Search PubMed⌕ Search

Biomedical subjects

S Cerutti

Publications and source records attributed to S Cerutti.

At least 73 records · Page 4Linked to original sources
PubMed1997

Autonomic function in narcolepsy: power spectrum analysis of heart rate variability.

Ten narcoleptic patients that had never been treated previously and ten healthy volunteers of comparable age underwent 48-h polygraphic recording to assess the effects of wakefulness and sleep on beat-to-beat heart rate variability by means of power spectrum analysis. The study revealed decreased power in the low frequencies (LF) during sleep (whereby an increase of the power in this band is associated with sympathetic activation) compared with wakefulness, with minimal values during stage 3-4 non-REM sleep and higher levels during REM sleep, both in patients and controls. Significantly reduced power in high frequencies (HF; mainly expression of parasympathetic control) and a significantly increased LF/HF ratio during wakefulness before sleep in narcoleptics compared with controls were found. Our study excludes a primary disturbance of cardiac autonomic nervous system in narcoleptics but suggests an altered circadian autonomic function in these patients.

Adult↗
PubMed1997

Vegetative background of sleep: spectral analysis of the heart rate variability.

Phasic events during sleep, either arousal or REM-burst related, and the associated transient cardiovascular responses have been the subject of intensive research in previous studies. However, nontransient (stationary) fluctuations in heart rate have been studied less extensively in the past. They allow a differentiation of the sympathetic and parasympathetic activation, which are related to a low-frequency (LF) and a high-frequency (HF) component of the heart rate variability (HRV) signal, respectively. The resulting LF/HF ratio is a quantitative index of the sympatho-vagal balance. Sleep polygrams from 20 healthy volunteers were recorded in a sleep laboratory. Standard vegetative tests (orthostatic and Valsalva tests) were evaluated. A segmentation procedure, performed on the HRV signal, separated 70-130 transients during the night from the records of stationary heart rate fluctuations. From these periods the sympatho-vagal balance, quantified by the LF/HF, was computed by means of spectral analysis. The more synchronized the sleep was, the more the LF/HF decreased, whereas the LF/HF was significantly increased during REM sleep, indicating a sympathetic predominance during this period. Such an increase was also evident during the last 15 min before REM sleep onset. Results suggest that spectral analysis of the HRV provides additional information of the ultradian rhythmic behavior of the autonomic nervous system function beyond the traditional cardiovascular measurements (mean heart rate, blood pressure, etc.). In contrast to these measurements, which generally show a continuously decreasing cardiovascular activity, as the night proceeds, the results of this study reveal a high sympathetic peak activity during the later REM sleep periods, which is comparable in magnitude to that found in the upright position in wakefulness. This activity may be associated to the well-known incidence peak of ischemic events in the early morning hours.

Arousal↗
PubMed1997

A multivariate time-variant AR method for the analysis of heart rate and arterial blood pressure.

This paper approaches the problem of short-term mechanisms that regulate heart rate and blood pressure variability signals, by focusing the evident changes of their frequency content during transients (dynamic situations in which the behaviour of these control mechanisms may vary on a beat-to-beat basis). In this study, we suggest an autoregressive time-variant spectral estimation method, which is able to follow such dynamic changes in the signals. This method has also been extended to a multivariate approach in order to take into account more than one process at a time, and to assess the mutual influences between the different controlling systems. The algorithms successfully tested on simulated series have also been used to analyse series recorded during a vaso-vagal syncope episode in a tilt manoeuvre and a physical exercise stress test protocol. The results show how this method is able to follow the changing dynamics of the signals on the basis of a closed-loop model of their interaction on a beat-to-beat basis. After a proper identification procedure of the blocks forming the model, it is possible, therefore, to obtain the classical spectral parameters and the gain of the transfer function between the signals. Such parameters constitute new time series that describe the physiopathology of the cardiovascular control systems, even during non-stationary epochs.

Algorithms↗
PubMed1997

Multivariate time-variant identification of cardiovascular variability signals: a beat-to-beat spectral parameter estimation in vasovagal syncope.

