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Biomedical subjects

G Baselli

Publications and source records attributed to G Baselli.

At least 19 recordsLinked to original sources

RR-arterial pressure variability relationships.

Methodological aspects of a causal black-box model of heart period/arterial pressure interaction, arterial pressure closed-loop regulation and respiration effects on both heart period and arterial pressure are revisited in the "time" (more exactly heart beat count) domain. Parameters are estimated from experimental data (model identification) by means of multiple linear regressions of actual samples over the past ones. The elements composing either heart period or systolic arterial pressure variability are visualised as beat-by-beat series. Indexes describing the signal interactions, the loop properties and the spectral components of the variability series are consequently summarised. In 17 normal young volunteers, the analysis was carried out during active standing, rest, mild clinostatic pedalling exercise at 10%, 20%, and 30% of the maximum effort, and recovery. A negative effect of heart period changes on systolic arterial pressure of - 13.3 mm Hg/s was found at rest. This effect, though augmented by exercise, appeared insignificant in explaining arterial pressure variability. Arterial baroreflex was assessed by alphaart index which had a value of 5.18 mm Hg/ms at rest, 3.78 mm Hg/ms during active standing, and decreased progressively with exercise down to 0.55 mmHg/ms. The pressure regulation loop displayed a tendency to amplify disturbances at low frequency (around 0.1 Hz) 5.94 times at rest, augmented to 8.88 times during standing, 7.55 at 30% exercise. The first parameter of the pressure auto-regression was slightly higher than 1 at rest and even more augmented during standing, thus, indicating a tendency of arterial pressure perturbations to persist from one beat to the next. These mechanisms appear important in the genesis of low-frequency pressure waves. Nonetheless, the trace of different sources was evident in the regression residuals. Noticeably, during exercise it explained 10.16% of total heart period variability compared to 12.49% related to the low-frequency oscillations of closed-loops. The origin of high-frequency waves synchronous with respiration appeared miscellaneous as well. Arterial pressure appeared negligibly affected by heart period changes. Conversely, a limited effect of arterial pressure waves was found on heart period superimposed to a large effect of cardiopulmonary reflexes directly modulating the sinus node. In conclusion, both high-frequency and low-frequency waves are composite phenomena and a multi-channel analysis comparing heart period and arterial pressure variability yields a variety of figures assessing cardiovascular regulation and cardiorespiratory coupling.

Adult↗

Assessment of inertial and gravitational inputs to the vestibular system.

A new device for the assessment of instantaneous angular and linear accelerations of the head is presented, which is based on four linear tri-axial accelerometers suitably attached to the head by an helmet. A procedure for reproducible helmet placement and calibration is given. A method is also illustrated to work out the different linear accelerations sensed by the vestibular organs in the left and right labyrinths and the components of the angular acceleration sensed by their semicircular canals. The computation is based on few individual parameters describing the helmet position with respect to external landmarks and on the average internal position and orientation of the vestibula. The purpose is to study the components of internal inertial forces, which represent the primary inputs to the vestibular system devoted to equilibrium and oculomotor control. The system is designed to be of easy application during rehabilitation exercises and in clinical environment during diagnostic and therapeutic manoeuvres. The prototype is tested with simple free movements such as "yes", "no", and gait.

Acceleration↗

Information domain analysis of cardiovascular variability signals: evaluation of regularity, synchronisation and co-ordination.

A unifying general approach to measure regularity, synchronisation and co-ordination is proposed. This approach is based on conditional entropy and is specifically designed to deal with a small amount of data (a few hundred samples). Quantitative and reliable indexes of regularity, synchronisation and co-ordination (ranging from 0 to 1) are derived in a domain (i.e. the information domain) different from time and frequency domains. The method is applied to evaluate regularity, synchronisation and co-ordination among cardiovascular beat-to-beat variability signals during sympathetic activation induced by head-up tilt (T), during the perturbing action produced by controlled respiration at 10, 15 and 20 breaths/min (CR10, CR15 and CR20), and after peripheral muscarinic blockade provoked by the administration of low and high doses of atropine (LD and HD). It is found that: (1) regularity of the RR interval series is around 0.209; (2) this increases during T, CR10 and HD; (3) the systolic arterial pressure (SAP) series is more regular (0.406) and its regularity is not affected by the specified experimental conditions; (4) the muscle sympathetic (MS) series is a complex signal (0.093) and its regularity is not influenced by HD and LD; (5) the RR interval and SAP series are significantly, though weakly, synchronised (0.093) and their coupling increases during T, CR10 and CR15; (6) the RR interval and respiration are coupled (0.152) and their coupling increases during CR10; (7) SAP and respiration are significantly synchronised (0.108) and synchronisation increases during CR10; (8) MS and respiration are uncoupled and become coupled (0.119) after HD; (9) the RR interval, SAP and respiration are significantly co-ordinated (0.118) and co-ordination increases during CR10 and CR15; (10) during HD the co-ordination among SAP, MS and the respiratory signal is larger than that among the RR interval, SAP, MS and the respiratory signal, thus indicating that the RR interval contributes towards reducing co-ordination.

