by spectral analysis of HRV and BPV before anesthesia (T0), just before induced hypotension (T1), and at 10 and 30 min after the start of induced hypotension (T2 and T3, respectively). The logarithmic HRV and BPV were integrated: sympathetic and parasympathetic mediated low frequency area (0.06-0.1 Hz, LF), parasympathetic related high frequency area (0.15-0.4 Hz, HF) and total frequency area (0.01-0.4 Hz). Blood loss was assessed by weighing gauzes and measuring suction.

RESULTS

Group DN had less blood loss (466 +/- 46 ml, mean +/- SEM) than group D (733 +/- 100 ml, P < 0.05). Diltiazem (11.4 +/- 0.9 microg x kg(-1) x min(-1)), and combination of diltiazem (0.25 +/- 0.01 mg x kg(-1)) and nicardipine (5.9 +/- 0.9 microg x kg(-1) x min(-1)) decreased LF-HRV at T2 and T3 (P < 0.05 vs T0 and T1), while nicardipine (8.1 +/- 0.8 microg x kg(-1) x min(-1)) showed increase in LF-HRV at T2 (P < 0.05 vs T1). HF-HRV unchanged through hypotension except for a decrease in group N at T3 (P < 0.05 vs T1). There were no increases in HF-BPV, and LF-BPV, except for a diltiazem induced decrease in LF-BPV at T3 (P < 0.05 vs T0 and T1).

CONCLUSION

Group D and group DN can be used for deliberate hypotension without an increase in sympathetically mediated LF-HRV.

Effect of illuminance and color temperature on lowering of physiological activity

To investigate how illuminance and color temperature in illumination affect the autonomic nervous system and central nervous system in conditions tending to lower physiological activity, and with an ordinary residential setting in mind, we performed an experiment on 8 healthy male subjects. The experimental conditions consisted of 4 conditions provided by a combination of 2 levels of color temperature (3000 K, 5000 K) and 2 levels of illuminance (30 lx, 150 lx). Physiological measurement was carried out during a process of 22 minutes of light exposure followed by 20 minutes of sleep in darkness. Heart rate variability (HRV) was used as an index of the autonomic nervous system, and alpha attenuation coefficient (AAC) and mean frequency of EEG were used as indices of the central nervous system. Subjective evaluation of drowsiness during the experiment was also carried out immediately following the 20 minutes sleep. No effect on HRV from illumination was noted, but significantly (p < 0.05) lower values for AAC were obtained under 3000 K conditions than 5000 K conditions in measurements during the first half of light exposure (Session 1). During alpha attenuation testing, significantly (p < 0.05) lower values for mean frequency in the theta-beta EEG bandwidth were also obtained under 3000 K conditions than 5000 K conditions, but that pattern persisted in measurement during the second half of light exposure (Session 2). Subjective drowsiness was also higher under 3000 K conditions than 5000 K conditions. These results suggest that low color temperature light creates a smooth lowering of central nervous system activity, and that low color temperature illumination can be used effectively in a bedroom or other such environment where it is desirable to facilitate lowered physiological activity.

The Computation of Evoked Heart Rate and Blood Pressure

Abstract For many years psychophysiologists have been interested in stimulus related changes in heart rate and blood pressure. To represent these evoked heart rate and blood pressure patterns, heart rate and blood pressure data have to be transformed into equidistant time series. This paper presents an extensive comparison between two methods. The most often used method is based on linear interpolation, also known as weighted averaging. The low pass filtering method presented here is based on a well-known model for the generation of heart beats, the integral pulse frequency modulation model (IPFM). The comparison shows that the results of the filtering and interpolation procedures are virtually identical. Practically, small differences between the methods disappear in the averaging process. Therefore, the interpolation method is a suitable practical alternative to the computationally complex filtering method.