In this paper a bivariate, time-variant model able to continuously measure the mutual interactions between heart rate and systolic blood pressure variability signals is presented. A recursive identification of the model parameters makes it possible to estimate, on a beat-to-beat basis, spectral low-frequency (LF) and high-frequency (HF) power, (LF/HF ratio) and cross-spectral (coherence and phase relationships between spectral peaks) indexes during nonstationary events. These indexes can be helpful in: 1) physiological study of autonomic nervous system mechanisms of cardiovascular control and 2) quantification and clinical evaluation of the neural and mechanical links between the two signals. In addition, an estimate of baroreceptive activation (alpha-gain) is continuously extracted. Before applying the model to cardiovascular signals, the reliability of the estimated parameters was tested on simulated signals. Subsequently, the model was applied to investigating vasovagal syncope episodes, aiming at the assessment of autonomic nervous system status and autonomic role in the dynamic phenomena which lead to syncope. The proposed model, which provides noninvasive beat-to-beat evaluation of the autonomic events, may be useful in the description of the syncopal episodes and in the comprehension of the complex physiological mechanisms of syncope.

Algorithms↗
PubMed1997

Spectral decomposition in multichannel recordings based on multivariate parametric identification.

A method of spectral decomposition in multichannel recordings is proposed, which represents the results of multivariate (MV) parametric identification in terms of classification and quantification of different oscillating mechanisms. For this purpose, a class of MV dynamic adjustment (MDA) models in which a MV autoregressive (MAR) network of causal interactions is fed by uncorrelated autoregressive (AR) processes is defined. Poles relevant to the MAR network closed-loop interactions (cl-poles) and poles relevant to each AR input are disentangled and accordingly classified. The autospectrum of each channel can be divided into partial spectra each relevant to an input. Each partial spectrum is affected by the cl-poles and by the poles of the corresponding input; consequently, it is decomposed into the relevant components by means of the residual method. Therefore, different oscillating mechanisms, even at similar frequencies, are classified by different poles and quantified by the corresponding components. The structure of MDA models is quite flexible and can be adapted to various sets of available signals and a priori hypotheses about the existing interactions; a graphical layout is proposed that emphasizes the oscillation sources and the corresponding closed-loop interactions. Application examples relevant to cardiovascular variability are briefly illustrated.

Algorithms↗
PubMed1997

The whale forgetting factor in recursive AR spectral analysis of heart rate variability signals.

Spectral parameters extracted from the heart rate variability signal are obtained on a beat-to-beat basis by means of autoregressive recursive identification. In this paper a whale forgetting window is introduced, instead of the classical exponential one, in order to reduce the noise influence on the estimated parameters. After proper simulation it was found that the whale forgetting window markedly reduces the noise in the identification, but maintains a good response to abrupt changes in the signal. The algorithm was thus applied to the analysis of the HRV data recorded during different transient situations in physiological and pathological conditions. The spectral parameters were obtained on a beat-to-beat basis and their trends were smoother and more accurate with respect to the traditional exponential window also in presence of noise or artifacts in the time series (sudden and short time changes, ectopic beats, etc.), without losing the signal variations of physiological interest.

Adult↗
PubMed1997

Study of the Lyapunov exponents in heart rate variability signals.

Heart rate variability signals obtained from 24 h recordings are analyzed for normal and pathological subjects. This time series contains information about the autonomic nervous system action regulating the beat-to-beat heart rate. Nonlinear contributions to the long period variability have been assessed by the calculation of the entire spectrum of Lyapunov exponents, after the system trajectory reconstruction, starting from the original variability signal. The positivity of Lyapunov exponent values, obtained from an unknown process, can establish whether the structure generating it shows nonlinear chaotic characteristics. This is what happens for the cardiovascular signals. Moreover, the different values obtained for the Lyapunov exponents operate a classification among the considered pathophysiological cases.

Electrocardiography, Ambulatory↗
PubMed1997

On-line analysis of AEP and EEG for monitoring depth of anaesthesia.

Achieving and monitoring adequate depth of anaesthesia is a challenge to the anaesthetist. With the introduction of muscle relaxing agents, the traditional signs of awareness are often obscured or difficult to interpret. These signs include blood pressure, heart rate, pupil size, etc. However, these factors do not describe the depth of anaesthesia, (DA), in a cerebral activity sense, hence there is a desire to achieve a better measure of the DA. Auditory Evoked Potentials (AEP) provide two aspects relevant to anaesthesia: (1) they have identifiable anatomical significance and, (2) their characteristics reflect the way in which the brain reacts to a stimulus. However, AEP is embedded in noise from the ongoing EEG background activity. Hence, processing is needed to improve the signal to noise ratio. The methods applied were moving time averaging (MTA) and ARX-modeling. The EEG was collected from the left hemisphere and analysed by FFT to 1 sec epochs and the spectral edge frequency was calculated. Both the changes in ARX extracted AEP and the spectral edge frequency of the EEG correlated well with the time interval between propofol induction and onset of anaesthesia measured by clinical signs (i.e., cessation of eye-lash reflex). The MTA extracted AEP was significantly slower in tracing the transition from consciousness to unconsciousness.