Atropine↗

Evaluation of respiratory influences on left ventricular function parameters extracted from echocardiographic acoustic quantification.

This study was designed to assess, using the echocardiographic acoustic quantification technique, the influence of respiration on left ventricular (LV) function and its modifications connected with the ageing process, quantifying in a non-invasive way the respiratory contribution to the LV volume variability. An automated algorithm is applied to extract the beat-to-beat measurements of LV function parameters from the LV volume signal, obtained from recordings lasting a few minutes. Mean values, amount of variability and spectral content were studied in a population of 17 normal young (mean age 25 +/- 1 years) and 12 normal old (mean age 64 +/- 2 years) subjects. Mean values of the beat-to-beat measurements of LV function parameters were able to point out alterations connected with the ageing process in peak filling rate, peak atrial filling rate and peak ejection rate. Spectral analysis, applied to the extracted variability series, displayed a predominance of the high-frequency (HF) component corresponding to respiration in all LV function parameters; moreover, age related changes of HF variability were observed in peak ejection rate. The HF power spectrum component of beat to beat series extracted from the LV signal can provide a non-invasive assessment of the fluctuations in ventricular parameters associated with respiration.

Adult↗

Assessment of arterial and cardiopulmonary baroreflex gains from simultaneous recordings of spontaneous cardiovascular and respiratory variability.

OBJECTIVES: In usual models of cardiovascular regulation, arterial pressure drives RR interval through a simple baroreflex, and the influence of respiration is dismissed. We examined the applicability of a trivariate autoregressive model to obtain separate values of the gain of the arterial and non-arterial, i.e. cardiopulmonary, components of the lumped baroreflex, employing spontaneous RR interval, systolic arterial pressure and respiration variability. DESIGN: We studied 30 normal subjects (age 37 +/- 1 years), both at rest and during standing, a condition known to enhance sympathetic activity while reducing venous return. Electrocardiogram was obtained by telemetry, arterial pressure by Finapres and respiration with a piezoelectric respiratory belt Data were acquired with a PC and processed with an ad hoc Windows program. METHODS: We employed an additive and a linear multivariate approach to approximate overall gain of the arterial pressure-heart beat period baroreflex (alphalumped) and of its arterial (alphaart) and non-arterial, i.e. cardiopulmonary (alphacp), components, from continuous beat-by-beat series of RR interval, systolic arterial pressure variability and respiration, without using any non-physiological intervention. RESULTS: The overall baroreflex gain at rest (alphalumped = 23.7 +/- 3.4 ms/mmHg) was subdivided into arterial (alphaart = 5.2 +/- 1.0 ms/mmHg) and cardiopulmonary (alphacp = 18.5 +/- 3.2ms/mmHg) components. During active orthostatism, alphaluumped was diminished to 10.0 +/- 2.2 ms/ mmHg. In addition, standing selectively reduced alphacp to 4.8 +/- 1.3 ms/mmHg, while alphaart was not significantly changed. CONCLUSIONS: A trivariate autoregressive model, that considers explicitly the influence of respiration, can subdivide overall, lumped, arterial pressure-heart period baroreflex gain, into two separate components, alphaart and alphacp. Only the latter is reduced by active orthostatism.

Adult↗

Prediction of short cardiovascular variability signals based on conditional distribution.

A new approach measuring the predictability of a process is proposed. The predictor is defined as the median of the distribution conditioned by a sequence of L - 1 previous samples (i.e., a pattern). A function referred to as the corrected mean squared predictor error is defined to prevent the perfect adequacy to the data (i.e., the decrease to zero of the prediction error), thus avoiding to divide the whole set of data in learning and test sets. This function exhibits a minimum and this minimum is taken as a measure of predictability of the series. The use of the minimization procedure avoids to fix a priori the pattern length L. This approach permits one a reliable measure of predictability on short data sequences (around 300 samples). Moreover, this method, in connection with a surrogate data approach, is useful to detect nonlinear dynamics. The analysis indicates that, in simulated and real data, predictability and nonlinearity measures provide different information. The application of this approach to the analysis of cardiovascular variability series of the heart period (RR interval) and systolic arterial pressure (SAP) shows: 1) SAP series is more predictable than RR interval series; 2) predictability of the RR interval series is larger during tilt, during controlled respiration at 10 breaths/min (bpm) and after high-dose administration of atropine; 3) SAP series is dominated by linear correlation; 4) RR interval series exhibits nonlinear dynamics during controlled respiration at 10 bpm and after low-dose administration of atropine, while it is linear during sympathetic activation produced by tilt and after peripheral parasympathetic blockade caused by high-dose administration of atropine.

