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On the Beat Detection Performance in Long-Term ECG Monitoring Scenarios

Título :
On the Beat Detection Performance in Long-Term ECG Monitoring Scenarios
Autor :
Melgarejo Meseguer, Francisco Manuel  
EVERSS, ESTRELLA  
Gimeno Blanes, Francisco Javier  
Blanco-Velasco, Manuel  
Molins Bordallo, Zaida  
Flores Yepes, Jose Antonio  
Rojo-Álvarez, José Luis  
García-Alberola, Arcadi  
Editor :
MDPI
Departamento:
Departamentos de la UMH::Ingeniería de Comunicaciones
Fecha de publicación:
2018-04
URI :
https://hdl.handle.net/11000/30601
Resumen :
Despite the wide literature on R-wave detection algorithms for ECG Holter recordings, the long-term monitoring applications are bringing new requirements, and it is not clear that the existing methods can be straightforwardly used in those scenarios. Our aim in this work was twofold: First, we scrutinized the scope and limitations of existing methods for Holter monitoring when moving to long-term monitoring; Second, we proposed and benchmarked a beat detection method with adequate accuracy and usefulness in long-term scenarios. A longitudinal study was made with the most widely used waveform analysis algorithms, which allowed us to tune the free parameters of the required blocks, and a transversal study analyzed how these parameters change when moving to different databases. With all the above, the extension to long-term monitoring in a database of 7-day Holter monitoring was proposed and analyzed, by using an optimized simultaneous-multilead processing. We considered both own and public databases. In this new scenario, the noise-avoid mechanisms are more important due to the amount of noise that exists in these recordings, moreover, the computational efficiency is a key parameter in order to export the algorithm to the clinical practice. The method based on a Polling function outperformed the others in terms of accuracy and computational efficiency, yielding 99.48% sensitivity, 99.54% specificity, 99.69% positive predictive value, 99.46% accuracy, and 0.85% error for MIT-BIH arrhythmia database. We conclude that the method can be used in long-term Holter monitoring systems.
Palabras clave/Materias:
QRS detection
ECG
long-term monitoring
Holter
7-day
Tipo documento :
application/pdf
Derechos de acceso:
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI :
https://doi.org/10.3390/s18051387
Aparece en las colecciones:
Artículos Ingeniería Comunicaciones



Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.