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Biomedical subjects

S Cerutti

Publications and source records attributed to S Cerutti.

At least 19 recordsLinked to original sources
PubMed1998

Cardiac autonomic patterns preceding occasional vasovagal reactions in healthy humans.

BACKGROUND: The wide range of clinical presentation of orthostatic vasovagal syncope suggests different underlying changes in the cardiac autonomic modulation. METHODS AND RESULTS: To evaluate the beat-by-beat modifications in the neural control of heart period preceding a syncopal event, we studied RR interval variability in 22 healthy subjects who experienced fainting for the first time during a 90 degrees head-up tilt and in 22 control subjects by means of time-variant power spectral analysis. Sympathetic and vagal modulations to the sinoatrial node were assessed by the normalized power of the low-frequency (LF, approximately 0.1-Hz) and high-frequency (HF, approximately 0.25-Hz) oscillatory components of RR variability. When the patients were supine, no differences were observed in the hemodynamic and spectral parameters of the 2 groups. During the tilt procedure, RR, LFNU, and HFNU (NU=normalized units) values were relatively stable in control subjects. During early tilt (T1), subjects with syncope had reduced RR intervals compared with control subjects. In 13 subjects with syncope, RR decreased while LFNU and LF/HF increased in the last minute of tilt before syncope (T2). Conversely, in the remaining 9 fainters, LFNU and LF/HF decreased from T1 to T2 and HFNU increased slightly. CONCLUSIONS: Two different patterns may be recognized in the cardiac autonomic changes preceding an occasional vasovagal event, namely, one characterized by a progressive increase of the marker of cardiac sympathetic modulation up to the onset of syncope, the other by a sympathetic inhibition with an impending vagal predominance. The recognition of different pathophysiological mechanisms in fainters may have important therapeutic implications.

Adolescent↗
PubMed1998

Quantifying electrocardiogram RT-RR variability interactions.

A dynamic linear parametric model is designed to quantify the dependence of ventricular repolarisation duration variability on heart period changes and other immeasurable factors. The model analyses the beat-to-beat series of the RR duration and of the interval between R- and T-wave apexes (RT period). Directly from these two signals, a parametric identification procedure and spectral decomposition techniques allow RT variability to be divided into RR-related and RR-unrelated parts and allow the RT-RR transfer function to be calculated. RT variability is driven by RR changes at low frequency (LF, around 0.1 Hz) and high frequency (HF, at the respiratory rate), whereas, at very low frequencies, the RR-unrelated contribution to the total RT variability is remarkable. During tilt at LF the RR-related RT percentage power increases (p < 0.02), the RR-unrelated RT percentage power remains unchanged, the gain of the RT-RR relationship largely increases (p < 0.001), and the phase is not significantly modified. Both the RR-related and the RR-unrelated RT percentage powers at LF are not affected by controlled respiration, and an increase in the RT-RR gain at HF is observed (p < 0.02). The proposed analysis may help to describe the regulation of the ventricular repolarisation process and to extract indexes quantifying the coupling between heart period and ventricular repolarisation interval changes.

Electrocardiography↗
PubMed1998

Performance assessment of standard algorithms for dynamic R-T interval measurement: comparison between R-Tapex and R-T(end) approach.

Three automatic approaches to ventricular repolarisation duration measurement (R-Tapex, R-T(end threshold) and R-T(end fitting) methods) are compared on computer-generated and real ECG signals, in relation to their reliability in the presence of the most common electrocardiographic artefacts (i.e. additive broadband noise and additive and multiplicative periodical disturbances). Simulations permit the evaluation of the amount of R-T beat-to-beat variability induced by the artefacts. The R-T(end threshold) method performs better than the R-T(end fitting) one, and, hence, the latter should be used with caution when R-T(end) variability is addressed. Whereas the R-Tapex method is more robust with regard to broadband noise than the R-T(end threshold) one, the reverse situation is observed in the presence of periodical amplitude modulations. A high level of broadband noise dose not prevent the detection of the central frequency of underlying R-T periodical changes. Comparison between the power spectra of the beat-to-beat R-T variability series obtained from three orthogonal ECG leads (X,Y,Z) is used to assess the amount of real and artefactual variability in 13 normal subjects at rest. The R-Tapex series displays rhythms at high frequency (HF) with a percentage power on the Z lead (57.1 +/- 4.9) greater than that on the X and Y leads (41.9 +/- 4.6 and 46.1 +/- 4.9, respectively), probably because of respiratory-related artefacts affecting the Z lead more remarkably. More uniform HF power distributions over X,Y,Z leads are observed in the R-T(end threshold) series (31.8 +/- 3.8, 39.2 +/- 4.1 and 35.1 +/- 4.2, respectively), thus suggesting minor sensitivity of the R-T(end threshold) measure to respiratory-related artefacts.

Algorithms↗
PubMed1998

Measuring regularity by means of a corrected conditional entropy in sympathetic outflow.

A new method for measuring the regularity of a process over short data sequences is reported. This method is based on the definition of a new function (the corrected conditional entropy) and on the extraction of its minimum. This value is taken as an index in the information domain quantifying the regularity of the process. The corrected conditional entropy is designed to decrease in relation to the regularity of the process (like other estimates of the entropy rate), but it is able to increase when no robust statistic can be performed as a result of a limited amount of available samples. As a consequence of the minimisation procedure, the proposed index is obtained without an a-priori definition of the pattern length (i.e. of the embedding dimension of the reconstructed phase space). The method is validated on simulations and applied to beat-to-beat sequences of the sympathetic discharge obtained from decerebrate artificially ventilated cats. At control, regular, both quasiperiodic and periodic (locked to ventilation) dynamics are observed. During the sympathetic activation induced by inferior vena cava occlusion, the presence of phase-locked patterns and the increase in regularity of the sympathetic discharge evidence an augmented coupling between the sympathetic discharge and ventilation. The reduction of complexity of the neural control obtained by spinalization decreases the regularity in the sympathetic outflow, thus pointing to a weaker coupling between the sympathetic discharge and ventilation.

