Causal linear parametric model for baroreflex gain assessment in patients with recent myocardial infarction

Spectral and cross-spectral analysis of R-R interval and systolic arterial pressure (SAP) spontaneous fluctuations have been proposed for noninvasive evaluation of baroreflex sensitivity (BRS). However, results are not in good agreement with clinical measurements. In this study, a bivariate parametric autoregressive model with exogenous input (ARXAR model), able to divide the R-R variability into SAP-related and -unrelated parts, was used to quantify the gain (alpha(ARXAR)) of the baroreflex regulatory mechanism. For performance assessing, two traditional noninvasive methods based on frequency domain analysis [spectral, baroreflex gain by autogressive model (alpha(AR)); cross-spectral, baroreflex gain by bivariate autoregressive model (alpha(2AR))] and one based on the time domain [baroreflex gain by sequence analysis (alpha(SEQ))] were considered and compared with the baroreflex gain by phenylephrine test (alpha(PHE)). The BRS evaluation was performed on 30 patients (61 +/- 10 yr) with recent (10 +/- 3 days) myocardial infarction. The ARXAR model allowed dividing the R-R variability (950 +/- 1,099 ms(2)) into SAP-related (256 +/- 418 ms(2)) and SAP-unrelated (694 +/- 728 ms(2)) parts. alpha(AR) (12.2 +/- 6.1 ms/mmHg) and alpha(2AR) (8.9 +/- 5.6 ms/mmHg) as well as alpha(SEQ) (12.6 +/- 7.1 ms/mmHg) overestimated BRS assessed by alpha(PHE) (6.4 +/- 4.7 ms/mmHg), whereas the ARXAR index gave a comparable value (alpha(ARXAR) = 5.4 +/- 3.3 ms/mmHg). All noninvasive methods were significantly correlated to alpha(PHE) (alpha(ARXAR) and alpha(SEQ) were more correlated than the other indexes). Thus the baroreflex gain obtained describing the causal dependence of R-R interval on SAP showed a good agreement with alpha(PHE) and may provide additional information regarding the gain estimation in the frequency domain.     

Entropies of short binary sequences in heart period dynamics

Dynamic aspects of R-R intervals have often been analyzed by means of linear and nonlinear measures. The goal of this study was to analyze binary sequences, in which only the dynamic information is retained, by means of two different aspects of regularity. R-R interval sequences derived from 24-h electrocardiogram (ECG) recordings of 118 healthy subjects were converted to symbolic binary sequences that coded the beat-to-beat increase or decrease in the R-R interval. Shannon entropy was used to quantify the occurrence of short binary patterns (length N = 5) in binary sequences derived from 10-min intervals. The regularity of the short binary patterns was analyzed on the basis of approximate entropy (ApEn). ApEn had a linear dependence on mean R-R interval length, with increasing irregularity occurring at longer R-R interval length. Shannon entropy of the same sequences showed that the increase in irregularity is accompanied by a decrease in occurrence of some patterns. Taken together, these data indicate that irregular binary patterns are more probable when the mean R-R interval increases. The use of surrogate data confirmed a nonlinear component in the binary sequence. Analysis of two consecutive 24-h ECG recordings for each subject demonstrated good intraindividual reproducibility of the results. In conclusion, quantification of binary sequences derived from ECG recordings reveals properties that cannot be found using the full information of R-R interval sequences.     

A new method in applying power spectral statistics to examine cardio-respiratory interactions in fish