Anesthesia↗
PubMed1996

Linear and nonlinear dynamics of heart rate variability after acute myocardial infarction with normal and reduced left ventricular ejection fraction.

We analyzed heart rate variability (HRV) in 2 groups of patients after acute myocardial infarction with normal and reduced ejection fraction (EF) by considering both the power of the 2 major harmonic components at low and high frequency and 2 indexes of nonlinear dynamics, namely the 1/f slope and the correlation dimension D2. HRV of patients with a reduced EF was characterized by a diminished RR variance as well as a different distribution of the residual power in all frequency ranges, with lower values of the low-frequency component expressed in both absolute and normalized units, and of the low- to high-frequency ratio. In these patients we also observed a steeper slope of the negative regression line between power and frequency in the very low frequency range. The presence of a smaller fractal dimension was suggested by a lower D2. Thus, in patients after acute myocardial infarction with a reduced EF, the reduction in HRV is associated with a different distribution of the residual power in the entire frequency range, which suggests a diminished responsiveness of sinus node to neural modulatory inputs.

Case-Control Studies↗
PubMed1996

Classification of coupling patterns among spontaneous rhythms and ventilation in the sympathetic discharge of decerebrate cats.

The spontaneous low- and high-frequency rhythms in the sympathetic discharge of decerebrate artificially ventilated cats are affected by external ventilation. Two graphical methods (i.e. the space-time separation plot and the frequency tracking locus) are used to classify the non-linear interactions. The observed behaviours in the sympathetic discharge consist of phase-locked periodic dynamics (at various frequency ratios with ventilation), quasiperiodic and aperiodic patterns. They depend on the experimental condition. In control condition the sympathetic discharge appears more frequently locked to each ventilatory cycle (1:1 dynamics). However, some cases of quasiperiodic dynamics are found. A sympathetic activation stimulus, such as inferior vena cava occlusion, is able to synchronize slow rhythms in the sympathetic discharge to a subharmonic of ventilation. During a sympathetic inhibition stimulus, such as aortic constriction, 1:1 dynamics is detected but the amplitude of the sympathetic responses can be modulated by unlocked slow rhythms. Moreover some cases of aperiodic dynamics are observed. Vagotomy reduces the 1:1 coupling between sympathetic outflow and ventilation. Vagotomy plus spinalisation disrupts periodic dynamics in the sympathetic discharge so that irregular and complex patterns are found.

Animals↗
PubMed1996

Non-linear algorithms for processing biological signals.

This paper illustrates different approaches to the analysis of biological signals based on non-linear methods. The performance of such approaches, despite the greater methodological and computational complexity is, in many instances, more successful compared to linear approaches, in enhancing important parameters for both physiological studies and clinical protocols. The methods introduced employ median filters for pattern recognition, adaptive segmentation, data compression, prediction and data modelling as well as multivariate estimators in data clustering through median learning vector quantizers. Another approach described uses Wiener-Volterra kernel technique to obtain a satisfactory estimation and causality test among EEG recordings. Finally, methods for the assessment of non-linear dynamic behaviour are discussed and applied to the analysis of heart rate variability signal. In this way invariant parameters are studied which describe non-linear phenomena in the modelling of the physiological systems under investigation.

Algorithms↗
PubMed1996

Assessment of heart rate variability changes during dipyridamole infusion and dipyridamole-induced myocardial ischemia: a time variant spectral approach.

