A time-variant algorithm of autoregressive (AR) identification is introduced and applied to the heart rate variability (HRV) signal. The power spectrum is calculated from the AR coefficients derived from each single RR interval considered. Time-variant AR coefficients are determined through adaptive parametric identification with a forgetting factor which obtains weighed values on a running temporal window of 50 preceding measurements. Power spectrum density (PSD) is hence obtained at each cardiac cycle, making it possible to follow the dynamics of the spectral parameters on a beat-by-beat basis. These parameters are mainly the LF (low frequency) and the HF (high frequency) powers, and their ratio LF/HF. These together account for the balanced sympatho-vagal control mechanism affecting the heart rate. This method is applied to subjects suffering from transient ischemic attacks. The time variant spectral parameters suggest an early activation of LF component in the HRV power spectrum. It precedes by approximately 1.5-2 min the tachycardia and the ST displacement, generally indicative of the onset of an ischemic episode. The results suggest an arousal of sympathetic system before the acute attack.

This paper considers the multiscale entropy (MSE) approach for estimating the regularity of time series at different scales. Sample entropy (SampEn) and approximate entropy (ApEn) are evaluated in MSE analysis on simulated data to enhance the main features of both estimators. We applied the approximate entropy and the sample entropy estimators to fetal heart rate signals on both single and multiple scales for an early identification of fetal sufferance antepartum. Our results show that the ApEn index significantly distinguishes suffering from normal fetuses between the 30th and the 35th week of gestation. Furthermore, our data shows that the MSE entropy values are reliable indicators of the fetal distress associated with the presence of a pathological condition at birth.

BACKGROUND AND OBJECTIVES--Autonomic dysfunction seems to be involved in the progression and prognosis of severe congestive heart failure. Parasympathetic activity can still be abnormal 4-8 weeks after haemodynamic improvement by heart transplantation. To identify patients in heart failure with a more pronounced neural derangement and to analyse the changes in sympathetic and parasympathetic activity soon after heart transplantation, spectral indices of heart rate variability were assessed in 30 patients in severe heart failure and in 13 patients after heart transplantation; a group of 15 age-matched subjects served as controls. METHODS AND RESULTS--Heart rate variability was assessed by standard electrocardiography (ECG) in patients in heart failure and by oesophageal ECG in patients after heart transplantation. Compared with controls, the mean RR interval and total power were reduced in heart failure. The 30 patients showed two different patterns of heart rate variability: in 14 no power was detected in the low frequency band (0.03-0.15 Hz) (LF) and total power was mainly concentrated in the high frequency band (0.15-0.45 Hz) (HF), whereas in the remaining 16 patients power in the LF band was increased and power in HF band was reduced compared with the controls. Patients with undetectable LF had a lower mean RR interval and total power (745(25) v 864(36) ms, p < 0.05; 118(16) v 902(202) ms2, p < 0.001), higher concentration of plasma noradrenaline (635(75) v 329(54) pg/ml, p < 0.05), and worse clinical status and prognosis (4 deaths v no deaths at 6 month follow up) than patients with a dominant LF band. In the post-transplant patients both the mean PP interval of the remnant atrium and total power resembled results in the patients with heart failure; in 7 of the 13 post-transplant patients no power was detectable in the LF band: when both HF and LF power were present the results resembled those in the 16 patients in heart failure. CONCLUSIONS--These data suggest that in more advanced stages of congestive heart failure, power spectral analysis of heart rate variability allows identification of a subgroup of patients with higher sympathetic activation and poorer clinical status who are at major risk of adverse events. In the short term after cardiac transplantation the spectral profile of the rhythm variability of the remnant atrium was not improved, suggesting that parasympathetic withdrawal and sympathetic hyperactivity persist, despite the restoration of ventricular function.

The main goal of this work is to suggest new indices for a correct identification of the intrauterine growth-restricted (IUGR) fetuses on the basis of fetal heart rate (FHR) variability analysis performed in the antepartum period. To this purpose, we analyzed 59 FHR time series recorded in early periods of gestation through a Hewlett Packard 1351A cardiotocograph. Advanced analysis techniques were adopted including the computation of the Lempel Ziv complexity (LZC) index and the multiscale entropy (MSE), that is, the entropy estimation with a multiscale approach. A multiparametric classifier based on k-mean cluster analysis was also performed to separate pathological and normal fetuses. The results show that the proposed LZC and the MSE could be useful to identify the actual IUGRs and to separate them from the physiological fetuses, providing good values of sensitivity and accuracy (Se = 77.8%, Ac = 82.4%).