Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence
Great effort has been devoted in recent years to the development of sudden cardiac risk predictors as a function of electric cardiac signals, mainly obtained from the electrocardiogram (ECG) analysis. But these prediction techniques are still seldom used in clinical practice, partly due to its limi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2016-03-01
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| Series: | Frontiers in Physiology |
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| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fphys.2016.00082/full |
| _version_ | 1818162512998170624 |
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| author | Francisco Javier eGimeno-Blanes Manuel eBlanco-Velasco Óscar eBarquero-Pérez Arcadi eGarcía-Alberola José Luis eRojo-Álvarez |
| author_facet | Francisco Javier eGimeno-Blanes Manuel eBlanco-Velasco Óscar eBarquero-Pérez Arcadi eGarcía-Alberola José Luis eRojo-Álvarez |
| author_sort | Francisco Javier eGimeno-Blanes |
| collection | DOAJ |
| description | Great effort has been devoted in recent years to the development of sudden cardiac risk predictors as a function of electric cardiac signals, mainly obtained from the electrocardiogram (ECG) analysis. But these prediction techniques are still seldom used in clinical practice, partly due to its limited diagnostic accuracy and to the lack of consensus about the appropriate computational signal processing implementation. This paper addresses a three-fold approach, based on ECG indexes, to structure this review on sudden cardiac risk stratification. First, throughout the computational techniques that had been widely proposed for obtaining these indexes in technical literature. Second, over the scientific evidence, that although is supported by observational clinical studies, they are not always representative enough. And third, via the limited technology transfer of academy-accepted algorithms, requiring further meditation for future systems. We focus on three families of ECG derived indexes which are tackled from the aforementioned viewpoints, namely, heart rate turbulence, heart rate variability, and T-wave alternans. In terms of computational algorithms, we still need clearer scientific evidence, standardizing, and benchmarking, siting on advanced algorithms applied over large and representative datasets. New scenarios like electronic health recordings, big data, long-term monitoring, and cloud databases, will eventually open new frameworks to foresee suitable new paradigms in the near future. |
| first_indexed | 2024-12-11T16:34:51Z |
| format | Article |
| id | doaj.art-36ce80aa344b435d9b68cc6711005edc |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-12-11T16:34:51Z |
| publishDate | 2016-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-36ce80aa344b435d9b68cc6711005edc2022-12-22T00:58:29ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2016-03-01710.3389/fphys.2016.00082182347Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific EvidenceFrancisco Javier eGimeno-Blanes0Manuel eBlanco-Velasco1Óscar eBarquero-Pérez2Arcadi eGarcía-Alberola3José Luis eRojo-Álvarez4Miguel Hernández UniversityUniversity of AlcaláUniversity Rey Juan CarlosHospital Universitario Virgen de la ArrixacaUniversity Rey Juan CarlosGreat effort has been devoted in recent years to the development of sudden cardiac risk predictors as a function of electric cardiac signals, mainly obtained from the electrocardiogram (ECG) analysis. But these prediction techniques are still seldom used in clinical practice, partly due to its limited diagnostic accuracy and to the lack of consensus about the appropriate computational signal processing implementation. This paper addresses a three-fold approach, based on ECG indexes, to structure this review on sudden cardiac risk stratification. First, throughout the computational techniques that had been widely proposed for obtaining these indexes in technical literature. Second, over the scientific evidence, that although is supported by observational clinical studies, they are not always representative enough. And third, via the limited technology transfer of academy-accepted algorithms, requiring further meditation for future systems. We focus on three families of ECG derived indexes which are tackled from the aforementioned viewpoints, namely, heart rate turbulence, heart rate variability, and T-wave alternans. In terms of computational algorithms, we still need clearer scientific evidence, standardizing, and benchmarking, siting on advanced algorithms applied over large and representative datasets. New scenarios like electronic health recordings, big data, long-term monitoring, and cloud databases, will eventually open new frameworks to foresee suitable new paradigms in the near future.http://journal.frontiersin.org/Journal/10.3389/fphys.2016.00082/fullHeart rate variabilitySudden cardiac deathtechnology transferrisk stratificationheart rate turbulencecomputational algorithms |
| spellingShingle | Francisco Javier eGimeno-Blanes Manuel eBlanco-Velasco Óscar eBarquero-Pérez Arcadi eGarcía-Alberola José Luis eRojo-Álvarez Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence Frontiers in Physiology Heart rate variability Sudden cardiac death technology transfer risk stratification heart rate turbulence computational algorithms |
| title | Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence |
| title_full | Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence |
| title_fullStr | Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence |
| title_full_unstemmed | Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence |
| title_short | Sudden Cardiac Risk Stratification with Electrocardiographic Indices - A Review on Computational Processing, Technology Transfer, and Scientific Evidence |
| title_sort | sudden cardiac risk stratification with electrocardiographic indices a review on computational processing technology transfer and scientific evidence |
| topic | Heart rate variability Sudden cardiac death technology transfer risk stratification heart rate turbulence computational algorithms |
| url | http://journal.frontiersin.org/Journal/10.3389/fphys.2016.00082/full |
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