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Biomedical subjects

M G Signorini

Publications and source records attributed to M G Signorini.

12 recordsLinked to original sources
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↗
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

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

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

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↗
PubMed1994

Autonomic changes during hypnosis: a heart rate variability power spectrum analysis as a marker of sympatho-vagal balance.

Spectral analysis of beat-to-beat variability in electrocardiography is a simple, noninvasive method to analyze sympatho-vagal interaction. The electrocardiogram is analyzed by means of an automatic, autoregressive modeling algorithm that provides a quantitative estimate of R-R interval variability by the computation of power spectral density. Two major peaks are recognizable in this specter: a low-frequency peak (LF, -0.1 Hz), related to the overall autonomic activity (ortho+parasympathetic) and a high-frequency peak (HF, -0.25 Hz), representative of the vagal activity. The LF/HF ratio is an index of the sympatho-vagal interaction. This technique was applied, using a computer-assisted electrocardiograph, to 10 healthy volunteers (6 high and 4 low hypnotizable subjects as determined by the Stanford Hypnotic Susceptibility Scale, Form C) in randomized awake and neutral hypnosis conditions. Preliminary results indicated that hypnosis affects heart rate variability, shifting the balance of the sympatho-vagal interaction toward an enhanced parasympathetic activity, concomitant with a reduction of the sympathetic tone. A positive correlation between hypnotic susceptibility and autonomic responsiveness during hypnosis was also found, with high hypnotizable subjects showing a trend toward a greater increase of vagal efferent activity than did low hypnotizables.

Adult↗
PubMed1994

Can power spectral analysis of heart rate variability identify a high risk subgroup of congestive heart failure patients with excessive sympathetic activation? A pilot study before and after heart transplantation.

BACKGROUND AND OBJECTIVES: Autonomic dysfunction seems to be involved in the progression and prognosis of severe congestive heart failure. Parasympathetic activity can still be abnormal 4-8 weeks after haemodynamic improvement by heart transplantation. To identify patients in heart failure with a more pronounced neural derangement and to analyse the changes in sympathetic and parasympathetic activity soon after heart transplantation, spectral indices of heart rate variability were assessed in 30 patients in severe heart failure and in 13 patients after heart transplantation; a group of 15 age-matched subjects served as controls. METHODS AND RESULTS: Heart rate variability was assessed by standard electrocardiography (ECG) in patients in heart failure and by oesophageal ECG in patients after heart transplantation. Compared with controls, the mean RR interval and total power were reduced in heart failure. The 30 patients showed two different patterns of heart rate variability: in 14 no power was detected in the low frequency band (0.03-0.15 Hz) (LF) and total power was mainly concentrated in the high frequency band (0.15-0.45 Hz) (HF), whereas in the remaining 16 patients power in the LF band was increased and power in HF band was reduced compared with the controls. Patients with undetectable LF had a lower mean RR interval and total power (745(25) v 864(36) ms, p < 0.05; 118(16) v 902(202) ms2, p < 0.001), higher concentration of plasma noradrenaline (635(75) v 329(54) pg/ml, p < 0.05), and worse clinical status and prognosis (4 deaths v no deaths at 6 month follow up) than patients with a dominant LF band. In the post-transplant patients both the mean PP interval of the remnant atrium and total power resembled results in the patients with heart failure; in 7 of the 13 post-transplant patients no power was detectable in the LF band: when both HF and LF power were present the results resembled those in the 16 patients in heart failure. CONCLUSIONS: These data suggest that in more advanced stages of congestive heart failure, power spectral analysis of heart rate variability allows identification of a subgroup of patients with higher sympathetic activation and poorer clinical status who are at major risk of adverse events. In the short term after cardiac transplantation the spectral profile of the rhythm variability of the remnant atrium was not improved, suggesting that parasympathetic withdrawal and sympathetic hyperactivity persist, despite the restoration of ventricular function.

Echocardiography, Transesophageal↗
PubMed1994

Non-linear dynamics of cardiovascular variability signals.

Long-term regulation of beat-to-beat variability involves several different kinds of controls. A linear approach performed by parametric models enhances the short-term regulation of the autonomic nervous system. Some non-linear long-term regulation can be assessed by the chaotic deterministic approach applied to the beat-to-beat variability of the discrete RR-interval series, extracted from the ECG. For chaotic deterministic systems, trajectories of the state vector describe a strange attractor characterized by a fractal of dimension D. Signals are supposed to be generated by a deterministic and finite dimensional but non-linear dynamic system with trajectories in a multi-dimensional space-state. We estimated the fractal dimension through the Grassberger and Procaccia algorithm and Self-Similarity approaches of the 24-h heart-rate variability (HRV) signal in different physiological and pathological conditions such as severe heat failure, or after heart transplantation. State-space representations through Return Maps are also obtained. Differences between physiological and pathological cases have been assessed and generally a decrease in the system complexity is correlated to pathological conditions.

Algorithms↗
PubMed1993

Power spectrum analysis of the fetal heart rate during noradrenaline infusion and acute hypoxemia in the chronic fetal lamb preparation.

In a chronically instrumented fetal lamb the effect on heart rate variability of noradrenaline as well as hypoxemia is studied by the use of power spectral analysis. Subsequent to both noradrenaline infusion and hypoxemia the very low frequency components of the variability are markedly decreased as compared with control conditions. After hypoxemia also a high frequency peak appears in the spectrum.

Acute Disease↗
PubMed1993

Time-variant power spectrum analysis for the detection of transient episodes in HRV signal.

A time-variant algorithm of autoregressive (AR) identification is introduced and applied to the heart rate variability (HRV) signal. The power spectrum is calculated from the AR coefficients derived from each single RR interval considered. Time-variant AR coefficients are determined through adaptive parametric identification with a forgetting factor which obtains weighed values on a running temporal window of 50 preceding measurements. Power spectrum density (PSD) is hence obtained at each cardiac cycle, making it possible to follow the dynamics of the spectral parameters on a beat-by-beat basis. These parameters are mainly the LF (low frequency) and the HF (high frequency) powers, and their ratio LF/HF. These together account for the balanced sympatho-vagal control mechanism affecting the heart rate. This method is applied to subjects suffering from transient ischemic attacks. The time variant spectral parameters suggest an early activation of LF component in the HRV power spectrum. It precedes by approximately 1.5-2 min the tachycardia and the ST displacement, generally indicative of the onset of an ischemic episode. The results suggest an arousal of sympathetic system before the acute attack.

Algorithms↗
PubMed1989

Spectral analysis of antepartum heart rate variability.

The present paper illustrates the basic methodological aspects of the power spectral analysis applied to fetal ECG starting from a gestational age around the 25th week of gestation until term. An abdominal ECG signal is recorded and fetal and maternal QRSs are recognised through selective digital filtering and averaging techniques. Power Spectral Density (PSD) of the discrete R-R series is then calculated through an autoregressive (AR) technique. In analogy with what happens in adult human subjects, fetuses manifest variability in correspondence to particular bands in the spectrum which are sensitive to the sympatho-vagal balance which controls many cardiovascular functions and respiration in different physiological conditions. Such a method is easily implemented on a personal computer and may be used to asses the development of the autonomic nervous system in fetuses as well as to show the physiopathological reasons which perturbate the relevant control mechanisms.

Cardiotocography↗