OBJECTIVES: We sought to evaluate changes in RR interval variability during dipyridamole infusion and dipyridamole-induced myocardial ischemia. BACKGROUND: Myocardial ischemia and the autonomic nervous system can be mutually interdependent. Spectral analysis of RR interval variability is a useful tool in assessing autonomic tone. METHODS: We used a time variant autoregressive spectral estimation algorithm that could extract spectral variables even in the presence of nonstationary signals. Two groups were considered: group A (patients with ischemia, n = 15) with effort or mixed angina, angiographically assessed coronary artery disease and positive exercise and dipyridamole echocardiographic test results, and group B (control subjects, n = 10) with normal exercise and dipyridamole echocardiographic test results. We investigated the following variables: RR interval mean and variance, low frequency (LF) and high frequency (HF) power in normalized units, LF ratio (LF/LFbasal power), HF ratio (HF/HFbasal power) and LF/HF ratio. For each test epoch, we calculated for group A and group B the mean value +/- SE of all indexes considered. Differences due to an effect either of group (ischemic vs. control) or of time (including both drug and ischemia effects) were analyzed by using analysis of variance for repeated measurements. RESULTS: Dipyridamole injection was characterized by a reduction of all spectral components in negative test. The LF ratio was the only variable able to discriminate patients with ischemia from control subjects (p < 0.05), whereas a time effect was evident for both mean RR interval and high frequency power in normalized units (p < 0.05). The LF ratio decreased in group B from 1 +/- 0.00 (basal) to 0.31 +/- 0.22 (peak), and increased in group A from 1 +/- 0.00 to 15.41 +/- 6.59, respectively. Results of an unpaired t test comparing the peak values of the two groups were also statistically significant (p < 0.01). CONCLUSIONS: Our data show that time variant analysis of heart rate variability evidences an increase in the low frequency ratio that allows differentiation of positive from negative test results, suggesting that the electrocardiogram may contain ischemia information unrelated to ST-T variations, even if their enhancement requires a more complex data processing procedure.

Aged↗
PubMed1996

Effect of a new model of hemodialysis potassium removal on the control of ventricular arrhythmias.

The primary aim of this multicenter, prospective, randomized cross-over study was to clarify whether a new model of hemodialysis (HD) potassium (K) removal using a decreasing intra-HD dialysate K concentration and a constant plasma-dialysate K gradient (treatment B) is capable of reducing the arrhythmogenic effect of standard HD, which has a constant dialysate K concentration and decreasing plasma-dialysate K gradient (treatment A). The secondary aim was to verify whether this new model is clinically safe. In treatment B, the initial dialysate K concentration had to be 1.5 mEq/liter less than the plasma K concentration, and exponentially decrease to 2.5 mEq/liter at the end of HD. Forty-two chronic HD patients with an increase in premature ventricular complexes (PVC) during dialysis were enrolled from 18 participating centers, and randomly assigned to either sequence 1 (ABA) or sequence 2 (BAB). A pool of 333 of 378 expected ECG Holter recordings were checked for signal quality; 269 (71%) from 36 patients (86%) had a satisfactory signal quality and 108 were selected for analysis (1 per patient per period). There was a difference in the natural logarithm of the increase in PVC/hr and PVC couplets/hr during HD between treatments A and B (1.70 +/- 1.59 vs. 1.09 +/- 1.76 and 0.94 +/- 0.86 vs. 0.64 +/- 1.01, a reduction of 36% and 32%, P = 0.011 and 0.047, respectively) without any carry over effect (P = 0.61 and 0.24, respectively). The fact that this decrease of one third is due to a lower plasma-dialysate K gradient is supported by the observation that it was more evident during the first than the last two hours of HD (a reduction in the natural logarithm of the increase in PVC/hr and PVC couplets/hr of 60% and 60%, P 0.002 and 0.009, vs. 26% and 17%, P = 0.098 and 0.332, respectively): the initial plasma-dialysate K gradient was 2.3 times lower during treatment B than during treatment A, without adversely affecting pre-HD plasma K levels. These results could have a considerably clinical impact not only because of the possibility of physiologically decreasing the arrhythmogenic effect of HD, but also because this effect can be considered a "marker" of the electrophysiological derangement induced by the administration of standard HD three times a week for years ("electric disequilibrium syndrome").

Aged↗
PubMed1996

Spectral analysis of short term R-Tapex interval variability during sinus rhythm and fixed atrial rate.

