The development and validation of an easy to use automatic QT-interval algorithm

Figures

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  Fig 1. Schematic representation the algorithm’s steps. A detailed description is given in the main text. Fs = sample frequency, Hz = hertz, IIR = infinite impulse response, FFT = fast Fourier transform, |VCG| = magnitude of the vectorcardiogram, SD = standard deviation, RMS = root mean square, SecDer = second derivative, Tend = T wave end.

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  Fig 2. Illustration of global QRS onset and local T wave landmarks detection. Global R peak is detected using a Pan-Tompkins algorithm on the ECGRMS signal. The global QRS onset is thereafter detected as a peak in the second derivative of the ECGRMS within a certain window preceding the global R peak. The local T peak (Tpk) is detected as the maximum or minimal peak between R+50ms and R+0.7RR. Thereafter, the tangent trough the point of maximum deflection between Tpk and Tpk+0.3RR is calculated from the first derivative. The intersection between this tangent and the baseline is detected as the local end of the T wave (Tend). Tpk = T-wave peak, Tend = T-wave end, RMS = root mean square, SecDer = second derivative, ms = milliseconds.

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  Fig 3. An example of the results of our algorithm. The QRS onset and global Tend detected by the algorithm is shown for a healthy control and patients with LQT-1, 2 and 3. QTalg = QT-interval determined by the algorithm, μQTobs = mean QT-interval determined by three observers, ms = milliseconds.

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  Fig 4. Validation results of the μQTobs VS QTalg. A linear regression between μQTobs and QTalg. B Bland-Altman analysis shows no bias (solid black line) and narrow limit of agreements (dashed lines). C The Distribution of differences shows that the differences are normally distributed around zero. All numbers corresponding with this figure can be found in Table 2. QTalg = QT-interval determined by the algorithm, μQTobs = mean QT-interval determined by three observers, SD = standard deviation, ms = milliseconds.