Adult↗

Assessing baroreflex gain from spontaneous variability in conscious dogs: role of causality and respiration.

A double exogenous autoregressive (XXAR) causal parametric model was used to estimate the baroreflex gain (alpha(XXAR)) from spontaneous R-R interval and systolic arterial pressure (SAP) variabilities in conscious dogs. This model takes into account 1) effects of current and past SAP variations on the R-R interval (i.e., baroreflex-mediated influences), 2) specific perturbations affecting R-R interval independently of baroreflex circuit (e.g., rhythmic neural inputs modulating R-R interval independently of SAP at frequencies slower than respiration), and 3) influences of respiration-related sources acting independently of baroreflex pathway (e.g., rhythmic neural inputs modulating R-R interval independently of SAP at respiratory rate, including the effect of stimulation of low-pressure receptors). Under control conditions, alpha(XXAR) = 14.7 +/- 7.2 ms/mmHg. It decreases after nitroglycerine infusion and coronary artery occlusion, even though the decrease is significant only after nitroglycerine, and it is completely abolished by total arterial baroreceptor denervation. Moreover, alpha(XXAR) is comparable to or significantly smaller than (depending on the experimental condition) the baroreflex gains derived from sequence, power spectrum [at low frequency (LF) and high frequency (HF)], and cross-spectrum (at LF and HF) analyses and from less complex causal parametric models, thus demonstrating that simpler estimates may be biased by the contemporaneous presence of regulatory mechanisms other than baroreflex mechanisms.

Animals↗

Conditional entropy approach for the evaluation of the coupling strength.

A method that enables measurement of the degree of coupling between two signals is presented. The method is based on the definition of an uncoupling function calculating, by means of entropy rates, the minimum amount of independent information (i.e. the information carried by one signal which cannot be derived from the other). An estimator of the uncoupling function able to deal with short segments of data (a few hundred samples) is proposed, thus enabling the method to be used for usual experimental recordings. A synchronisation index is derived from the estimate of the uncoupling function by means of a minimisation procedure. It quantifies the maximum amount of information exchanged between the two signals. Simulations in which non-linear coordination schemes are produced and changes in the coupling strength are artificially induced are used to check the ability of the proposed index to measure the degree of synchronisation between signals. The synchronisation analysis is utilised to measure the coupling strength between the beat-to-beat variability of the sympathetic discharge and ventilation in decerebrate artificially ventilated cats and the degree of synchronisation between the beat-to-beat variability of the heart period and ventricular repolarisation interval in normal subjects and myocardial infarction patients. The sympathetic discharge and ventilation are strongly coupled and the coupling strength is not affected by manoeuvres capable of increasing or depressing sympathetic activity. The synchronisation is lost after spinalisation. The synchronisation analysis confirms that the heart period and ventricular repolarisation interval are well coordinated. In normal subjects, the synchronisation index is not modified by experimental conditions inducing changes in the sympathovagal balance. On the contrary, it strongly decreases after myocardial infarction, thus detecting and measuring the uncoupling between the heart period and ventricular repolarisation interval.

Animals↗

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↗

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↗

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↗

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↗

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↗

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↗

Linear multivariate models for physiological signal analysis: theory.

The general linear parametric multivariate modelling concept is presented. This model combines a variety of different kinds of multivariate linear models. The concept of partial spectral analysis is derived from the general model. Some emphasis is laid on the causality demands of the model, and it is shown that the classic strictly-causal structure must be abandoned in order to utilise the modelling in many practical situations. Two special sub-class models are described in detail: the multivariate autoregressive model and the multivariate dynamic adjustment model. Furthermore, time-varying modelling is considered. The modelling of the real system is presented on a general level as a system identification cycle. The application of the methods to real physiological data is presented in the companion paper.

Data Collection↗

Linear multivariate models for physiological signal analysis: applications.

Some applications of linear multivariate modelling methods in the analysis of physiological signals are presented. These applications illustrate the methods in the analysis of cardiovascular dynamics, which has been one of the main application fields of the multivariate modelling during the last ten years. It is demonstrated that physiologically meaningful information about the causal interactions in the cardiovascular system can be drawn from the routinely available clinical signals. Both static and dynamic conditions are considered.

Humans↗

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↗