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ABSTRACT: Long-term monitoring of ECG signals is receiving much attention, still being an open issue how to deal with this massive source of information. In particular, Heart Rate Variability (HRV) indices have been widely used to characterize the state of the autonomous regulation of the heart from 24-hour Holter monitoring, but there is few knowledge on the long-term evolution of HRV indices. A data set of 7-day Holter recordings in 12 Congestive Heart Failure (CHF) patients was assembled. For its analysis, an automatic rhythmometric procedure was designed, allowing to characterize the ultradian and the infradian components, with possible inclusion of near-periodic fluctuations. A bootstrap hypothesis test allows us to systematically adjust the model architecture for each patient. The temporal evolution of relevant time-domain (AVNN, SDNN, NN50), frequency-domain (LF, HF, HFn, LF/HF), and nonlinear (¿<sub>1</sub>, SampEn) HRV indices, was analyzed. Larger relative deviations from the daily average pattern were more clearly observed in nonlinear indices and in NN50. Infradian subharmonic was mostly present in NN50, AVNN, ¿<sub>1</sub>, and SampEn. Long-term monitoring of HRV conveys new relevant rhythmometric information that can be analyzed with the proposed automatic procedure.
Computers in Cardiology, 2009; 10/2009
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ABSTRACT: Digital recovery of cardiac signals from paper printed recordings in implantable cardioverter defibrillators (ICD) is needed whenever signals in digital format can not be retrieved from stored electrograms (EGM). Though many methods have been proposed for digital recovery of paper printed ECG, none has specifically addressed the intracardiac EGM, which are only available in black and white. Our aims were: (1) to propose an image processing algorithm suitable for recovering ICD stored EGM; (2) to evaluate its performance in different cardiac rhythms by using an adequate time synchronization processing for this application. An image processing algorithm was designed for recovering the signals from ICD paper printed EGM. EGM from simultaneously acquired tip-ring and can-coil ICD lead configurations were scanned. Tip-ring and can-coil recordings were automatically separated into two streams, and signal tracking was made for each stream. Recovered EGM were compared to their gold standard (ICD sampled and stored recordings). Time alignment of recovered and gold standard EGM was observed to be fundamental on the performance measurements, so that three different techniques (LS, spline, and matched filter) were benchmarked. Consistent lower performance was observed in tip-ring than in can-coil recovered EGM and performance was improved by LS alignment with respect to spline and matched filter. In conclusion, our algorithm allows to automatically recovering ICD EGM from paper printed recordings.
Computers in Cardiology, 2009; 10/2009
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ABSTRACT: Heart rate turbulence (HRT) is a transient acceleration and subsequent deceleration of the heart rate after a premature ventricular complex (PVC), and it has been shown to be a strong risk stratification criterion in patients with cardiac disease. In order to reduce the noise level of the HRT signal, conventional measurements of HRT use a patient-averaged template of post-PVC tachogram (PPT), hence providing with long-term HRT indexes. We hypothesize that the reduction of the noise level at each isolated PPT, using signal processing techniques, will allow us to estimate short-term HRT indexes. Accordingly, its application could be extended to patients with reduced number of available PPT. In this paper, several HRT denoising procedures are proposed and tested, with special attention to support vector machine (SVM) estimation, as this is a robust algorithm that allows us to deal with few available time samples in the PPT. Pacing-stimulated HRT during electrophysiological study are used as a low-noise gold standard. Measurements in a 24-h Holter patient database reveal a significant reduction in the bias and the variance of HRT measurements. We conclude that SVM denoising yields short-term HRT measurements and improves the signal-to-noise level of long-term HRT measurements.
IEEE Transactions on Biomedical Engineering 03/2009; · 2.28 Impact Factor
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ABSTRACT: Though alternans phenomena in the cardiac repolarization phase has been shown to be related to arrhythmgenesis, a definitive estimation method from the T wave of ECG recordings is not yet available. We propose a statistical signal processing scheme which compares the T-wave morphology of even and odd beats by using a running matched filter, in order to increase the signal to noise ratio of the estimation. Given that previously proposed hypothesis tests for alternans detection rely on the knowledge of noise statistical distribution, we also analyzed the usefulness of a nonparametric bootstrap test. Data set composed of 100 ECG recordings included in the Challenge Database were used. Principal Component Analysis was previously made for multilead recordings. Subsequent preprocessing for each available lead consisted of conventional baseline removing, filtering, R-wave detection, exclusion of too noisy segments, T-wave segmentation, and template generation for even and odd beats. The difference between the template and a given beat was obtained by minimizing the absolute error of their comparison with a windowed circular shift. A paired bootstrap resampling test was made for deciding whether the averaged differences between the template and the T-waves were significant compared to the noise level.
Computers in Cardiology, 2008; 10/2008
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ABSTRACT: Chaos and fractal based measurements, such as detrended fluctuation analysis (DFA), have been widely used for quantifying the heart rate variability (HRV) for cardiac risk stratification purposes. However, the physiological meaning of these measurements is not clear. Given that existing lumped parameter models contain a detailed physiological description of several of the circulatory system regulation processes, we hypothesize that controlled changes in these processes will highlight the physiological basis in DFA indices. We used a detailed lumped parameter model of HRV, introduced earlier. Ten signals were generated in different physiological conditions. DFA coefficients alpha<sub>1</sub>, alpha<sub>2</sub>, and the Hurst exponent, were calculated. A clear disruption point was always observed. Modifications in sympatho-vagal activity yielded significant changes in alpha<sub>1</sub> when compared to basal, but not in alpha<sub>2</sub> or Hurst exponent. Modifications in non-nervous system mediated changes yielded significant differences only for peripheral resistance and heart period, only in alpha<sub>1</sub>. In conclusion, the analysis of the effect of changes in the regulatory system on the HRV chaotic/fractal indices can be analyzed using detailed lumped parameter models.
Computers in Cardiology, 2007; 11/2007