Normalization of respiratory sinus arrhythmia by factoring in tidal volume

The amplitude of respiratory sinus arrhythmia (RSA) was measured in eight healthy young male students with special reference to the effect of tidal volume (Vt). Under simultaneously controlled respiratory frequency and Vt, the heart rate variability (HRV) of the subjects was measured. While the respiratory frequency was adjusted to either 0.25 or 0.10 Hz, the Vt was controlled at 13 different volumes for each frequency. Linear relationships between RSA amplitude and Vt were observed and close correlations were obtained for 0.25 Hz compared with 0.10 Hz. However, regression equations showed a marked variation among subjects. Furthermore, RSA amplitude was related to vital capacity. Subjects who had lower vital capacity tended to show higher RSA amplitudes at the same Vt. Therefore, the ratio (% Vt) of Vt to vital capacity is a more effective index in normalizing RSA than raw tidal volume. From these results, we have proposed a normalized RSA (RSA amplitude/% Vt) as a new index of autonomic activity that provides a constant value regardless of Vt.

A comparative analysis of preprocessing techniques of cardiac event series for the study of heart rhythm variability using simulated signals

In the present study, using noise-free stimulated signals, we performed a comparative examination of several preprocessing techniques that are used to transform the cardiac event series in a regularly sampled time series, appropriate for spectral analysis of heart rhythm variability (HRV). First, a group of noise-free simulated point event series, which represents a time series of heartbeats, was generated by an integral pulse frequency modulation models. In order to evaluate the performance of the preprocessing methods, the differences between the spectra of the preprocessed simulated signals and the true spectrum (spectrum of the model input modulating signals) were surveyed by visual analysis and by contrasting merit indices. It is desired that estimated spectra match the true spectrum as close as possible, showing a minimum of harmonic components and other artifacts. The merit indices proposed to quantify these mismatches were the leakage rate, defined as a measure of leakage components (located outside some narrow windows centered at frequencies of model input modulating signals) with respect to the whole spectral components, and the numbers of leakage components with amplitudes greater than 1%, 5% and 10% of the total spectral components. Our data, obtained from a noise-free simulation, indicate that the utilization of heart rate values instead of heart period values in the derivation of signals representative of heart rhythm results in more accurate spectra. Furthermore, our data support the efficiency of the widely used preprocessing technique based on the convolution of inverse interval function values with a rectangular window, and suggest the preprocessing technique based on a cubic polynomial interpolation of inverse interval function values and succeeding spectral analysis as another efficient and fast method for the analysis of HRV signals.

Heart rate variability: origins, methods, and interpretive caveats

Components of heart rate variability have attracted considerable attention in psychology and medicine and have become important dependent measures in psychophysiology and behavioral medicine. Quantification and interpretation of heart rate variability, however, remain complex issues and are fraught with pitfalls. The present report (a) examines the physiological origins and mechanisms of heart rate variability, (b) considers quantitative approaches to measurement, and (c) highlights important caveats in the interpretation of heart rate variability. Summary guidelines for research in this area are outlined, and suggestions and prospects for future developments are considered.

Thermal entrainment of heart rate in the preterm infant

Using spectral analysis we have studied changes in the heart rate during periodic thermal stimulation of one foot of infants during quiet sleep. Twenty-two appropriately grown preterm infants were studied in the first 15 d after birth to quantify responses in comparison with previously reported term infants. Babies were stimulated at 0.05, 0.10, and 0.15 Hz. Spectral power was calculated at the stimulus frequency +/-0.01 Hz and +/-0.02 Hz and over the low frequency range 0.03 Hz to 0.17 Hz. The data show that 1) there is an increase in power around the frequency of stimulation for each frequency studied (p < 0.002); and 2) there is an increase in the ratio of local to low frequency power at 0.05 Hz (p = 0.002) and 0.10 Hz (p = 0.001), but not at 0.15 Hz (p = 0.109). These data confirm the concept of entrainment in the appropriately grown preterm infant but demonstrate that it occurs over a wider frequency range than previously reported. The wider range is the same as that of the term infant, although there are differences in the patterns of entrainment between the two groups. Further work is required to map out the maturation of the autonomic nervous system in both the term and the preterm infant with respect to the low frequency components of the heart rate variability power spectrum.

