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Biomedical subjects

G Baselli

Publications and source records attributed to G Baselli.

At least 37 records · Page 2Linked to original sources
PubMed1993

Power spectrum analysis of cardiovascular variability monitored by telemetry in conscious unrestrained rats.

Beat-to-beat variability of arterial pressure and heart period (R-R) was studied in eight conscious freely-moving adult male rats in which telemetric recordings of arterial pressure, ECG and respiratory movements were obtained under unrestrained and unstressed conditions. The beat-to-beat time series of these signals (systolic arterial pressure, diastolic arterial pressure and R-R) were analyzed, in the frequency domain, using autoregressive spectral analysis in order to detect and quantify the rhythmic components. In basal conditions, the systolic arterial pressure variability spectrum was characterized by three major spectral components which had central frequencies respectively of 0.08 +/- 0.03 Hz (very low frequency), 0.43 +/- 0.02 Hz (low frequency) and 1.36 +/- 0.19 Hz (high frequency). Similar rhythmic components were found in R-R signal variability. The very low frequency component included a higher percentage of total power in R-R variability spectrum (75.3%) than in systolic arterial pressure variability spectrum (58.4%). The low frequency component was more pronounced in both systolic and diastolic arterial pressure variability spectra. The high frequency component of R-R, systolic and diastolic arterial pressure was synchronous with respiration. Cross-spectral analysis revealed a high statistical coherence between R-R and arterial pressure variabilities in all the three frequency bands. An alpha-adrenergic blocker (phentolamine) specifically abolished the low frequency components of systolic and diastolic arterial pressure variability spectra, thus suggesting that low frequency is a marker of sympathetic modulation of vasomotor activity. The low frequency component of R-R variability spectrum was also markedly blunted. We suggest that cardiovascular variability signals, (R-R, systolic and diastolic arterial pressure) are composed almost of two main rhythms linked to respiration and vasomotor activity. These rhythms can be quantified in conscious unrestrained rats by using telemetry and spectral analysis. This approach seems to offer a new powerful tool for pharmacological studies in conscious small animals.

Animals↗
PubMed1992

Spectral analysis of sympathetic discharge, R-R interval and systolic arterial pressure in decerebrate cats.

In 19 decerebrate and artificially ventilated cats, we analyzed, with a power spectral methodology, the variability simultaneously present in R-R interval and in thoracic preganglionic sympathetic outflow. R-R interval was characterized, as already described in humans and other experimental preparations, by two rhythmic components occurring at a frequency of about 0.1 Hz (low-frequency, LF) and at one corresponding to respiratory rate (high-frequency, HF) which, in these experiments, was set at 0.32 Hz. Two similar rhythmic components were also present in the sympathetic discharge. Arterial pressure changes were produced by aorta or vena cava flow obstruction in order to produce reflex responses in sympathetic activity. Reflex sympathetic excitations induced an increase in the LF component of both R-R interval and sympathetic discharge variabilities, while the HF components were simultaneously reduced. In contrast, reflex sympathetic inhibitions were accompanied by a decrease in LF components of both variability signals, while the HF components were simultaneously increased. A significant and positive correlation was found between changes in impulse activity and the amplitude of LF component of either R-R interval or sympathetic discharge variabilities. These data support the hypothesis that the low-frequency component of R-R variability can be used as a marker of sympathetic modulation.

Animals↗
PubMed1991

Signal averaging of pre- and post-extrasystolic beats in patients with ventricular arrhythmias.

To evaluate the effects of premature ventricular beats on the impulse conduction of adjacent sinus cycles, we compared the high amplification signal-averaged electrocardiogram parameters of the pre- and post-extrasystolic beats with those of the remaining sinus cycle. According to the duration of filtered QRS (fQRS), to the voltage of root mean square of the terminal 40 ms (RMS 40) and to the duration of low amplitude terminal components of the sinus cycles, ventricular late potentials were detected in nine out of 29 subjects. Patients with an abnormal signal-averaged electrocardiogram exhibited a longer fQRS (146 +/- 6 versus 116 +/- 2 ms), a reduced RMS40 voltage (18 +/- 2 versus 80 +/- 10 microV) and a prolonged duration of less than 40 microV components (42 +/- 4 versus 17 +/- 2 ms). Analysis of the pre-extrasystolic beats did not reveal any significant variation in the above parameters, showing a mean difference of 0.44 +/- 2.4 ms; 0.02 +/- 1.14 microV; 1 +/- 1.9 ms and of -1.45 +/- 1.02 ms; 3.5 +/- 8.6 microV; -0.7 +/- 0.84 ms respectively, for patients with and without ventricular late potentials. In addition, no significant variation was observed when the post-extrasystolic beats were considered. These results indicate that the sinus cycles adjacent to premature ventricular discharges do not present variations of signal-averaged electrocardiogram parameters that may suggest an influence of the ectopic beats on their intramyocardial impulse propagation.