Power spectral analysis (PSA) provides a powerful tool for determining frequency oscillations in time signals, and it is accepted that mammals can show distinct components in the heart rate (fH) spectrum that are synchronous with ventilatory frequency (fV). Using similar signal processing techniques, these fundamental components at fV are not apparent in the spectrum calculated from fish fH. Here we compare conventional PSA on the R-R interval tachogram generated from ECG traces recorded in rats and fish, with PSA on the raw ECG waveform. The rat R-R tachogram showed a defined sigmoidal component, whereas the fish R-R tachogram was a more chaotic waveform. In agreement with the literature, PSA of these respective waveforms produced a component at the same frequency as ventilation in the rat, but of lower frequency than ventilation for the fish. Applying PSA to the rat ECG produced a spectrum with a fundamental component of similar frequency to that observed in the R-R tachogram spectrum, indicating that the latter adequately contained heart rate variability (HRV) oscillations. However, PSA of the ECG in fish contrasted with that from the R-R tachogram, with components observed in the latter spectrum being absent from the former. This suggests that the frequency components determined by PSA on the fish R-R tachogram were not true components, but were aliased (or folded-back) from higher up in the spectrum. Using established aliasing equations, recalculation of these peaks showed that their true frequency was similar to that of the ventilatory frequency for individual fish. The extent of cardio-respiratory interaction, resulting in fV < f(H/2) in rats but fV > f(H/2) in fish, is suggested to be the origin of the differences observed.     

Spectral analysis of R-R interval variability in inspiratory breath holding in man at rest and during emotional strain

30 young males performed inspiratory breath holdings during expectation of an aversive stimulus and at relative rest. The consecutive R-R intervals of the ECG from breath-hold trial were analysed via spectral analysis of time series. Following parameters were ascertained for each breath holding: mean R-R interval, total R-R interval variability, breath-hold time and relative variability in three spectral bands 3-8 s, 8-12 s and 12-18 s. Neither of these variables was influenced by expectation of an aversive stimulus. The data were subsequently analysed by means of multivariate analysis. Three distinct frequency components were selected according to both histogram data and multivariate analysis. Their modal periods were 5-6 s, 12 s and 16 s respectively. The 8-12 s component of R-R interval variability dominated during breath holdings. The 3-8 s band bore a negative relationship to breath-hold time.     

Observations on respiratory and cardiovascular rhythmicities during yogic high-frequency respiration.

Yogic high-frequency respiration--kapalabhati (KB)--was studied in 24 subjects from a point of rhythmicity. Respiratory movements, blood pressure and R-R intervals of ECG were recorded in parallel and evaluated by spectral analysis of time series. Respiratory signals during KB were modulated by 0.1 Hz rhythm in 82% of experiments. This component was also present in R-R intervals and blood pressure during KB. Frequency (0.2-0.3 Hz) was observed in 67% of respiratory records. The presence of the component 0.2-0.3 Hz in respiration was dependent on resting respiratory frequency. This frequency component was reduced in R-R intervals but increased in blood pressure during kapalabhati as compared to that at rest. The occurrence of both frequency components in respiration during KB supports the hypothesis about the integrative role of cardiovascular and respiratory rhythms in physiological states characterized by altered respiratory frequency.     

Signal processing methods for information enhancement in atrial fibrillation: Spectral analysis and non-linear parameters

Recently, the research efforts in the context of electrocardiographical recording during atrial fibrillation (AF) has been directed to broaden the understandings on the electrophysiological and structural remodelling occurring during the arrhythmia and on characterizing the different types of AF. Following this line, both surface ECG and endocardial electrograms have been thoroughly studied and a series of linear and non-linear parameters were computed either directly on the electrograms or on the derived activation series.

In this paper, we reviewed some signal processing methods used to characterize surface ECG and endocardial electrograms during AF, focusing on spectral and non-linear analysis. In particular, parametric and non-parametric methods for spectral analysis of the residual ECG, i.e. atrial waves obtained from surface ECG after removing ventricular activity, and endocardial recordings are described. The different purposes of spectral analysis (exploring autonomic functions, analysis of spontaneous AF behaviour and predicting therapeutic effects) are illustrated with some examples. In addition, we described some more recent non-linear methods applied to AF, assessing the organization of atrial signals as well as ventricular response in AF. In particular, methods derived from embedding time series and based on entropy computation are illustrated and exemplified.     

