Maurizio Varanini

Deriving the respiratory sinus arrhythmia from the heartbeat time series using Empirical mode decomposition

Abstract Heart rate variability (HRV) is a well-known phenomenon whose characteristics are of great clinical relevance in pathophysiologic investigations. In particular, respiration is a powerful modulator of HRV contributing to the oscillations at highest frequency. Like almost all natural phenomena, HRV is the result of many nonlinearly interacting processes; therefore any linear analysis has the potential risk of underestimating, or even missing, a great amount of information content. Recently the technique of empirical mode decomposition (EMD) has been proposed as a new tool for the analysis of nonlinear and nonstationary data. We applied EMD analysis to decompose the heartbeat intervals series, derived from one electrocardiographic (ECG) signal of 13 subjects, into their components in order to identify the modes associated with breathing. After each decomposition the mode showing the highest frequency and the corresponding respiratory signal were Hilbert transformed and the instantaneous phases extracted were then compared. The results obtained indicate a synchronization of order 1:1 between the two series proving the existence of phase and frequency coupling between the component associated with breathing and the respiratory signal itself in all subjects.

Noninvasive ECG as a Tool for Predicting Termination of Paroxysmal Atrial Fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia and entails an increased risk of thromboembolic events. Prediction of the termination of an AF episode, based on noninvasive techniques, can benefit patients, doctors and health systems. The method described in this paper is based on two-lead surface electrocardiograms (ECGs): 1-min ECG recordings of AF episodes including N-type (not terminating within an hour after the end of the record), S-type (terminating 1 min after the end of the record) and T-type (terminating immediately after the end of the record). These records are organised into three learning sets (N, S and T) and two test sets (A and B). Starting from these ECGs, the atrial and ventricular activities were separated using beat classification and class averaged beat subtraction, followed by the evaluation of seven parameters representing atrial or ventricular activity. Stepwise discriminant analysis selected the set including dominant atrial frequency (DAF, index of atrial activity) and average HR (HRmean, index of ventricular activity) as optimal for discrimination between N/T-type episodes. The linear classifier, estimated on the 20 cases of the N and T learning sets, provided a performance of 90% on the 30 cases of a test set for the N/T-type discrimination. The same classifier led to correct classification in 89% of the 46 cases for N/S-type discrimination. The method has shown good results and seems to be suitable for clinical application, although a larger dataset would be very useful for improvement and validation of the algorithms and the development of an earlier predictor of paroxysmal AF spontaneous termination time.

Adaptive threshold QRS detector with best channel selection based on a noise rating system

QRS detection performance can depend on the type of noise present in each lead involved in the overall processing. A common approach to QRS detection is based on a QRS enhanced signal obtained from the derivatives of the pre-filtered leads. However, the signal pre-filtering cannot be able to perform a complete noise rejection and the use of derivatives can enhance the noise as well. In many cases the noise occurs only on one lead and the addition of a noisy lead to the QRS enhanced signal decreases the overall detection performances of the QRS detector. For this reason the noise estimation on each channel, providing information for the channel inclusion or rejection in building the QRS enhanced signal, can improve the overall performances of the QRS detector. The results have been evaluated on the 48 records of the MIT-BIH Arrhythmia Database where each ECG record is composed by 2 leads sampled at 360 Hz for a total duration of about 30 minutes. The annotated QRSs are 109494 in total. The results have been very satisfying on all the annotated QRSs and, with the inclusion of an automatic criterion for ventricular flutter detection, a sensitivity=99.76% and a positive predictive value=99.81% have been obtained.

Revisiting the potential of time-domain indexes in short-term HRV analysis

Abstract In the context of HRV analysis, we evaluated the information content of two measures that can easily be derived from the classical RR time-domain indexes. The two measures are: 1) the ratio sd/rmssd, where sd is the RR standard deviation and rmssd is the root mean square of squared differences of consecutive RR beats; and 2) the ratio sd2/sd1, where sd2 and sd1 are extracted from the Poincaré plot and represent the transversal and longitudinal dispersion of the cloud of points (RRi ,RRi +1). We compared the performance of the two measures with that of the classical LF/HF ratio in a group of healthy subjects who underwent a 70° upright tilt test. The goodness of the results obtained by the two measures, the simplicity of their calculation and their applicability free from a priori assumptions on the characteristics of the data are proposed to the attention of the community involved in the HRV analysis as a possible alternative to the LF/HF ratio.

An efficient unsupervised fetal QRS complex detection from abdominal maternal ECG.

Non-invasive fetal heart rate is of great relevance in clinical practice to monitor fetal health state during pregnancy. To date, however, despite significant advances in the field of electrocardiography, the analysis of abdominal fetal ECG is considered a challenging problem for biomedical and signal processing communities. This is mainly due to the low signal-to-noise ratio of fetal ECG and difficulties in cancellation of maternal QRS complexes, motion and electromyographic artefacts. In this paper we present an efficient unsupervised algorithm for fetal QRS complex detection from abdominal multichannel signal recordings combining ICA and maternal ECG cancelling, which outperforms each single method. The signal is first pre-processed to remove impulsive artefacts, baseline wandering and power line interference. The following steps are then applied: maternal ECG extraction through independent component analysis (ICA); maternal QRS detection; maternal ECG cancelling through weighted singular value decomposition; enhancing of fetal ECG through ICA and fetal QRS detection. We participated in the Physionet/Computing in Cardiology Challenge 2013, obtaining the top official scores of the challenge (among 53 teams of participants) of event 1 and event 2 concerning fetal heart rate and fetal interbeat intervals estimation section. The developed algorithms are released as open-source on the Physionet website.

