Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring
Noise and artifacts are inherent contaminating components and are particularly present in Holter electrocardiogram (ECG) monitoring. The presence of noise is even more significant in long-term monitoring (LTM) recordings, as these are collected for several days in patients following their daily acti...
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| Format: | Article |
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MDPI AG
2017-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/17/11/2448 |
| _version_ | 1798026802287869952 |
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| author | Estrella Everss-Villalba Francisco Manuel Melgarejo-Meseguer Manuel Blanco-Velasco Francisco Javier Gimeno-Blanes Salvador Sala-Pla José Luis Rojo-Álvarez Arcadi García-Alberola |
| author_facet | Estrella Everss-Villalba Francisco Manuel Melgarejo-Meseguer Manuel Blanco-Velasco Francisco Javier Gimeno-Blanes Salvador Sala-Pla José Luis Rojo-Álvarez Arcadi García-Alberola |
| author_sort | Estrella Everss-Villalba |
| collection | DOAJ |
| description | Noise and artifacts are inherent contaminating components and are particularly present in Holter electrocardiogram (ECG) monitoring. The presence of noise is even more significant in long-term monitoring (LTM) recordings, as these are collected for several days in patients following their daily activities; hence, strong artifact components can temporarily impair the clinical measurements from the LTM recordings. Traditionally, the noise presence has been dealt with as a problem of non-desirable component removal by means of several quantitative signal metrics such as the signal-to-noise ratio (SNR), but current systems do not provide any information about the true impact of noise on the ECG clinical evaluation. As a first step towards an alternative to classical approaches, this work assesses the ECG quality under the assumption that an ECG has good quality when it is clinically interpretable. Therefore, our hypotheses are that it is possible (a) to create a clinical severity score for the effect of the noise on the ECG, (b) to characterize its consistency in terms of its temporal and statistical distribution, and (c) to use it for signal quality evaluation in LTM scenarios. For this purpose, a database of external event recorder (EER) signals is assembled and labeled from a clinical point of view for its use as the gold standard of noise severity categorization. These devices are assumed to capture those signal segments more prone to be corrupted with noise during long-term periods. Then, the ECG noise is characterized through the comparison of these clinical severity criteria with conventional quantitative metrics taken from traditional noise-removal approaches, and noise maps are proposed as a novel representation tool to achieve this comparison. Our results showed that neither of the benchmarked quantitative noise measurement criteria represent an accurate enough estimation of the clinical severity of the noise. A case study of long-term ECG is reported, showing the statistical and temporal correspondences and properties with respect to EER signals used to create the gold standard for clinical noise. The proposed noise maps, together with the statistical consistency of the characterization of the noise clinical severity, paves the way towards forthcoming systems providing us with noise maps of the noise clinical severity, allowing the user to process different ECG segments with different techniques and in terms of different measured clinical parameters. |
| first_indexed | 2024-04-11T18:41:10Z |
| format | Article |
| id | doaj.art-c9cdbd20b9dc4062a5d383ef1a0fdb43 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:41:10Z |
| publishDate | 2017-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c9cdbd20b9dc4062a5d383ef1a0fdb432022-12-22T04:08:58ZengMDPI AGSensors1424-82202017-10-011711244810.3390/s17112448s17112448Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG MonitoringEstrella Everss-Villalba0Francisco Manuel Melgarejo-Meseguer1Manuel Blanco-Velasco2Francisco Javier Gimeno-Blanes3Salvador Sala-Pla4José Luis Rojo-Álvarez5Arcadi García-Alberola6Cardiology Service, Arrhythmia Unit, Hospital General Universitario Virgen de la Arrixaca, El Palmar, Murcia 30120, SpainCardiology Service, Arrhythmia Unit, Hospital General Universitario Virgen de la Arrixaca, El Palmar, Murcia 30120, SpainDepartment of Signal Theory and Communications, University of de Alcalá, Alcalá de Henares, Madrid 28805, SpainDepartment of Signal Theory and Communications, Miguel Hernández University, Elche, Alicante 03202, SpainInstituto de Neurociencias, Miguel Hernández University–CSIC, Alicante 03550, SpainDepartment of Signal Theory and Communications, Rey Juan Carlos University, Fuenlabrada, Madrid 28943, SpainCardiology Service, Arrhythmia Unit, Hospital General Universitario Virgen de la Arrixaca, El Palmar, Murcia 30120, SpainNoise and artifacts are inherent contaminating components and are particularly present in Holter electrocardiogram (ECG) monitoring. The presence of noise is even more significant in long-term monitoring (LTM) recordings, as these are collected for several days in patients following their daily activities; hence, strong artifact components can temporarily impair the clinical measurements from the LTM recordings. Traditionally, the noise presence has been dealt with as a problem of non-desirable component removal by means of several quantitative signal metrics such as the signal-to-noise ratio (SNR), but current systems do not provide any information about the true impact of noise on the ECG clinical evaluation. As a first step towards an alternative to classical approaches, this work assesses the ECG quality under the assumption that an ECG has good quality when it is clinically interpretable. Therefore, our hypotheses are that it is possible (a) to create a clinical severity score for the effect of the noise on the ECG, (b) to characterize its consistency in terms of its temporal and statistical distribution, and (c) to use it for signal quality evaluation in LTM scenarios. For this purpose, a database of external event recorder (EER) signals is assembled and labeled from a clinical point of view for its use as the gold standard of noise severity categorization. These devices are assumed to capture those signal segments more prone to be corrupted with noise during long-term periods. Then, the ECG noise is characterized through the comparison of these clinical severity criteria with conventional quantitative metrics taken from traditional noise-removal approaches, and noise maps are proposed as a novel representation tool to achieve this comparison. Our results showed that neither of the benchmarked quantitative noise measurement criteria represent an accurate enough estimation of the clinical severity of the noise. A case study of long-term ECG is reported, showing the statistical and temporal correspondences and properties with respect to EER signals used to create the gold standard for clinical noise. The proposed noise maps, together with the statistical consistency of the characterization of the noise clinical severity, paves the way towards forthcoming systems providing us with noise maps of the noise clinical severity, allowing the user to process different ECG segments with different techniques and in terms of different measured clinical parameters.https://www.mdpi.com/1424-8220/17/11/2448noise mapsECGnoise clinical severityHolterexternal event recorderlong-term monitoringnoise bars |
| spellingShingle | Estrella Everss-Villalba Francisco Manuel Melgarejo-Meseguer Manuel Blanco-Velasco Francisco Javier Gimeno-Blanes Salvador Sala-Pla José Luis Rojo-Álvarez Arcadi García-Alberola Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring Sensors noise maps ECG noise clinical severity Holter external event recorder long-term monitoring noise bars |
| title | Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring |
| title_full | Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring |
| title_fullStr | Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring |
| title_full_unstemmed | Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring |
| title_short | Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring |
| title_sort | noise maps for quantitative and clinical severity towards long term ecg monitoring |
| topic | noise maps ECG noise clinical severity Holter external event recorder long-term monitoring noise bars |
| url | https://www.mdpi.com/1424-8220/17/11/2448 |
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