Analysis of heart rate variability has been proven useful in stratifying post myocardial patients at risk and in evaluating autonomic dysfunction. Recently augmented inter-lead variability of the QT interval has been associated with increased mortality as a result of arrhythmia and proposed as a marker of dispersion of ventricular repolarization. As the duration of the QT interval is largely dependent upon the length of the preceding cardiac cycle it is tempting to analyse whether neural mechanisms might also directly exert additional modulation. Using autoregressive algorithms we therefore analysed RR and R-Tapex interval variabilities in 15 normal subjects during sinus rhythm and in six patients with a fixed atrial rate. In controls mean R-Tapex interval and variance measured on the vector magnitude were, respectively, 245 +/- 6 ms and 5.1 +/- 0.7 ms2. Spectral analysis of R-Tapex indicated the presence of two spectral components which corresponded to the low and high frequency components of heart rate variability. In R-Tapex variability, high frequency (44 +/- 4 nu) was predominant over low frequency (29 +/- 4 nu). During controlled respiration, a manoeuvre associated with enhanced vagal modulation of sinus node, there was a further increase in high frequency (58 +/- 4 nu) whereas during tilt the low frequency component of R-Tapex variability became predominant (57 +/- 6 nu). In patients with a fixed atrial rate, variance was extremely low (3 +/- 0.9 ms2) and only a respiration-related high frequency component was recognizable in spectral analysis of RR and R-Tapex variabilities. This component was likely to depend upon mechanically induced changes in cardiac vector orientation. These data indicate that during sinus rhythm short-term R-Tapex interval variability is characterized by the same rhythmical components present in RR variability. However, the presence of a very low variance and of only a high frequency component in patients in whom the physiological variability of sinus node is abolished by atrial pacing. suggests that neural modulatory mechanisms do not exert a direct effect on the length of the R-Tapex interval.

Adult↗
PubMed1996

Power spectrum analysis contribution to the detection of cardiovascular dysautonomia in multiple sclerosis.

In multiple sclerosis (MS) autonomic cardiovascular dysfunction is an uncommon, but potentially dangerous event, to which studies of spectral analysis of heart rate variability have not been applied, yet. MATERIAL AND METHODS--We studied 16 patients with definite MS (11 women and 5 men, mean age 30.3 +/- 7.4 yrs., mean EDSS 2.06 +/- 1.42) and 16 sex- and age-matched healthy controls. Besides cardiovascular reflex tests (valsalva manoeuvre, deep breathing, lying to standing, Blood Pressure response to standing and sustained handgrip), each underwent spectral analysis of the R-R interval short-term variability at rest and after tilting, to detect three components: very low frequency (VLF), low frequency (LF) and high frequency (HF). A recent brain MRI was obtained from patients, to compare plaque characteristics with spectral parameters. RESULTS--At cardiovascular reflexes, only four patients (25%) showed an impairment, mostly of a mild degree. VLF and LF at rest were lower in MS subjects than in controls (p < 0.01). No significant correlation was found between spectral parameters and lesion area or localization as detected on MRI. CONCLUSIONS--Spectral analysis could usefully flank reflex tests to detect autonomic subclinical cardiovascular abnormalities.

Adult↗
PubMed1996

Non-linear dynamics and chaotic indices in heart rate variability of normal subjects and heart-transplanted patients.

OBJECTIVES: Heart rate variability (HRV) is characterised by a variety of linear, non-linear, periodical and non-periodical oscillations. The aim of the present study was mainly to investigate the role played by neural mechanisms in determining non-linear and non-periodical components. METHODS: Analysis was performed in 7 recently heart transplanted patients and in 7 controls of similar age whose HRV signal was collected during 24 h. Parameters that quantify non-linear dynamic behaviour, in a time series, were calculated. We first assessed the specific non-linear nature of the time series by a test on surrogate data after Fourier phase randomization. Furthermore, the D2 correlation dimension, K2 Kolmogorov entropy, and H self-similarity exponent of the signal were estimated. From this last parameter, the dimension D = 1/H can be obtained. In order to assess whether the dynamics of the system are compatible with chaotic characteristics, the entire spectrum of Lyapunov exponents was calculated. We used return maps to graphically represent the non-linear and non-periodical behaviours in patients and controls. RESULTS: Surrogate data suggest that the HRV time courses have unique non-linear characteristics. D2, K2 and 1/H parameters were significantly lower in transplanted subjects than in controls. Positivity of the first Lyapunov exponent indicates divergence of trajectories in state-space. Furthermore, the display of return maps on projections obtained after Singular Value Decomposition, especially in low-complexity data (as in transplanted patients), shows a structure which is suggestive of a strange attractor. These findings support the hypothesis that chaotic dynamics underlie HRV. CONCLUSION: These results indicate that non-linear dynamics are likely to be present in HRV control mechanisms, giving rise to complex and qualitatively different behaviours. System complexity decreases in transplanted patients and this may be related to loss of the neural modulation of heart rate.

Adult↗