Modulating effect of respiration on atrioventricular conduction time assessed using PR interval variation

A NOVEL FRAMEWORK FOR SIGNAL REPRESENTATION AND SOURCE SEPARATION: APPLICATIONS TO FILTERING AND SEGMENTATION OF BIOSIGNALS

A general technique for representing quasi-periodic oscillations, typical of biomedical signals, is described. Using energy thresholding and Gaussian kernels, in conjunction with a nonlinear gradient descent optimization, it is shown that significant noise reduction, compression and turning point location is possible. As such, the signal representation model can be considered a form of correlated source separation. Applications to filtering, modelling and robust ECG QT-analysis are described.

Comparison of three methods for beat-to-beat-interval extraction from continuous blood pressure and electrocardiogram with respect to heart rate variability analysis

In recent years the analysis of heart rate variability (HRV) has become a suitable method for characterizing autonomous cardiovascular regulation. The aim of this study was to investigate the differences in HRV estimated from continuous blood pressure (BP) measurement by different methods in comparison to electrocardiogram (ECG) signals. The beat-to-beat intervals (BBI) were simultaneously extracted from the ECG and blood pressure of 9 cardiac patients (10 min, Colin system, 1000-Hz sampling frequency). For both data types, slope, peak, and correlation detection algorithms were applied. The short-term variability was calculated using concurrent 10-min BP and ECG segments. The root mean square errors in comparison to ECG slope detection were: 1.74 ms for ECG correlation detection; 5.42 ms for ECG peak detection; 5.45 ms for BP slope detection; 5.75 ms for BP correlation detection; and 11.96 ms for BP peak detection. Our results show that the variability obtained with ECG is the most reliable. Moreover, slope detection is superior to peak detection and slightly superior to correlation detection. In particular, for ECG signals with higher frequency characteristics, peak detection often exhibits more artificial variability. Besides measurement noise, respiratory modulation and pulse transit time play an important role in determining BBI. The slope detection method applied to ECG should be preferred, because it is more robust as regards morphological changes in the signals, as well as physiological properties. As the ECG is not recorded in most animal studies, distal pulse wave measurement in combination with correlation or slope detection may be considered an acceptable alternative.

Real-time multichannel system for beat-to-beat QT interval variability

The measurement of beat-to-beat QT interval variability (QTV) shows clinical promise for identifying several types of cardiac pathology. However, until now, there has been no device capable of displaying, in real time on a beat-to-beat basis, changes in QTV in all 12 conventional leads in a continuously monitored patient. Although several software programs have been designed to analyze QTV, heretofore, such programs have all involved only a few channels (at most) and/or have required laborious user interaction or offline calculations and postprocessing, limiting their clinical utility. This article describes a PC-based electrocardiogram software program recently codeveloped by our laboratories that, in real time, acquires, analyzes, and displays QTV in each of the 8 independent channels that constitute the 12-lead conventional electrocardiogram. The system also analyzes and displays the QTV from QT-interval signals that are derived from multiple channels and from singular value decomposition such that the effect of noise and other artifacts on the QTV results are substantially reduced compared with existing single-channel methods.

Effect of pentobarbital on spectral characteristics and phase ratios of wave oscillations of cardiac contraction period and time of atrioventricular conduction in cats

Effects of pentobarbital on spectral characteristics and phase ratios of wave oscillations of the cardiac contraction period (RR interval) and time of atrioventricular conduction (AV interval) were studied in experiments of cats. Pentobarbital moderately reduced the mean values of both intervals and significantly reduced their standard deviations and spectral powers in all frequency bands (high-frequency, low-frequency, and very low-frequency). Pentobarbital treatment led to deceleration of breathing, the frequency range of respiratory oscillations of RR and AV intervals shifted in some cases from high to low frequencies; evaluation of spectral power in the intermittent band corresponding to respiration frequency (instead of standard fixed high-frequency band) showed that pentobarbital suppressed the respiratory oscillations in these bands. Pentobarbital induced inversion of phase ratio between respiratory oscillations of RR and AV intervals: oscillations of both intervals before pentobarbital coincided by phase, while after pentobarbital injection they were in antiphase. The mechanisms of the latter phenomenon deserve further investigation.

Chronodromotropic coordination in cats

The coordinated nervous influences on HR and atrioventricular conduction velocity (chronodromotropic coordination) were examined in wakeful cats. The wave structure and reflex reactions of RR and atrioventricular (AV) intervals to stress noise stimulation were studied under normal conditions and during the action of blockers of peripheral receptors in ANS. Variations of both intervals had similar wave structure (power spectrum) and similar reactions to noise stimulus. Atropine pronouncedly decreased all components of the spectra in the high, low, and very low frequency ranges. It eliminated the reactions of both intervals to noise stimulation. In RR intervals, the high-frequency spectrum component decreased more strongly than the low-frequency ones. By contrast, in AV intervals atropine most greatly decreased the very-low-spectrum component, while the high frequency was decreased less of all. Propranolol produced no effect on the response to noise. It did not decrease components of the wave structure in both intervals, except for the very-low-frequency peak of AV interval. The nervous chronotropic and dromotropic influences were largely coordinated, although they were not obligatorily parallel.

Effects of RR segment duration on HRV spectrum estimation

Although patterns of heart rate variability (HRV) hold considerable promise for clarifying issues in clinical applications, the inappropriate quantification and interpretation of these patterns may obscure critical issues or relationships and may impede rather than foster the development of clinical applications. The duration of the RR interval series is not a matter of convenience but a fine balance between two important issues: acceptable variance and stationarity of the time series on one hand, and acceptable resolution of the spectral estimate and reduced spectral leakage on the other. Further, in the standard short-term HRV analysis, it has been observed that the previous studies in HRV spectral analysis use a wide range of RR interval segment duration for spectral estimation by Welch's algorithm. The standardization of RR interval segment duration is also important for comparisons among studies and is essential for within-study experimental contrasts. In the present study, a comparative analysis for RR interval segment durations has been made to propose an optimal RR interval segment duration. Firstly a simulated signal was analyzed with Hann window and zero padding for the segment lengths of 1024, 512, 256 and 128 samples resampled at 4 Hz with 50% overlapping. Again, the above procedure was applied to RR interval series and it was concluded that segment length of 256 samples with 50% overlapping provides a smoothed spectral estimate with clearly outlined peaks in low- and high-frequency bands. This easily understandable and interpretable spectral estimate leads to a better visual and automated analysis, which is not only desirable in basic physiology studies, but also a prerequisite for a widespread utilization of frequency domain techniques in clinical studies, where simplicity and effectiveness of information are of primary importance.