Non-linear and linear forecasting of the EEG time series

The method of non-linear forecasting of time series was applied to different simulated signals and EEG in order to check its ability of distinguishing chaotic from noisy time series. The goodness of prediction was estimated, in terms of the correlation coefficient between forecasted and real time series, for non-linear and autoregressive (AR) methods. For the EEG signal both methods gave similar results. It seems that the EEG signal, in spite of its chaotic character, is well described by the AR model.     

Saturation of high-frequency oscillations of R-R intervals in healthy subjects and patients after acute myocardial infarction during ambulatory conditions

This study was designed to assess the relationship between R-R interval length and heart rate (HR) variability in healthy subjects and patients after an acute myocardial infarction (AMI). Twenty-four-hour ambulatory ECG recordings were obtained for 76 healthy subjects and 82 post-AMI patients. The high-frequency (HF, 0.15-0.4 Hz) spectral power of R-R intervals was analyzed in 5-min sequences over 24 h and plotted as a function of the corresponding mean R-R interval length. Quadratic regression model was used to study the relationship between R-R interval length and HF power. If a distinct deflection point (R-R0) occurred in the quadratic regression (r >0.50) model before maximum R-R interval, indicating the plateau of HF power, the relationship between R-R interval and HF power was defined as saturated. Otherwise, the relationship was defined as linear (r >0.50) or low correlated (r >0.50). The relationship was saturated in 35, linear in 38, and low correlated in 3 healthy subjects. In post-AMI patients, the relationship was saturated in 9 subjects, linear in 44 subjects, and low correlated in 29 patients. The HF power analyzed from the 24-h period did not differ between the saturated and linear groups, but when analyzed from the linear portion only, HF spectral power was smaller in the linear than the saturated group both among healthy subjects (P <0.05) and post-AMI patients (P <0.05). Saturation of the HF oscillations of R-R intervals is a common phenomenon in healthy subjects and also present in post-AMI patients during ambulatory conditions. This saturation effect may bias the quantification of cardiac vagal function when HR variability is analyzed from Holter recordings.     

Deriving heart period variability from blood pressure waveforms.

International standards for calculating heart period variability (HPV) from a series of R-wave intervals (R-R) in an electrocardiographic (ECG) recording have been widely accepted. It is possible, and potentially useful in various settings, to use systolic blood pressure waveform intervals to estimate HPV, but the validity of HPV derived from blood pressure (BP) waveforms has not been established. To test the reliability between BP- and ECG-derived HPV indexes, we evaluated data from 234 healthy adults in four studies of HPV reactivity to stress. Study conditions included resting baseline, arithmetic, Stroop test, speech presentation, and orthostatic tilt. Continuous ECG and BP recordings were sampled at a rate of 500 Hz, scored by the same methods, and used to calculate heart rate and time- and frequency-domain measures of HPV. Overall, reliability between the two methods was very high for computing heart rate and HPV indexes. High-frequency HPV indexes were somewhat less reliably computed. In conclusion, in healthy adults, with the use of appropriate methods, BP waveforms can produce reliable indexes of HPV.     

Electrocardiogram,vectocardiogram and body surface maps in patients with panic disorder

An increased risk of myocardial ischemic changes was demonstrated in patients suffering from panic disorder (PD). Using classical ECG methods, this risk cannot be evaluated in most patients. We measured the vectocardiogram (VCG) using Frank orthogonal leads and body surface maps (BSM) including 12-lead ECG. In our study of 11 PD patients (2 men, 9 women), without any seizures and pharmacological treatment and without cardiovascular symptoms, we found marked sinus tachycardia (heart rate 90.1 +/- 12.2 min(-1)) and a shorter R-R interval (678 +/- 93.6 ms) than in 27 controls (heart rate 73.6 +/- 7.7min(-1), R-R 822.7 +/- 86.4 ms) (5 men, 22 women) (p<0.001). The VCG measured spatial QRS-STT angle was more opened (70.3 +/- 24.5 degrees) than in the control group (49.5 +/- 19.5 degrees) (p<0.05). The maximum (extremum) in depolarization (DIAM max 30, 40) and repolarization (RIAM max 35) of body surface isoarea and isointegral (RIIM max) maps was less positive (p<0.001) and the minimum (DIAM min 40) was less negative than in the controls (p<0.05) even in the period free of a panic attack. Our results showed the changes in the heart electric field parameters occurred in PD patients when compared to the control group.     

