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

Institute of Physiology, School of Medicine, University of Ljubljana, Ljubljana 1104, Slovenia.
Journal of electrocardiology (Impact Factor: 1.36). 11/2006; 39(4):358-67. DOI: 10.1016/j.jelectrocard.2006.03.004
Source: PubMed

ABSTRACT 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.

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Available from: Todd T Schlegel, Mar 31, 2015
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    • "Baumert et al. [36] compared three algorithms, template stretch [24], template shift [37] and a conventional (derivative) approach [35], and showed that using these data the template based algorithms outperform the other method in most cases. However, the authors emphasize certain limitations of the comparison , arising e.g. from differing beat rejection strategies. "
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    ABSTRACT: We propose a novel method for evaluating the similarity between two 1d patterns. Our method, referred to as two-dimensional signal warping (2DSW), extends the basic ideas of known warping techniques such as dynamic time warping and correlation optimized warping. By employing twodimensional piecewise stretching 2DSW is able to take into account inhomogeneous variations of shapes. We apply 2DSW to ECG recordings to extract beat-to-beat variability in QT intervals (QTV) that is indicative of ventricular repolarization lability and typically characterised by a low signal-to-noise ratio. Simulation studies show high robustness of our approach in presence of typical ECG artefacts. Comparison of shortterm ECG recorded in normal subjects versus patients with myocardial infarction (MI) shows significantly increased QTV in patients (normal subject 2:36ms 1:05ms vs. MI patients 5:94ms 5:23ms (mean std), p < 0:001). Evaluation of a standard QT database shows that 2DSW allows highly accurate tracking of QRS-onset and T-end. In conclusion, the two-dimensional warping approach introduced here is able to detect subtle changes in noisy quasi-periodic biomedical signals such as ECG and may have diagnostic potential for measuring repolarization lability in MI patients. In more general terms, the proposed method provides a novel means for morphological characterization of 1d signals.
    IEEE Transactions on Signal Processing 11/2014; 62(21):1-1. DOI:10.1109/TSP.2014.2354313 · 2.79 Impact Factor
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    • "Therefore, in this study, we incorporated an alternative Rpeak detection technique and baseline removal approach in the existing computer software, which was developed by Berger and his co-workers [13]. The performance of the updated approach has been compared with the existing method [13] and two other methods (conventional method [21], template time shift method [22]) on simulated ECG as described in a previous article [23]. "
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    ABSTRACT: The aim of this study was to enhance the ECG pre-processing modalities for beat-to-beat QT interval variability measurement based on template matching. The R-peak detection algorithm has been substituted and an efficient baseline removal algorithm has been implemented in existing computer software. To test performance we used simulated ECG data with fixed QT intervals featuring Gaussian noise, baseline wander and amplitude modulation and two alternative algorithms. We computed the standard deviation of beat-to-beat QT intervals as a marker of QT interval variability (QTV). Significantly a lower beat-to-beat QTV was found in the updated approach compared the original algorithm. In addition, the updated template matching computer software outperformed the previous version in discarding fewer beats. In conclusion, the updated ECG preprocessing algorithm is recommended for more accurate quantification of beat-to-beat QT interval variability.
    Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 07/2013; 2013:2563-2566. DOI:10.1109/EMBC.2013.6610063
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    • "The main idea of the time shifting technique is to construct separate QRS and T wave templates and shift them in time to obtain precise QT interval estimates. The algorithm is fully automated to avoid any influence of the operator and has been described in detail elsewhere [25]. "
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    ABSTRACT: Increased beat-to-beat variability in the QT interval (QTV) of ECG has been associated with increased risk for sudden cardiac death, but its measurement is technically challenging and currently not standardized. The aim of this study was to investigate the performance of commonly used beat-to-beat QT interval measurement algorithms. Three different methods (conventional, template stretching and template time shifting) were subjected to simulated data featuring typical ECG recording issues (broadband noise, baseline wander, amplitude modulation) and real short-term ECG of patients before and after infusion of sotalol, a QT interval prolonging drug. Among the three algorithms, the conventional algorithm was most susceptible to noise whereas the template time shifting algorithm showed superior overall performance on simulated and real ECG. None of the algorithms was able to detect increased beat-to-beat QT interval variability after sotalol infusion despite marked prolongation of the average QT interval. The QTV estimates of all three algorithms were inversely correlated with the amplitude of the T wave. In conclusion, template matching algorithms, in particular the time shifting algorithm, are recommended for beat-to-beat variability measurement of QT interval in body surface ECG. Recording noise, T wave amplitude and the beat-rejection strategy are important factors of QTV measurement and require further investigation.
    PLoS ONE 07/2012; 7(7):e41920. DOI:10.1371/journal.pone.0041920 · 3.23 Impact Factor
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