Approximate minimum bias multichannel spectral estimation for heart rate variability

Spectral decomposition of variations in heart rate permits noninvasive measurement of autonomic nervous activity in humans and animals. Autonomic metrics based on spectral analysis are useful in monitoring clinical conditions such as diabetic neuropathy and reinnervation in heart transplant patients. A persistent problem in deriving such autonomic measures is the prerequisite of an accurate and unbiased power spectrum of heart rate variability (HRV). Numerous parametric and nonparametric power spectrum estimators have been introduced, each with its own advantages and drawbacks. Estimator bias has received little attention, despite the fact that at least one common HRV spectrum estimator, the autoregressive method, is known to exhibit bias even in idealized circumstances. We introduce an approximately minimum bias, nonparametric, multichannel spectrum estimation procedure for HRV and contemporaneous signals. The procedure, which is designed specifically for irregular sampling, does not require data segmentation and provides statistically consistent, low variance multichannel spectrum estimates. Estimator performance on simulated and clinical data is presented and compared with results from autoregressive models and Welch periodograms with and without compensation for irregular sampling. Results indicate that the proposed method exhibits advantages over conventional HRV spectrum estimators. Relative computational complexity of the proposed method is also considered.

Postural effect on respiratory sinus arrhythmia with various respiratory frequencies

Heart rate variations during steady state respiration with various frequencies were studied on seven healthy male students at two different body positions. Respiration was controlled at four different frequencies (0.083, 0.100, 0.200, 0.250Hz), and the tidal volume was simultaneously controlled at 1500ml (0.083, 0.100Hz) or 1000ml (0.200, 0.250Hz). A tilting bed was used for changing body position, and the measurements were conducted at horizontal and vertical position. RSA (respiratory sinus arrhythmia) amplitude at 0.250Hz was significantly decreased at vertical position compared with horizontal position. At 0.200Hz the significant decrease could not be obtained although some tendency of decrease appeared. Contrary to these high frequencies, the amplitudes at low frequencies (0.083, 0.100Hz) were significantly increased (p < 0.01) during vertical position. This postural effect on the low frequency RSA could be regarded as a similar result on MWSA (Mayer wave relate sinus arrhythmia) which reflects sympathetic nervous activity. Furthermore, the ratio between the amplitude at 0.100Hz and that at 0.250Hz was significantly correlated with mean heart rate (n = 56, r = 0.73). From these results it was assumed that the RSA amplitude at low frequency associate a with not only parasympathetic nerves but also sympathetic nerves whereas the amplitude at high frequency was solely mediated by parasympathetic nerves.

Differential effects of ketamine and midazolam on heart rate variability

Alterations in autonomic activity caused by anaesthesia can be assessed by spectral analysis of heart rate variability (HRV). This study examined the effects of ketamine and midazolam on HRV. Thirty patients of ASA PS 1 were studied. Fifteen were given ketamine (2 mg.kg-1) and 15 received midazolam (0.3 mg.kg-1), iv. The RR intervals of ECG were measured before and after induction of anaesthesia for ten minutes during spontaneous respiration. Power spectral density of the data was computed using fast Fourier transform. The spectral peaks within each measurement were calculated: low frequency area (LF, 0.04-0.15 Hz), high frequency area (HF, 0.15-0.5 Hz), and total power (TP, 0.04-0.5 Hz). Normalized unit power was derived as follows: low frequency area (nuLF): LF/TP x 100%, high frequency area (nuHF): HF/TP x 100%. Both ketamine and midazolam caused reductions in all measurements of HRV power (P < 0.05). However, ketamine increased nuLF from 64 +/- 14% to 75 +/- 13% (P < 0.05) and decreased nuHF from 36 +/- 14% to 25 +/- 13% (P < 0.05), while midazolam decreased nuLF from 66 +/- 15% to 54 +/- 14% (P < 0.05) and increased nuHF from 34 +/- 15% to 46 +/- 14% (P < 0.05). These results documented that both ketamine and midazolam reduced the total power and all frequency components of power in spite of their opposing effects on autonomic nervous activity. However, normalized unit power showed the expected sympathetic activation with ketamine and sympathetic depression with midazolam since ketamine increased nuLF and midazolam decreased nuLF.