The ECG changes due to altitude and to catecholamines

In order to distinguish the effects of beta-receptor stimulation on the ECG from other factors during short-term adjustment to hypoxic aerohypoxia, the ECG of 19 volunteers were compared during moderately acute, stepwise exposure to high altitude (6,000 m) in a low pressure chamber, once with and once without beta-receptor blockade (propranolol), and after isoprenaline inhalation at ground level. The results show that beta-receptor stimulation accounts mainly for most ECG changes during altitude exposure, i.e., for the shortening of R-R interval, the lengthening of Q-T and in particular for the ST-T flattening, the latter therefore being only an indirect sign of hypoxia. After exclusion of the catecholamines, the minor but still significant ECG changes at altitude (shortening of R-R interval, increase of P wave, prolongation of P-Q, deviation of the R vector, T wave flattening in the left precordial leads) may be attributed to other, so far undefined factors, such as cardiac hypoxia, vagal withdrawal, or increase of pulmonary resistance.     

A Novel Method for Fast Change-Point Detection on Simulated Time Series and Electrocardiogram Data

Although Kolmogorov-Smirnov (KS) statistic is a widely used method, some weaknesses exist in investigating abrupt Change Point (CP) problems, e.g. it is time-consuming and invalid sometimes. To detect abrupt change from time series fast, a novel method is proposed based on Haar Wavelet (HW) and KS statistic (HWKS). First, the two Binary Search Trees (BSTs), termed TcA and TcD, are constructed by multi-level HW from a diagnosed time series; the framework of HWKS method is implemented by introducing a modified KS statistic and two search rules based on the two BSTs; and then fast CP detection is implemented by two HWKS-based algorithms. Second, the performance of HWKS is evaluated by simulated time series dataset. The simulations show that HWKS is faster, more sensitive and efficient than KS, HW, and T methods. Last, HWKS is applied to analyze the electrocardiogram (ECG) time series, the experiment results show that the proposed method can find abrupt change from ECG segment with maximal data fluctuation more quickly and efficiently, and it is very helpful to inspect and diagnose the different state of health from a patient''s ECG signal.     

The surgeon's mental load during decision making at various stages of operations

In surgeons while opening the wound, during the operation proper, closing the skin and immediately after the operation, the ECG was recorded telemetrically for 5-min periods. From the ECG recordings, indices reflecting cardiac arrhythmia and emotional level were calculated. It is concluded that the process of decision making during the vital stages of operations causes a fall in the CHRV (the coefficient of heart rate variability), S2 (the variance of R-R intervals) and VR (the variability range of R-R intervals). It seems that of the indices studied, the most suitable for evaluation of the degree of mental loading due to decision making processes are the CHRV and S2. During all the stages of surgery studied, and immediately after the operation, an increase in tonus of the sympathetic nervous system occurs in surgeons indicating a rise in emotional level.     

Effects of atropine and propranolol on the respiratory, circulatory, and ECG responses to high altitude in man