Quantifying different degrees of coupling in detrended cross-correlation analysis

Detrended cross-correlation analysis provides a scaling exponent that should characterize the power-law cross-correlation of two simultaneously recorded series. This exponent by itself is not able to guarantee the presence of cross-correlation, being strongly influenced by the auto-correlation properties of the single series. Through the use of σDCCA coefficients and simulation with ARFIMA models we built families of curves that can be used as templates to correctly detect the power-law behaviour and quantify the degree of coupling between series with any degree of auto-correlation.

Effect of acute administration of vitamin C on muscle sympathetic activity, cardiac sympathovagal balance, and baroreflex sensitivity in hypertensive patients

BACKGROUND Essential hypertension is characterized by both increased oxidative stress and sympathetic traffic. Experimental studies have shown that reactive oxygen species can modulate autonomic activity. OBJECTIVE The aim of this study was to determine whether acute administration of the antioxidant vitamin C modifies sympathetic nerve activity in essential hypertension. DESIGN Thirty-two untreated patients with essential hypertension and 20 normotensive subjects received vitamin C (3 g intravenously in 5 min) or vehicle. Heart rate, noninvasive beat-to-beat blood pressure, and muscle sympathetic nerve activity (microneurography) were monitored at baseline and up to 20 min after the infusion. Spectral analysis of RR interval variability and spontaneous baroreflex sensitivity were also computed. RESULTS Vitamin C infusion significantly lowered blood pressure in hypertensive patients but not in normotensive subjects (maximal changes in systolic blood pressure: -4.9 ± 10.1 compared with -0.7 ± 4.0 mm Hg, respectively; P < 0.05). Moreover, muscle sympathetic nerve activity was significantly reduced after vitamin C infusion in hypertensive patients (from 53.3 ± 12.2 to 47.4 ± 11.5 bursts/100 heart beats; P < 0.01) but not in healthy subjects (from 42.0 ± 10.1 to 42.7 ± 11.8 bursts/100 heart beats; NS). On the contrary, in 16 hypertensive patients, sodium nitroprusside in equidepressor doses induced a significant increase in muscle sympathetic nerve activity compared with vitamin C (+10.0 ± 6.9 bursts/100 heart beats). Sympathovagal balance and spontaneous baroreflex sensitivity were restored during vitamin C infusion in hypertensive subjects. CONCLUSIONS These results indicate that acute administration of vitamin C is able to reduce cardiovascular adrenergic drive in hypertensive patients, which suggests that oxidative stress is involved in the regulation of sympathetic activity in essential hypertension.

Cardiovascular and respiratory correlates of deep nociceptive stimulation, suggestions for analgesia, pain imagery and cognitive load as a function of hypnotizability

Hypnotizability is a cognitive trait modulating some physiological responses to cognitive and physical stimulation also in the normal awake state and in the absence of specific suggestions. Aim of the study was the characterization of the cardiovascular correlates of deep pain induced by nociceptive pressor stimulation without (PAIN) and with (AN) suggestions for analgesia, pain imagery/perception (IM) and mental computation (MC) in not hypnotized highly (Highs) and low (Lows) hypnotizable healthy subjects of both genders. The subjective experience of pain intensity, relaxation and task related fatigue were measured through a structured interview. Heart rate, blood pressure, skin blood flow and respiratory activity were monitored throughout the experimental session. Only Highs perceived lower pain intensity during AN with respect to PAIN and were able to perceive pain during IM. Heart rate decreased during PAIN, increased during MC and did not change during AN and IM in both groups. On the whole, the haemodynamic response consisted of decreased systolic/mean blood pressure and maximum skin blood flow together with increased diastolic blood pressure/minimum skin blood flow in both groups during all conditions. Scarce differences were observed between Highs and Lows (in systolic blood pressure during IM and in respiratory amplitude during PAIN, AN and IM, modulated by gender). The results indicate that in not hypnotized subjects hypnotizability is not associated with relevant differences in the autonomic responses to deep pain, suggestions for analgesia, pain imagery/perception and cognitive load.

Heart-rate control during pain and suggestions of analgesia without deliberate induction of hypnosis.

Abstract Heart rate and heart-rate variability (HRV) were studied through a set of different methods in high (highs) and low hypnotizable subjects (lows) not receiving any deliberate hypnotic induction in basal conditions (simple relaxation) and during nociceptive-pressor stimulation with and without suggestions of analgesia. ANOVA did not reveal any difference between highs and lows for heart rate and for the HRV indexes extracted from the series of the interbeat intervals (RR) of the ECG in the frequency (spectral analysis) and time domain (standard deviation, Poincaré plot) in both basal and stimulation conditions. Factors possibly accounting for the results and likely responsible for an underestimation of group differences are discussed.

Cardiac and respiratory monitoring through non-invasive and contactless radar technique

The aim of this study was the evaluation of a microwave (MW) device for vital signs monitoring of patients and for MW signal characterization in terms of physiological content and meaning. Experimental tests were executed on volunteers in selected and controlled conditions and with different device setting. In each test session the MW signal was digitally acquired and saved together with true physiological signals coming from standard medical instrumentation. Single and multichannel data processing were applied in order to extract characteristic features from each signal and to identify any significant correlation. The results show the ability of the method to obtain precise indications on small physiological movements such as breathing or heartbeat; the received MW signal seems to offer specific information about the mechanical dynamics of the cardiac system. With our configuration settings, main limitations of this approach come from its low capacity to penetrate deeply into the body and to the poor spatial resolution.