Animals↗
PubMed1998

Respiratory sinus arrhythmia and cardiovascular neural regulation in athletes.

Studies using spectral analysis of cardiovascular variability as a noninvasive means for assessing autonomic nervous system activity have provided controversial results in athletes. One reason is that a slow breathing rate--a common feature in athletes--affects spectral estimation because it causes the low-frequency (LF) and high-frequency (HF) components to overlap. Low-frequency power increases during sympathetic activation; high-frequency corresponds to respiratory sinus arrhythmia. In this study, to assess how controlled respiration influences autonomic nervous system activity, we determined the effect of controlled and uncontrolled breathing conditions on cardiovascular variability. Our aim was to identify a standard respiratory rate for spectral estimation of cardiovascular neural control in athletes. During electrocardiographic recordings, subjects lay supine and breathed at their spontaneous frequency and at rates of 15, 12, and 10 to 14 (random) breaths x min(-1). Uncontrolled and random breathing rates significantly altered spectral sympathetic indices; conversely, 15 and 12 breaths x min(-1) redistributed respiratory related power through the HF, thus yielding correct LF power estimation. None of the breathing conditions significantly changed mean heart rate, arterial blood pressure, or spectral total power of cardiovascular variability. In conclusion, when power spectral analysis is used for assessing autonomic activity in athletes, respiration should be standardized at 15 breaths x min(-1). Controlled respiration at this rate leaves autonomic nervous system activity unchanged.

Adolescent↗
PubMed1998

Assessment of the coupling between RTapex and RR interval as an index of temporal dispersion of ventricular repolarization.

To evaluate the dynamic characteristics of the relationship between the RT and RR intervals we analyzed the RR/RTapex variability interaction with a dynamic parametric model whose parameters can be directly estimated from the beat-to-beat series RR and RTapex intervals. The model is designed to separate the fraction of RTapex variability driven by RR changes from that independent of RR variations and to quantify the gain and phase of the relationship between RR and RTapex intervals. The percentage of RTapex variability driven by RR variability was significantly greater in young normal subjects in comparison with postmyocardial infarction patients as well as with age-matched control subjects. This new approach based on the quantification of the RTapex variability dependent and independent of beat-to-beat RR interval changes could be used to quantify the degree of uncoupling between the two signals thus providing a new and noninvasive index of temporal dispersion of ventricular repolarization.

Adult↗
PubMed1997

Individual recognition by heart rate variability of two different autonomic profiles related to posture.

BACKGROUND: Power spectrum analysis of heart rate variability (HRV) can estimate the state of sympathovagal balance modulating sinus node activity. In view of the large distribution of spectral variables, a recognition of well-defined physiological conditions has never been attempted on an individual basis. METHODS AND RESULTS: We considered 10 spectral variables extracted from short segments (200 to 500 cardiac cycles) of 350 ECG tracings recorded in normal subjects in both supine and upright positions (700 patterns). The tracings were first ordered consecutively and subsequently assigned alternatively to a training or to a test set (each consisting of 175 cases, providing 350 patterns considered to be independent). A forecasting linear method estimated a normalized activation index (ranging from -1 for supine to +1 for upright) that concentrated the information derived from spectral variables and that identified, in the test set, individual by individual, approximately 84% of corresponding body postures. CONCLUSIONS: The combined use of spectral methodology and forecasting analysis has revealed an information content embedded, per se, in a short series of RR intervals capable of recognizing, individual by individual, two different autonomic profiles related to posture.

Adolescent↗
PubMed1997

Matching a computerized brain atlas to multimodal medical images.

A method for matching a digital brain anatomical atlas to multimodal medical images (MRI, PET, and SPET) was implemented. The digital atlas was derived from anatomical templates of the brain, cut according to the orbitomeatal orientation. The atlas consists of a set of contiguous slices schematically describing the brain as anatomical contours and of a set of regions of interest (ROIs) classifying the brain into functionally homogeneous areas. The matching procedure includes (a) an edge detection method for the extraction of anatomical contours and (b) a warping algorithm based on contour matching to fit the atlas to the individual brain anatomy, as described by MRI. Once the atlas is matched to MRI, the associated templates of ROI can be overlapped with functional PET/SPET studies, individually registered to MRI. The method was tested on MRI studies. The efficacy of the warping algorithm in overlapping atlas and MRI contours was assessed by calculating for each slice an index representing the extent of overlapping (I). Values of I in the range 0.8-0.9 were found (I = 1 complete overlapping). Local accuracy was also verified by comparing the position of correspondent anatomical ROI in the atlas and MRI images before and after warping. The atlas-matching procedure was applied to representative MRI/PET clinical images for an objective regional analysis of functional data.

Algorithms↗
PubMed1997

Total and partial coherence analysis of spontaneous and evoked EEG by means of multi-variable autoregressive processing.

The joint use of total and partial coherence between pairs of EEGs simultaneously recorded in a standard set, is shown to enhance what is caused by direct correlation between cortical subsystems and what is instead related to the spread of the electromagnetic field. A multi-variable autoregressive approach is employed in the computation, giving results even for a very short time window, thus allowing coherence to be investigated at the main cortical latencies of evoked potentials. In particular, when a combined visual and somatosensory stimulation is applied, cortical interactions are captured in the frequency domain.

Adult↗
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↗