In order to analyze the respiratory, cardiovascular, and ECG responses to acute hypoxic hypoxia, three experimental series were carried out in a randomized manner on 11 healthy, unacclimatized volunteers at rest during standardized stepwise exposure to 6000 m (PAO2 35.2 +/- 2.9 mmHg/4.7 +/- 0.4 kPa) in a low-pressure chamber a) without (control), b) with propranolol, and c) with atropine combined with propranolol. The results show that hypoxic hyperventilation and alveolar gases are not affected by activation of the sympatho-adrenal axis or by parasympathetic withdrawal. Sympathetic activity, however, increases heart rate, stroke volume (pulse pressure), estimated cardiac output and systolic blood pressure, whereas decreased parasympathetic activity increases heart rate and estimated cardiac output, but lowers stroke volume. The fall in peripheral resistance, observed during progressive hypoxia in all three groups, is thought to be due to hypoxia-induced depression of the vasomotor center. At altitude catecholamine secretion and vagal withdrawal synergistically account in the ECG for the R-R shortening, the relative Q-T lengthening, the elevation of the P wave and the ST-T flattening. Probable direct hypoxic effects on the heart are the increase in P-Q duration and the minor but still significant depression of the T wave. It is concluded that at altitude increased sympatho-adrenal and decreased parasympathetic activity is without effect on hypoxic hyperventilation, but accounts for most of the cardiovascular and ECG changes. Diminution of sympathetic activity and imminent vagotonia arising after acute ascent to 6000 m probably reflect hypoxia of the central nervous system.     

Relationship between cortical electrical and cardiac autonomic activities in the awake lizard, Gallotia galloti

ECG and EEG signals were simultaneously recorded in lizards, Gallotia galloti, both in control conditions and under autonomic nervous system (ANS) blockade, in order to evaluate possible relationships between the ANS control of heart rate and the integrated central nervous system activity in reptiles. The ANS blockers used were prazosin, propranolol, and atropine. Time-domain summary statistics were derived from the series of consecutive R-R intervals (RRI) of the ECG to measure beat-to-beat heart rate variability (HRV), and spectral analysis techniques were applied to the EEG activity to assess its frequency content. Both prazosin and atropine did not alter the power spectral density (PSD) of the EEG low frequency (LF: 0.5-7.5 Hz) and high frequency (HF: 7.6-30 Hz) bands, whereas propranolol decreased the PSD in these bands. These findings suggest that central beta-adrenergic receptor mechanisms could mediate the reptilian waking EEG activity without taking part any alpha(1)-adrenergic and/or cholinergic receptor systems. In 55% of the lizards in control conditions, and in approximately 43% of the lizards under prazosin and atropine, a negative correlation between the coefficient of variation of the series of RRI value (CV(RRI)) and the mean power frequency (MPF) of the EEG spectra was found, but not under propranolol. Consequently, the lizards' HRV-EEG-activity relationship appears to be independent of alpha(1)-adrenergic and cholinergic receptor systems and mediated by beta-adrenergic receptor mechanisms.     

A pilot investigation of the effect of extremely low frequency pulsed electromagnetic fields on humans' heart rate variability

The question whether pulsed electromagnetic field (PEMF) can affect the heart rhythm is still controversial. This study investigates the effects on the cardiocirculatory system of ELF-PEMFs. It is a follow-up to an investigation made of the possible therapeutic effect ELF-PEMFs, using a commercially available magneto therapeutic unit, had on soft tissue injury repair in humans. Modulation of heart rate (HR) or heart rate variability (HRV) can be detected from changes in periodicity of the R-R interval and/or from changes in the numbers of heart-beat/min (bpm), however, R-R interval analysis gives only a quantitative insight into HRV. A qualitative understanding of HRV can be obtained considering the power spectral density (PSD) of the R-R intervals Fourier transform. In this study PSD is the investigative tool used, more specifically the low frequency (LF) PSD and high frequency (HF) PSD ratio (LF/HF) which is an indicator of sympatho-vagal balance. To obtain the PSD value, variations of the R-R time intervals were evaluated from a continuously recorded ECG. The results show a HR variation in all the subjects when they are exposed to the same ELF-PEMF. This variation can be detected by observing the change in the sympatho-vagal equilibrium, which is an indicator of modulation of heart activity. Variation of the LF/HF PSD ratio mainly occurs at transition times from exposure to nonexposure, or vice versa. Also of interest are the results obtained during the exposure of one subject to a range of different ELF-PEMFs. This pilot study suggests that a full investigation into the effect of ELF-PEMFs on the cardiovascular system is justified.     