Adult↗
PubMed1990

The influence of exercise intensity on the power spectrum of heart rate variability.

The power spectral analysis of R-R interval variability (RRV) has been estimated by means of an autoregressive method in seven sedentary males at rest, during steady-state cycle exercise at 21 percent maximal oxygen uptake (%VO2max), SEM 2%, 49% VO2max, SEM 2% and 70% VO2max, SEM 2% and during recovery. The RRV, i.e. the absolute power of the spectrum, decreased 10, 100 and 500 times in the three exercise intensities, returning to resting value during recovery. In the RRV power spectrum three components have been identified: (1) high frequency peak (HF), central frequency about 0.24 Hz at rest and recovery, and 0.28 Hz, SEM 0.02, 0.37 Hz, SEM 0.03 and 0.48 Hz, SEM 0.06 during the three exercise intensities, respectively; (2) low frequency peak (LF), central frequency about 0.1 Hz independent of the metabolic state; (3) very low frequency component (VLF), less than 0.05 Hz, no peak observed. The HF peak power, as a percentage of the total power (HF%), averaged 16%, SEM 5% at rest and did not change during exercise, whereas during recovery it decreased to 5%-10%. The LF% and VLF% were about 50% and 35% at rest and during low exercise intensity, respectively. At higher intensities, LF% decreased to 16% and VLF% increased to 70%. During recovery a return to resting values occurred. The HF component may reflect the increased respiratory rate and the LF peak changes the resetting of the baroreceptor reflex with exercise. The hypothesis is made that VLF fluctuations in heart rate might be partially mediated by the sympathetic system.

Adult↗
PubMed1990

Spectral analysis of sympathetic discharge in decerebrate cats.

To evaluate if the 0.1-Hz low-frequency oscillations of R-R interval are a reflection of rhythmical pattern of discharge of the sympathetic outflow, we analysed in 10 decerebrate cats heart rate and cardiac sympathetic efferent discharge variability. A predominant low-frequency component was present in both signals, thus suggesting that the 0.1-Hz rhythm indeed reflects a rhythmical pattern of discharge of sympathetic outflow.

Animals↗
PubMed1990

Sympathetic activation during treadmill exercise in the conscious dog: assessment with spectral analysis of heart period and systolic pressure variabilities.

We studied in seven conscious dogs the dynamic rearrangements in neural control of heart rate and left ventricular pressure during treadmill exercise as assessed by spectral analysis. The presence, at rest, of a major high-frequency component (HF), an indicator of vagal tone, was reverted during exercise to a major low-frequency component (LF), an indicator of sympathetic activation. These changes were blunted by chronic beta and alpha 1 adrenergic receptor blockade.

Animals↗
PubMed1990

Effects of tilt and exercise on signal-averaged electrocardiogram after acute myocardial infarction.

To determine whether enhanced sympathetic activity could alter a non-invasive index of cardiac instability, we analysed the effects of 90 degrees head-up tilt and submaximal exercise stress test on high amplification signal-averaged electrocardiogram in 64 patients after acute myocardial infarction. At rest, ventricular late potentials were detected in 25% of patients, characterized by a significant prolongation of filtered QRS complex (137 +/- 3 vs 115 +/- 2 ms) and of its components smaller than 40 microV (38 +/- 2 vs 16 +/- 1 ms), as well as by a reduced root mean square voltage calculated for the terminal 40 ms of QRS complex (RMS40 voltage) (19 +/- 1 vs 75 +/- 9 microV) in comparison to patients without micropotentials. Sympathetic activation induced by tilt caused a significant increase in heart rate (from 67 +/- 3 to 79 +/- 3 beats min-1) but did not modify either the incidence of ventricular late potentials or the values of any of the signal-averaged electrocardiogram parameters considered. In 19 patients, recordings were also obtained during a submaximal bicycle exercise stress test at a heart rate of 114 +/- 4 beats min-1 and with systolic arterial blood pressure at 153 +/- 6 mmHg. No effect on signal-averaged electrocardiogram parameters was detectable during this experimental intervention. These data indicate that after myocardial infarction, sympathetic activation does not seem to modify signal-averaged electrocardiogram parameters.

Electrocardiography↗
PubMed1990

Continuous 24-hour assessment of the neural regulation of systemic arterial pressure and RR variabilities in ambulant subjects.

