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R Atarius

Publications and source records attributed to R Atarius.

5 recordsLinked to original sources
PubMed1997

Detection of cardiac late potentials in nonstationary noise.

An 'instantaneous' optimal filter is presented for improving the signal-to-noise ratio in averaged electrocardiograms (ECGs). The filter design is based on a simple model that accounts for correlation across the ensemble of beats but ignores correlation in time. Another property of the model is that the noise level is allowed to change from beat to beat. Simulation results indicate that an improved performance is achieved by the new filter when compared to a filter with a similar structure but designed for processing beats with a constant noise level. Several ECG examples are included to demonstrate the performance of the filter for detecting late potentials.

Algorithms↗
PubMed1996

Maximum likelihood analysis of cardiac late potentials.

This study presents a new time-domain method for the detection of late potentials in individual leads. Basic statistical properties of the ECG samples are modeled in order to estimate the amplitude and duration of late potentials. The signal model accounts for correlation in both time and across the ensemble of beats. Late potentials are modeled as a colored process with unknown amplitude which is disturbed by white, Gaussian noise. Maximum likelihood estimation is applied to the model for estimating the amplitude of the late potentials. The resulting estimator consists of an eigenvector-based filter followed by a nonlinear operation. The performance of the maximum likelihood procedure was compared to that obtained by traditional time-domain analysis based on the vector magnitude. It was found that the new technique yielded a substantial improvement of the signal-to-noise ratio in the function used for endpoint determination. This improvement leads to a prolongation of the filtered QRS duration in cases with late potentials.

Action Potentials↗
PubMed1995

Reproducibility of the signal-averaged electrocardiogram using individual lead analysis.

The aim of the study was to evaluate the immediate reproducibility of time domain parameters in the signal averaged electrocardiogram using a new method for endpoint determination in individual Frank leads. The method is based on a statistical model of the electrocardiogram (ECG) in which maximum likelihood (ML) estimation is employed. The reproducibility of the ML method was compared to that of conventional time domain analysis using the vector magnitude (VM) of Frank leads. Fifty-nine patients were included in the study and two consecutive ECGs were recorded for signal averaging. The results showed that the mean of the absolute difference of the filtered QRS duration (QRSD) between two consecutive recordings was significantly lower for the ML method than the conventional method when employing 60 Hz highpass filtering (2.1 +/- 2.2 ms vs 5.9 +/- 10.2 ms, P < 0.05). Moreover, the ML method resulted in a significantly longer QRSD compared to the VM-based method (P < 0.05). The terminal amplitude of the QRS complex (RMS40) showed a greater variability than the QRSD for both methods, although the ML method was associated with a higher reproducibility than the VM method for the 60 Hz filter. These findings may contribute to a better identification of patients at high risk of ventricular arrhythmias. A reduction in the number of measurement errors has important implications when QRS changes are analysed over time.

Adult↗
PubMed1995

Signal-to-noise ratio enhancement of cardiac late potentials using ensemble correlation.

An optimal one-weight "filter" is presented for the purpose of improving the signal-to-noise ratio of averaged ECG recordings in the analysis of late potentials. Based on a simple statistical model, the filter is estimated from the ensemble correlation of available beats. The correlation estimator is found by a maximum likelihood procedure in which the observed signal is assumed to have a Gaussian distribution. The performance of the optimal filter is studied in relation to an ensemble with individual or subaveraged beats.

Action Potentials↗