Comparison of methods for estimating motor unit firing rate time series from firing times

The central nervous system regulates recruitment and firing of motor units to modulate muscle tension. Estimation of the firing rate time series is typically performed by decomposing the electromyogram (EMG) into its constituent firing times, then lowpass filtering a constituent train of impulses. Little research has examined the performance of different estimation methods, particularly in the inevitable presence of decomposition errors. The study of electrocardiogram (ECG) and electroneurogram (ENG) firing rate time series presents a similar problem, and has applied novel simulation models and firing rate estimators. Herein, we adapted an ENG/ECG simulation model to generate realistic EMG firing times derived from known rates, and assessed various firing rate time series estimation methods. ENG/ECG-inspired rate estimation worked exceptionally well when EMG decomposition errors were absent, but degraded unacceptably with decomposition error rates of ⩾1%. Typical EMG decomposition error rates—even after expert manual review—are 3–5%. At realistic decomposition error rates, more traditional EMG smoothing approaches performed best, when optimal smoothing window durations were selected. This optimal window was often longer than the 400 ms duration that is commonly used in the literature. The optimal duration decreased as the modulation frequency of firing rate increased, average firing rate increased and decomposition errors decreased. Examples of these rate estimation methods on physiologic data are also provided, demonstrating their influence on measures computed from the firing rate estimate.     

Poincaré plot interpretation using a physiological model of HRV based on a network of oscillators

In this paper, we develop a physiological oscillator model of which the output mimics the shape of the R-R interval Poincaré plot. To validate the model, simulations of various nervous conditions are compared with heart rate variability (HRV) data obtained from subjects under each prescribed condition. For a variety of sympathovagal balances, our model generates Poincaré plots that undergo alterations strongly resembling those of actual R-R intervals. By exploiting the oscillator basis of our model, we detail the way that low- and high-frequency modulation of the sinus node translates into R-R interval Poincaré plot shape by way of simulations and analytic results. With the use of our model, we establish that the length and width of a Poincaré plot are a weighted combination of low- and high-frequency power. This provides a theoretical link between frequency-domain spectral analysis techniques and time-domain Poincaré plot analysis. We ascertain the degree to which these principles apply to real R-R intervals by testing the mathematical relationships on a set of data and establish that the principles are clearly evident in actual HRV records.     

A hybrid on-line ECG segmenting system for long-term monitoring.

This paper introduces a new hybrid ECG beat segmenting system, which can be applied in the processing unit of single-channel, long-term ECG monitors for the on-line segmentation of the ECG signal. Numerous ECG segmentation techniques are already existing and applied, however sufficiently robust and reliable methods currently require more than one ECG signal channel and quite complex computations, which are practically not feasible in stand-alone, low-cost monitors. Our new system approach presents a time domain segmentation technique based on a priori physiological and morphological information of the ECG beat. The segmentation is carried out after classifying the ECG beat, using the linear approximation of the filtered ECG signal and considering the pathophysiological properties as well. The proposed algorithms require moderate computational power, allowing the practical realization in battery powered stand-alone long-term cardiac monitors or small-sized cardiac defibrillators. The prototype version of the system was implemented in Matlab. The test and evaluation of the system was carried out with the help of reference signal databases.     

Non-linear dynamic analysis of the cardiac rhythm during transient myocardial ischemia.

Coronary artery occlusions related to myocardial ischemia drive cardiac control system reactions that may lead to heart failure. The purpose of this study was to assess the autonomic nervous system (ANS) response during prolonged percutaneous transluminal coronary angioplasty (PTCA). Continuous ECG data were acquired from 50 patients before and during PTCA, with occlusions in the left anterior descending, left circumflex or right coronary artery. Heart rate variability (HRV) was analyzed for 3-min segments of the R-R interval signal obtained from ECG data. The ANS behavior was evaluated by HRV analysis using fractal-like indices. The fractal scalar exponent alpha(1) and power-law slope beta decreased considerably during PTCA. This indicates that significant reactions of autonomic control of the heart rate occurred during coronary artery occlusions, with a reduction in complexity of the ANS.