The relation between event-related brain potential, heart rate, and blood pressure responses in an S1-S2 paradigm

Event-related brain potential (ERP), heart rate (HR), and blood pressure (BP) responses were examined during the 6 s foreperiod of a choice-reaction task. Low and high trait-anxious males were required to make same/different judgements based on the similarity of two successively presented visual patterns. The pitch of a warning tone, presented at the beginning of the foreperiod, indicated whether speed or accuracy was to be emphasized on that trial. In different conditions, subjects received either a monetary reward or aversive noise, depending on their performance. Two clusters of parallel variations were observed in the foreperiod: (1) speed/accuracy instructions affected the amplitude of the CNV and, in interaction with anxiety group, the initial decreases in HR and diastolic BP; (2) type of reward, in interaction with speed/accuracy instructions, affected the amplitude of the P300 and PSW, the mid-interval HR acceleration, and subsequent increases in diastolic and systolic BP. A correlational analysis showed a close relationship between changes in HR and BP, whereas no relationship was evident between changes in ERPs and changes in HR and BP.

A comparison of cardiovascular reflex tests and spectral analysis of heart rate variability in healthy subjects

Determination of whether results of cardiovascular reflex tests and spectral analysis of heart rate variability are age dependent and whether there is correlation between results of both, cardiovascular reflex tests (the Valsalva manoeuvre, deep breathing test, handgrip test, cold face stimulus test, orthostatic test) and spectral analysis of heart rate variability were performed on 83 healthy volunteers of both genders, aged 21 to 70 years. We found that results of all heart rate based tests and results of spectral analysis decreased with aging, while results of blood pressure based tests did not. Parasympathetic activity predominated in younger subjects, while in older subjects sympathetic activity was dominant. Valsalva, deep breathing, and orthostatic ratios correlated with integrals of amplitude spectra in the standing posture and deep breathing and cold face stimulus ratios with integrals of amplitude spectra in the supine posture, whereas blood pressure changes during handgrip and orthostatic test did not correlate with integrals of the amplitude spectra. These findings suggest that tests based on heart rate may be more sensitive than tests based on blood pressure changes. This study supports the use of spectral analysis as an additional clinical test of autonomic nervous system function and stresses the importance of age in the evaluation of the results of autonomic nervous system function testing.

Heart-rate variation: what are we measuring?

Many methods have been proposed during the last two decades for the assessment of autonomic nervous system function by quantification of the heart-rate variation (HRV). Relatively little has been written about the HRV in relation to physiological models of the heart-rate regulation. The integral pulse frequency model (IPFM) is a simple model that describes the genesis of heartbeats under the influence of the autonomic nervous system. By comparing simulated HRV data generated with the IPFM model with data from healthy volunteers we found similarities indicating that the model accurately reflects real data. Furthermore, we found a considerable difference between HRV measurements based on beat-by-beat heart-rate and measurements based on the heartbeat interval. Our results suggest that the commonly used electrocardiographic RR interval representation of heart-rate variation might possess an inherent nonlinear, mean heart-rate-dependent property indicating that analysis directly based on RR intervals can give biased results with respect to the underlying autonomic activity. The conclusions embrace all measurements of variation that are directly based on RR intervals including simple indices as well as higher-level quantification such as spectral analysis.

