2013
DOI: 10.1016/j.medengphy.2012.11.007
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New approach for T-wave peak detection and T-wave end location in 12-lead paced ECG signals based on a mathematical model

Abstract: -This paper presents an innovative approach for T-wave peak detection and subsequent T-wave end location in 12-lead paced ECG signals based on a mathematical model of a skewed Gaussian function. Following the stage of QRS segmentation, we establish search windows using a number of the earliest intervals between each QRS offset and subsequent QRS onset. Then, we compute a template based on a Gaussian-function, modified by a mathematical procedure to insert asymmetry, which models the Twave. Cross-correlation an… Show more

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Cited by 48 publications
(27 citation statements)
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“…The surface ECGs were exported at 16-bit digital resolution for analysis in custom software written in MATLAB version R2009a (Mathworks, Natick, USA) by WBN, with further work to refine the software by Madeiro et al 14 The timing of the QRS onset, T wave peak (Tp) and T wave end (Te) were analysed automatically, and all data points were manually verified by WBN. The R2I2 is derived using ECG surrogates for the APD (ie, QRS onset to T wave peak (QTp) and DI (ie, T wave peak to QRS onset (TpQ)).…”
Section: Methodsmentioning
confidence: 99%
“…The surface ECGs were exported at 16-bit digital resolution for analysis in custom software written in MATLAB version R2009a (Mathworks, Natick, USA) by WBN, with further work to refine the software by Madeiro et al 14 The timing of the QRS onset, T wave peak (Tp) and T wave end (Te) were analysed automatically, and all data points were manually verified by WBN. The R2I2 is derived using ECG surrogates for the APD (ie, QRS onset to T wave peak (QTp) and DI (ie, T wave peak to QRS onset (TpQ)).…”
Section: Methodsmentioning
confidence: 99%
“…The QRS, P and T waves detection is a perfect example, we can cite [1][2][3][4]. Some methods are based on sparse derivatives [5], on mathematical model [6], peak detection [7], on nonlinear transform [8], on slope estimation [9,10], on filtering [11], on correlation analysis [12]. Some algorithms are based on the wavelet transform because ECG signals are intrinsically nonstationary.…”
Section: Introductionmentioning
confidence: 99%
“…Body surface signals (BSPs) are sampled at 1 kHz and pre-processed with a 2 nd order Savitzky-Golay filter with cut-off frequency at 150 Hz [7], notch filter at 60 Hz [8]. Baseline wandering is removed by subtracting the output of a second order Lynn's lowpass filter from the delayed output [5], eliminating frequencies below 0.26 Hz.…”
Section: Electrocardiographic Analysesmentioning
confidence: 99%
“…The 12-lead ECG was obtained from the BSPs. Segmentation consists of selecting 4 consecutive beats and then identifying the peaks and onset-offset from the P, QRS and T waves throughout recently validated methods [6,7,8]. Leads 48 and 49 are also considered to show correlation with left atrium activity [9].…”
Section: -Lead Ecg Segmentationmentioning
confidence: 99%