Precise T-wave endpoint detection using polynomial fitting and natural geometric approach algorithm
QT interval (QT) is defined as the distance between the beginning of the QRS complex and the end of the T-wave, and it reflects the time course of the ventricular depolarization and repolarization on the surface electrocardiogram (ECG). QT and its variability over time are modulated by the autonomic...
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| Veröffentlicht in: | Biomedical signal processing and control Jg. 80; S. 104254 |
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| Abstract | QT interval (QT) is defined as the distance between the beginning of the QRS complex and the end of the T-wave, and it reflects the time course of the ventricular depolarization and repolarization on the surface electrocardiogram (ECG). QT and its variability over time are modulated by the autonomic nervous system and are related to arrhythmogenesis. A challenging task for appropriate QT assessment is the detection of the T-wave endpoint. This study proposes a novel automatic approach to correctly identify the T-wave endpoint. After the peak of the T-wave, it was assumed that the quasi-asymptotical hyperbolic waveform decay of the T-wave acutely bends to meet the ECG baseline and then smooths out onto the TP segment. The point showing the maximal baseline bending is usually assumed by the cardiologists as the T-wave endpoint. In this approach, the terminal portion of the T-wave was represented by a parsimonious-optimal order polynomial function, in which the Cartesian curvature was calculated. One hundred and one ECG records from Physionet QT Database were analyzed to investigate the performance of the method. A Cartesian Curvature-based method (CGM) was developed and applied for automated detection of the T-waves endpoints. Q-waves were also measured automatically. The QTs were calculated and compared with respective cardiologist manual marks provided by QT Database by Pearson's correlation and Bland-Altman charts. High correlation (Pearson's Correlation = 0.94; p < 0.001) between the novel approach and the reference marks, observed in all analyses, showed the method's suitability to identify T-wave endpoints. The CGM performs as the cognitive experience of the cardiologist and has a simple mathematical implementation, indicating to be a promising tool for QT interval assessment. |
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| AbstractList | QT interval (QT) is defined as the distance between the beginning of the QRS complex and the end of the T-wave, and it reflects the time course of the ventricular depolarization and repolarization on the surface electrocardiogram (ECG). QT and its variability over time are modulated by the autonomic nervous system and are related to arrhythmogenesis. A challenging task for appropriate QT assessment is the detection of the T-wave endpoint. This study proposes a novel automatic approach to correctly identify the T-wave endpoint. After the peak of the T-wave, it was assumed that the quasi-asymptotical hyperbolic waveform decay of the T-wave acutely bends to meet the ECG baseline and then smooths out onto the TP segment. The point showing the maximal baseline bending is usually assumed by the cardiologists as the T-wave endpoint. In this approach, the terminal portion of the T-wave was represented by a parsimonious-optimal order polynomial function, in which the Cartesian curvature was calculated. One hundred and one ECG records from Physionet QT Database were analyzed to investigate the performance of the method. A Cartesian Curvature-based method (CGM) was developed and applied for automated detection of the T-waves endpoints. Q-waves were also measured automatically. The QTs were calculated and compared with respective cardiologist manual marks provided by QT Database by Pearson's correlation and Bland-Altman charts. High correlation (Pearson's Correlation = 0.94; p < 0.001) between the novel approach and the reference marks, observed in all analyses, showed the method's suitability to identify T-wave endpoints. The CGM performs as the cognitive experience of the cardiologist and has a simple mathematical implementation, indicating to be a promising tool for QT interval assessment. |
| ArticleNumber | 104254 |
| Author | Winkert, T. Benchimol-Barbosa, P.R. Nadal, J. |
| Author_xml | – sequence: 1 givenname: T. surname: Winkert fullname: Winkert, T. email: thaiswinkert@peb.ufrj.br organization: Biomedical Engineering Program, COPPE Institute, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil – sequence: 2 givenname: P.R. surname: Benchimol-Barbosa fullname: Benchimol-Barbosa, P.R. email: eagar@yahoo.com organization: Biomedical Engineering Program, COPPE Institute, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil – sequence: 3 givenname: J. surname: Nadal fullname: Nadal, J. email: jn@peb.ufrj.br organization: Biomedical Engineering Program, COPPE Institute, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil |
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| Cites_doi | 10.1016/j.medengphy.2012.11.007 10.1109/10.844227 10.1002/clc.4960200326 10.1016/j.compbiomed.2018.02.020 10.1016/j.jelectrocard.2006.05.018 10.1177/2042098612454283 10.1109/TBME.2003.821031 10.1016/j.jacc.2008.12.014 10.1186/1475-925X-10-77 10.1016/S0022-0736(86)80030-9 10.1136/hrt.75.5.498 10.1111/j.1542-474X.1997.tb00325.x 10.4330/wjc.v8.i1.57 10.1016/j.bspc.2019.03.001 10.1016/j.amjcard.2016.09.041 10.1136/hrt.71.4.386 10.1161/JAHA.112.001552 10.1161/CIRCEP.111.962605 10.1016/j.jcp.2010.11.029 10.1007/BF02447064 10.1161/01.CIR.0000145144.56673.59 10.1016/j.jacc.2005.10.024 10.1016/0002-8703(81)90407-5 10.1016/S0010-4809(84)80017-8 10.1109/51.993193 |
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| Keywords | QT interval Automated method ECG CGM TTI RMSD QTM T-wave endpoint Polynomial fitting Cartesian curvature RMS T-wave CGC |
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Arrhythmia Electrophysiol. doi: 10.1161/CIRCEP.111.962605 – volume: 230 start-page: 851 issue: 4 year: 2011 ident: 10.1016/j.bspc.2022.104254_b0080 article-title: On the properties and limitations of the height function method in two-dimensional Cartesian geometry publication-title: J. Comput. Phys. doi: 10.1016/j.jcp.2010.11.029 – volume: 17 start-page: 492 issue: 4 year: 1979 ident: 10.1016/j.bspc.2022.104254_b0095 article-title: Accuracy of QRS detection in relation to the analysis of high-frequency components in the electrocardiogram publication-title: Med. Biol. Eng. 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Heart J. doi: 10.1016/0002-8703(81)90407-5 – volume: 17 start-page: 258 issue: 3 year: 1984 ident: 10.1016/j.bspc.2022.104254_b0135 article-title: The use of cross-correlation function for the alignment of ECG waveforms and rejection of extrasystoles publication-title: Comput. Biomed. Res. doi: 10.1016/S0010-4809(84)80017-8 – volume: 21 start-page: 42 issue: 1 year: 2002 ident: 10.1016/j.bspc.2022.104254_b0130 article-title: The principles of software QRS detection publication-title: IEEE Eng. Med. Biol. Mag. doi: 10.1109/51.993193 |
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| Snippet | QT interval (QT) is defined as the distance between the beginning of the QRS complex and the end of the T-wave, and it reflects the time course of the... |
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| StartPage | 104254 |
| SubjectTerms | Automated method Cartesian curvature Polynomial fitting QT interval T-wave T-wave endpoint |
| Title | Precise T-wave endpoint detection using polynomial fitting and natural geometric approach algorithm |
| URI | https://dx.doi.org/10.1016/j.bspc.2022.104254 |
| Volume | 80 |
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