Study of cardiac arrhythmia using the Kalman filter

It has been known for some time that the variability of the R-R intervals in the electrocardiogram signal yields valuable information concerning the various types of arrhythmia that might be present. It has recently been suggested that the identification of cardiac arrhythmia might be possible by applying spectral analysis techniques to the data. An investigation is made into the possible application of the Kalman filter identifier in the calculation of time varying spectra of the data, with a view to studying the onset of arrhythmia and also short bursts of arrhythmia. To this end, data from the MIT-BIH database are analysed; in particular, cases of bigenimy, trigenimy, second degree block and ventricular flutter have been looked at. It is found that this technique can, in many cases, detect the onset of arrhythmia and sometimes actually identify the arrhythmia that is present. It is suggested that the Kalman filter identifier could have a general application in studying both the normal and arrhythmic segments of data to yield valuable medical information concerning the subject under study.

Inferring vagal effects on the heart from changes in cardiac cycle length: implications for cycle time-dependency

Since the now classical experiments by Brown and Eccles in 1934, the effect of a stimulation of the vagus nerve on the heart has been derived from changes in the length of cardiac periods. Based on a simple model for the genesis of heartbeats, it is shown that the procedure employed by Brown and Eccles gives a distorted picture of the actual vagal effect. A corrected procedure for inferring the vagal effect from changes in heart period length is proposed. This new procedure is applied to empirical data from animal experiments with direct stimulation of the vagus nerve. It is shown that, if the vagal effect depends on time of stimulation within the cardiac cycle (cycle time-dependency), single vagal effect curves for each time of stimulation within the cycle have to be constructed. Other data reduction procedures are reviewed with respect to their appropriateness for demonstrating cycle time-dependency.

Plotting systolic, diastolic, and pulse pressure on a real time scale

Since a valid non-invasive method for continuously measuring blood pressure is available for the psychophysiological laboratory, a procedure must be found for depicting blood pressure characteristics (systolic, diastolic, pulse pressure) on a real time scale, that is not simply from one heartbeat to the next. Values for blood pressure characteristics are actualized by heartbeats and thus occur at discrete points in time only, quite like values for heart rate. It is being assumed that the conditions for the blood pressure characteristics vary continuously, however, and that a value, actualized by a heartbeat, is representative for a time interval extending halfway before and after the point in time where it occurs. For computing a value for a real time interval it is proposed to weight the blood pressure values according to the amount of time their respective time intervals extend within the real time interval.

Respiratory modulation of heart rate in newborn infants

Spectral analysis was performed on ventilation and instantaneous heart rate data recorded in 15 term infants during quiet sleep in the first week after delivery, and in 11 of these infants during active sleep. There was a close relation between the main peaks of the ventilation spectra and the corresponding histograms of the reciprocals of Ttot. The spectra for instantaneous heart rate showed power at the rate of breathing (HF) and also at lower frequencies, 0.04-0.2 Hz (LF). During quiet sleep, the relative magnitudes of the HF and LF peaks for heart rate were found to depend on the respiratory rate and the variability of Ttot. During active sleep, most of the power in the heart rate spectrum was concentrated in the LF region. Weighted coherences between ventilation and heart rate were higher during quiet than active sleep, both in the HF and LF spectra. LF power was higher during active than quiet sleep in both ventilation and heart rate. The results suggest that the pattern of breathing has a marked effect on the shape of the heart rate spectrum. In most infants, however, there is no fixed phase relationship between oscillations in ventilation and heart rate, at high or low frequencies. These oscillations are affected by sleep state and hence, by implication, by central nervous system rhythm generators.

Statistical approach for the estimation of daily physical activity levels using the probability density function of heart rate

An investigation was undertaken into the statistical properties of heart rate during daily physical activity. The probability density function of the heart rate was estimated using the Gram-Charlier series. In addition, the probability density was separated into two Gaussian distributions: relatively low and relatively high heart rates. The former appeared to correspond to the metabolic rate associated with basic daily living and the latter appeared to be associated with more active physical activity of the type necessary to sustain or elevate the level of physical fitness. The higher heart rate distribution of five subjects occupied 8.72 +/- 2.15% of a period of waking. The validity of the statistical approach was confirmed with fractional estimation error of 1.22 +/- 0.62%.

