Causal relationship between heart rate and arterial blood pressure variability signals.
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Biomedical subjects
Publications and source records attributed to G Baselli.
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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.
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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.
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.
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.
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.
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.
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A parametric method for autoregressive (AR) auto- and cross-spectral analysis is presented for the contemporaneous processing of heart rate and arterial blood pressure variability signals. In particular, the introduced bivariate spectral analysis (phase and coherence spectra) provides quantitative and objective means which are useful to measure the role played by the neural controlling systems (sympathetic and parasympathetic systems) on the cardiovascular signals under different pathophysiological conditions. Algorithmic aspects, connected to the way of processing discrete numerical series synchronized to single cardiac beats, are particularly stressed. Important applications are foreseen both in physiological studies and in clinical practice as an aid to the detection of various relevant cardiovascular pathologies such as hypertension and diabetes.
A system providing high quality direct arterial blood pressure recordings and electrocardiograms in ambulatory patients was devised using a modified commercially available Holter type magnetic tape recorder together with a microminiature Millar (3F) tip transducer. This system did not require a perfusion line and solved the major drawbacks of other available systems. Pressure and electrocardiographic data were fed directly from the playback unit into a minicomputer for automatic beat to beat waveform analysis. Thus the blood pressure and RR interval variability signals could be simultaneously analysed with autoregressive modelling techniques to provide a quantitative estimate of sympathovagal balance in ambulant patients. The system was reliable, simple, and safe to use.
The present paper introduces an original method of digital signal processing for an automatic analysis of non-invasive abdominal ECG recordings on pregnant women starting from the 25th week of gestation. The procedure has been implemented on a DEC-VAX 750 digital computer at the Department of Electrical Engineering, Polytechnic of Milano and the signals are recorded at the Department of Obstetrics and Gynecology "L. Mangiagalli", University of Milano, Italy. The experimental results presented in here are still preliminary as only few cases have been considered up to now (about 20) and the goal of the paper is mainly focused on the algorithmic aspects of the whole procedure implemented in the computer and on the approach of heart rate variability (HRV) signal analysis both in the mother and in the fetus. Abdominal ECG lead processing is illustrated starting from the step of maternal (M) and fetal (F) QRS recognitions through linear digital filtering (derivative and low-pass FIR filter, Weber-Cappellini window) and weighted averaging techniques synchronized with maternal QRS's. Figure 1 a shows the original abdominal lead; figure 1 b the filtered signal for MQRS recognitions; figure 2 a the template of maternal cardiac cycle as obtained after the averaging operation synchronized with the instants of MQRS occurrence. The subtraction of the template results in the abdominal lead shown in figure 1 c in which the contribution of MECG is practically entirely reduced even in the case of MQRS and FQRS overlapping.(ABSTRACT TRUNCATED AT 250 WORDS)
We investigated the duration of fetal electrocardiographic events during normal pregnancies and during pregnancies with fetal abnormalities. The fetal abdominal signal was processed and enhanced by means of the averaging technique after removing the maternal complex. In normal pregnancies P wave and QRS complex duration increases progressively from the 17th week up to the term: this increase parallels the gain in weight of the fetal heart and particularly of the ventricular mass. These results indicated that the duration of fetal complexes could be used as an index of the size, development and maturity of the fetal heart. When fetal growth retardation (FGR) is present, the weight of the fetal heart is significantly reduced, and is reflected in a decrease in QRS duration. In a series of 107 cases the sensitivity of this parameter in detecting FGR was 81% and the specificity 93%. Moreover no perinatal death nor Apgar values below 7 occurred in growth retarded fetuses with normal QRS duration, while in the group with shortened QRS neonatal deaths were 11% and Apgar scores below 7 26%. Abdominal FECG do provide important auxiliary information for prenatal diagnosis of congenital heart defects (CHD). Anomalies with abnormal atrioventricular connection were reflected in longer PR interval. Ventricular hypertrophia and hypoplasia were associated with increased or decreased QRS duration, respectively. Furthermore, the three fetuses which developed congestive heart failure showed prolonged QRS duration. In severe RH disease, chronic fetal anemia can lead to myocardial hypertrophy and cardiac enlargement.(ABSTRACT TRUNCATED AT 250 WORDS)
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The signal constituted by the successive R-R intervals in the ECG tracing carries important information about the control mechanisms of heart rate. The present paper describes advanced methods of parameter extraction from the R-R duration time series which use autoregressive (AR) modeling and power spectral estimates applied to patients in the MIT-BIH arrhythmia data base. The described methodologies enhance information which characterize the most common rhythm disturbances (A-V block, bigeminy/trigeminy, atrial and ventricular flutter, atrial fibrillation, etc.). Important applications of such methods are in the area of the pathophysiological comprehension of cardiac rhythm control mechanisms in the research side and the classification of abnormal rhythms as well in the clinical side. A few examples from the data base are illustrated which show interesting properties of signal processing and classification in respect to the more traditional methods.
The methods of identification and spectral estimate are applied to the tachogram, i.e. the time series constituted by the cycle-by-cycle R-R interval durations measured on the ECG signal from cardiological patients in ambulatory rehabilitation training after episodes of myocardial infarction or ischemic disease. The Batch Least Squares Method is applied to identify the series as an AR process of 5th order. The whiteness test and Rissanen's optimization criterion are also fulfilled. The clinical information is in this way highly compressed in the pole diagram and in the Maximum Entropy Spectrum (MES) estimated on the basis of the AR coefficients. The experimental results in a restricted set of patients confirm the feasibility of new instrumentation design criteria for non-conventional R-R intervals parametrisation, successive diagnostic classification and beat prediction. Finally, some preliminary considerations about the capabilities of the introduced methods put into evidence the role of computerized techniques in recognizing the fundamental patterns of physiopathological heart rate variability, which the usual conventional methods of ECG analysis are not able to detect in a reliable way.
The analysis of power spectral density (PSD) or RR variability in the electrocardiogram (ECG) has suggested that, in the early phase of essential hypertension, sympatho-vagal interaction is characterized by a sympathetic predominance. Recently, we have developed a high fidelity, direct arterial pressure ambulatory recording system which allows a beat by beat computer analysis of arterial pressure and heart rate. A microminiature tip transducer (Millar, diameter 0.8 mm) is inserted percutaneously into the radial artery and connected to a Holter two-channel magnetic tape recorder. The tip transducer has a wide band pass (> 1 kHz), excellent stability (congruent to 2 mmHg/24 h) and does not require a perfusion line. The overall frequency response of the entire recording-reproducing system is better than 20 Hz (-3 dB). The ECG and pressure signals are analysed with automatic autoregressive modelling algorithms to provide a quantitative estimate of blood pressure and heart rate variability through the computation of the PSD. In seven hypertensive patients, systolic arterial pressure and variance were higher during the day (157 +/- 9 mmHg and 122 +/- 9 mmHg2) than during the night (122 +/- 4 mmHg and 30 +/- 3 mmHg2). The PSD of RR and of systolic arterial pressure consisted of a predominant low frequency peak (congruent to 0.09 cycles/beat) during the day, and two peaks at low and high (congruent to 0.25 cycles/beat) frequency during the night. While RR variance was similar during both day- and night-time, a predominant low frequency peak was observed during the day.(ABSTRACT TRUNCATED AT 250 WORDS)
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