In this study, we tested the hypothesis that the neural control of circulation in humans undergoes continuous but in part predictable changes throughout the day and night. Dynamic 24-hour recordings were obtained in two groups of ambulant subjects. In 18 hospitalized patients free to move, direct high-fidelity arterial pressures and electrocardiograms were recorded, and in an additional 28 nonhospitalized subjects, only electrocardiograms were obtained. Spectral analysis of systolic arterial pressure and of RR interval variabilities provided quantitative markers of sympathetic and vagal control of the sinus node and of sympathetic modulation of vasomotor tone. With this approach, the low-frequency (approximately 0.1 Hz) component of RR interval and systolic arterial pressure variabilities is considered a marker primarily of sympathetic activity, whereas the high-frequency (approximately 0.25 Hz) component of RR interval variability, related to respiration, seems to be a marker primarily of vagal activity. We observed a pronounced and consistent reduction in the markers of sympathetic activity and an increase in those of vagal activity during the night. In the invasive studies, while the subjects were still lying in bed after waking up, the markers of sympathetic activity rose rapidly and concomitantly with a simultaneous vagal withdrawal. Noninvasive studies confirmed the early morning rise of the markers of sympathetic activity and the circadian pattern of sympathovagal balance. These data indicate that the ominously increased rate of cardiovascular events in the morning hours may reflect the sudden rise of sympathetic activity and the reduction of vagal tone.

Blood Pressure↗
PubMed1989

Compressed spectral arrays for the analysis of 24-hr heart rate variability signal: enhancement of parameters and data reduction.

Heart rate variability signal in the form of an R-R interval tachogram is detected in Holter type 24-hr ECG recordings. Spectral analysis is carried out over consecutive nonoverlapping records, and the information is displayed in the form of a compressed spectral array through parametric techniques. The trends of spectral parameters such as low-frequency (LF) and high-frequency (HF) powers and central frequencies are also plotted, together with the classical mean R-R value and variance relative to each single spectrum. These parameters quantify the effect of sympatho-vagal balance on heart rate control during the 24-hr period and provide important elements for the diagnostic evaluation of various pathologies, like hypertension. A spectral compression algorithm which checks the position of the poles relative to LF and HF bands inside the unitary circle in the complex zeta-plane is also developed. Applications of this procedure are foreseen in the clinical evaluation of ambulant patients as well as in the study of physical and psychological stress.

Algorithms↗
PubMed1988

Parameter extraction from heart rate and arterial blood pressure variability signals in dogs for the validation of a physiological model.

The paper describes an automatic procedure for improving the extraction of parameters in heart rate (HR) and arterial blood pressure (ABP) beat-to-beat variability signals. Auto- and cross-spectral analysis of such signals is carried out through parametric models and the distribution of the power of the spectra and the phase relationships are compared in various physiological situations induced in the dogs via drug infusion or surgical interventions which do influence the control mechanisms of HR and ABP. This "black-box" approach allows the obtention, directly from the processing of the above-mentioned signals, of the estimation of parameters relative to cardiovascular models, as the ones described by simple equations (Windkessel and Starling laws are introduced as examples). These parameters seem to validate significantly the capability of such models to describe the physiological interactions existing between the two considered signals. Applications may be foreseen both for research and clinical purposes.

Algorithms↗
PubMed1988

Changes in autonomic regulation induced by physical training in mild hypertension.

The adaptive effects of physical training on cardiovascular control mechanisms were studied in 11 subjects with mild hypertension. In these subjects we assessed the gain of the heart period-systolic arterial pressure relationship in the unfit and the fit state by using 1) an open loop approach, whereby the gain is expressed by the slope of the regression of heart period as a function of systolic arterial pressure, during a phenylephrine-induced pressure rise and 2) a closed loop approach with proper simplification, whereby the gain is expressed by the index alpha, obtained through simultaneous spectral analysis of the spontaneous variabilities of heart period and systolic arterial pressure. Both methods indicated that training significantly increased the gain of the relationship between heart period and systolic arterial pressure at rest and reduced arterial pressure and increased heart period significantly. This gain was drastically reduced during bicycle exercise both in the unfit and fit state. In a second group of normotensive (n = 7; systolic pressure, 133 +/- 3 mm Hg) and hypertensive (n = 7; systolic pressure, 180 +/- 10 mm Hg) subjects undergoing 24-hour diagnostic continuous electrocardiographic and high fidelity arterial pressure monitoring, the index alpha was significantly reduced in the hypertensive group at rest. Furthermore, when analyzed continuously over the entire 24-hour period, this index underwent minute-to-minute changes with lower values during the day and higher values during the night. We propose the index alpha as a quantitative indicator of the changes in the gain of baroreceptor mechanisms occurring with physical training in mild hypertension and during a 24-hour period in ambulatory subjects.