Study of cardiac arrhythmia using zero-crossing analysis

It has been known for some time that the variability of the R-R intervals in the electrocardiogram yields valuable information concerning the types of arrhythmia which might be present. In this paper, an investigation is made into the application of zero-crossing analysis to the study of such variability. The number of times the R-R interval crosses its mean value over a specified interval of time is counted, and may be associated with a particular characteristic frequency, related to the dominant frequency components of the power spectrum of R-R intervals. Higher order crossing counts may be computed by taking combinations of sum and difference operations on the original time series. The advantage of using zero-crossing analysis over spectral analysis is the computational simplicity of the former. It is demonstrated, by analysing data taken from the MIT-BIH Arrhythmia database, that zero crossing analysis can sometimes be used t distinguish between different arrhythmias, but forethought concerning the number of sum and difference operations to be taken on the original data set is required when computing the higher order crossing counts.

Longterm heartrate telemetry in small mammals: a comprehensive approach as a prerequisite for valid results

This paper describes a miniature telemetry system which is capable of precise, reliable longterm registration of heartrate (HR) in animals as small as laboratory mice. The ECG-transmitters have a weight of 0.9-1.5 g and a respective lifetime of 3-6 months depending on battery size. With suitable receiving antennas, transmitting range is sufficient for continuous reception in 200 m2 enclosures. The radio signals are demodulated in a signal processor and the ECG is converted to HR on the base of single interbeat intervals. General technical problems of telemetry like miniaturization, performance control, HR acquisition and artifact distinction are discussed. The experimental approach emphasizes the necessity of continuous registration of HR as a reference for experimental responses. Longterm shifts of HR due to social and nonsocial influences as well as experimental feedback effects are demonstrated and discussed.

Respiratory sinus arrhythmia in new-born infants

1. Ventilation was measured in eleven healthy term infants during both quiet and active sleep, using the trunk plethysmograph, and instantaneous heart rate was derived from the electrocardiogram. Variations in individual respiratory and cardiac cycles were compared in each sleep state, and cross-correlations between ventilation and heart rate were used in the analysis of the data. 2. It was found that heart rate and respiratory rate were higher and more variable during active than during quiet sleep, with a small reduction in tidal volume. 3. Cross-correlations showed that respiratory sinus arrhythmia was present in both sleep states, but was more marked during quiet sleep. 4. Running cross-correlations using a 5 s window showed that phase relationships between ventilation and heart rate, were, on the whole, stable during quiet sleep, but markedly unstable during active sleep. 5. It is concluded that in the investigation of respiratory sinus arrhythmia in the new-born, it is important to take account of sleep state, the methods of measuring ventilation and heart rate, and to use analytical techniques suited to the specific purpose of the study. 6. Respiratory sinus arrhythmia is considered to be due to an interaction between systems controlling breathing and those controlling the cardiovascular system, and that this interaction is affected by sleep state.

Time-dependent bradycardia: a new effect?

Time-dependent bradycardia, a term introduced by the Laceys (Lacey and Lacey, 1980), refers to the fact that the duration of a cardiac cycle is related to when in that cycle, or the just preceding cycle, certain stimuli occur. Since stimulus effects on heart activity with very short latencies have been known for a long time, the question arises whether the effect is one in its own right, or whether it is simply a result of the new way of data reduction introduced by the Laceys. Theoretically, the effect can be explained without assuming anything beyond the well-known short latency bradycardia often observed upon stimulation. Derivation of the effect from an empirical curve of cardiac activity not related to cycle phase shows that we are not dealing with a new effect.

Rhythm of sounds produced by larvae of the oriental hornet Vespa orientalis: spectral analysis

In the hornet nest of the species Vespa orientalis, there is transmission of information by acoustic means between the larvae and the adults. The rhythmic pattern of the sounds produced by the larvae was recorded and spectrally analyzed for rhythm frequencies by use of the Fast Fourier Transform. The frequency of the "larval activity duration till cessation" was 0.018 Hz whereas the interval between two successive sound productions ranged from 0 to 1.0 Hz. The possible significance of precise signaling by the larvae towards efficient communication in colonies of social insects is discussed.