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Please use this identifier to cite or link to this item: http://dspace.ucuenca.edu.ec/handle/123456789/34255
Title: ECG Multilead QT interval estimation using support vector machines
Authors: Wong de balzan , Sara Null
Cuadrado, Jhosmary
Dugarte, Nelson
Medina, Ruben
Morocho Zurita, Carlos Villie
Vanegas Peralta, Pablo Fernando
metadata.dc.ucuenca.correspondencia: Cuadrado, Jhosmary, jhosmary.cuadros@sansano.usm.cl
Keywords: Interval estimation
Vector machines
Multilead QT
metadata.dc.ucuenca.areaconocimientofrascatiamplio: 2. Ingeniería y Tecnología
metadata.dc.ucuenca.areaconocimientofrascatidetallado: 2.11.2 Otras Ingenierias y Tecnologías
metadata.dc.ucuenca.areaconocimientofrascatiespecifico: 2.11 Otras Ingenierias y Tecnologías
metadata.dc.ucuenca.areaconocimientounescoamplio: 05 - Ciencias Físicas, Ciencias Naturales, Matemáticas y Estadísticas
metadata.dc.ucuenca.areaconocimientounescodetallado: 0511 - Biología
metadata.dc.ucuenca.areaconocimientounescoespecifico: 051 - Ciencias Biológicas y Afines
Issue Date: 2019
metadata.dc.ucuenca.volumen: Volumen 2019
metadata.dc.source: Journal of Healthcare Engineering
metadata.dc.identifier.doi: 10.1155/2019/6371871
metadata.dc.type: ARTÍCULO
Abstract: 
This work reports a multilead QT interval measurement algorithm for a high-resolution digital electrocardiograph. The software enables off-line ECG processing including QRS detection as well as an accurate multilead QT interval detection algorithm using support vector machines (SVMs). Two fiducial points ( and ) are estimated using the SVM algorithm on each incoming beat. This enables segmentation of the current beat for obtaining the P, QRS, and T waves. The QT interval is estimated by updating the QT interval on each lead, considering shifting techniques with respect to a valid beat template. The validation of the QT interval measurement algorithm is attained using the Physionet PTB diagnostic ECG database showing a percent error of with respect to the database annotations. The usefulness of this software tool is also tested by considering the analysis of the ECG signals for a group of 60 patients acquired using our digital electrocardiograph. In this case, the validation is performed by comparing the estimated QT interval with respect to the estimation obtained using the Cardiosoft software providing a percent error of .
Description: 
This work reports a multilead QT interval measurement algorithm for a high-resolution digital electrocardiograph. The software enables off-line ECG processing including QRS detection as well as an accurate multilead QT interval detection algorithm using support vector machines (SVMs). Two fiducial points ( and ) are estimated using the SVM algorithm on each incoming beat. This enables segmentation of the current beat for obtaining the P, QRS, and T waves. The QT interval is estimated by updating the QT interval on each lead, considering shifting techniques with respect to a valid beat template. The validation of the QT interval measurement algorithm is attained using the Physionet PTB diagnostic ECG database showing a percent error of with respect to the database annotations. The usefulness of this software tool is also tested by considering the analysis of the ECG signals for a group of 60 patients acquired using our digital electrocardiograph. In this case, the validation is performed by comparing the estimated QT interval with respect to the estimation obtained using the Cardiosoft software providing a percent error of .
URI: http://dspace.ucuenca.edu.ec/handle/123456789/34255
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85065251764&origin=inward
metadata.dc.ucuenca.urifuente: https://www.hindawi.com/journals/jhe/contents/year/2019
ISSN: 2040-2295
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