Adult↗
PubMed1988

Automatic assessment of the interaction between respiration and heart rate variability signal.

The present paper introduces an original method of processing heart rate variability (HRV) and respiration signals as detected respectively through chest electrodes and thoracic belt in dogs under different experimental conditions. Signals are processed as time series synchronous with the occurrence of QRS complexes on ECG signal and auto and cross spectra are accordingly calculated. Two particular bands appear mainly of interest on the spectrum of HRV signal: one in correspondence with the respiration rate and another one at a lower frequency value. Values of power at these frequency bands together with coherence and phase between HRV signal and respiration complete the parameters which try to quantify a few aspects of the complex dynamic relationships between the original signals. In particular, controlled respiration in dogs was studied through the connection with an automatic ventilator, as well as the effects of drugs which interact with the neural regulatory systems (i.e. sympathetic and parasympathetic nervous system). Gain and phase relationships between heart rate variability and respiration, obtained with spectral analysis, could be used to provide a better understanding of the neural control mechanisms linking heart rate and respiration in various experimental conditions. The method described in this study is to be used both in physiological and clinical research.

Animals↗
PubMed1987

Heart rate variability as an index of sympathovagal interaction after acute myocardial infarction.

By analysis of spectral components of heart rate variability, sympathovagal interaction was assessed in patients after acute myocardial infarction (AMI). At 2 weeks after AMI (n = 70), the low-frequency component was significantly greater (69 +/- 2 vs 53 +/- 3 normalized units [NU], p less than 0.05) and the high-frequency component was significantly smaller (17 +/- 1 vs 35 +/- 3 NU) than in 26 age-matched control subjects. This difference was likely to reflect an alteration of sympathovagal regulatory outflows with a predominance of sympathetic activity. At 6 (n = 33) and 12 (n = 29) months after AMI, a progressive decrease in the low- (62 +/- 2 and 54 +/- 3 NU) and an increase in the high-frequency (23 +/- 2 and 30 +/- 2 NU) spectral components was observed, which suggested a normalization of sympathovagal interaction. An increase in sympathetic efferent activity induced by tilt did not further modify the low-frequency spectral component (78 +/- 3 vs 74 +/- 3 NU) in a subgroup of 24 patients at 2 weeks after AMI. Instead, 1 year after AMI, this maneuver was accompanied by an increase in the low-frequency component (77 +/- 3 vs 53 +/- 3 NU, p less than 0.05) of a magnitude similar to the one observed in control subjects (78 +/- 3 vs 53 +/- 3 NU). These data indicate that the sympathetic predominance that is detectable 2 weeks after AMI is followed by recovery of vagal tone and a normalization of sympathovagal interaction, not only during resting conditions, but also in response to a sympathetic stimulus.

Adult↗
PubMed1987

Single sweep analysis of visual evoked potentials through a model of parametric identification.

An original method is presented for the single sweep analysis of visual evoked potentials (VEP's). The introduced algorithm bases upon an AutoRegressive with eXogenous input (ARX) modeling. A Least Squares procedure estimates the coefficients of the model and allows to obtain a complete black-box description of the signal generation mechanism, besides providing a filtered version of the single sweep potential. The performance of the algorithm is verified on proper simulation tests and the experimental results put into evidence the noticeable improvement of signal-to-noise ratio with a consequent better recognition of the classical parameters of the peaks (latencies and amplitudes). The possibility of measuring these parameters on a single sweep basis enables to evaluate the dynamics of the Central Nervous System response during the entire course of the examination. A classification of the estimated evoked potentials in a small number of subsets, on the basis of their morphology, is also possible.

Algorithms↗
PubMed1987

Heart rate variability signal processing: a quantitative approach as an aid to diagnosis in cardiovascular pathologies.

The heart rate variability (HRV) signal carries important information about the systems controlling heat rate and blood pressure, mainly elicited by autonomic nervous system (sympathetic and parasympathetic) controls. The present paper illustrates methods of HRV signal processing by using autoregressive (AR) modeling and power spectral density estimate. The information enhanced in this way seems to be particularly sensitive in discriminating various cardiovascular pathologies (hypertension, myocardial infarction, diabetic neuropathy, etc.). This method provides a simple non-invasive analysis, based on the processing of spontaneous oscillations in heart rate. Particular emphasis is directed to the algorithms used and to their direct application by using proper computerized techniques: only a few paradigmatical examples will be illustrated as preliminary results.

Cardiovascular Diseases↗