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Short-time regularity assessment of fibrillatory waves from the surface ECG in atrial fibrillation
- Source :
- RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, instname
- Publication Year :
- 2012
-
Abstract
- This paper proposes the first non-invasive method for direct and short-time regularity quantification of atrial fibrillatory (f) waves from the surface ECG in atrial fibrillation (AF). Regularity is estimated by computing individual morphological variations among f waves, which are delineated and extracted from the atrial activity (AA) signal, making use of an adaptive signed correlation index. The algorithm was tested on real AF surface recordings in order to discriminate atrial signals with different organization degrees, providing a notably higher global accuracy (90.3%) than the two non-invasive AF organization estimates defined to date: the dominant atrial frequency (70.5%) and sample entropy (76.1%). Furthermore, due to its ability to assess AA regularity wave to wave, the proposed method is also able to pursue AF organization time course more precisely than the aforementioned indices. As a consequence, this work opens a new perspective in the non-invasive analysis of AF, such as the individualized study of each f wave, that could improve the understanding of AF mechanisms and become useful for its clinical treatment.<br />The authors are grateful to Drs Javier Vinas, Elio Martin and Alejandro Vazquez for their contribution to classify blindly the AF episodes used in this work. This work was supported by the projects TEC2010-20633 from the Spanish Ministry of Science and Innovation and PPII11-0194-8121 and PII1C09-0036-3237 from Junta de Comunidades de Castilla-La Mancha.
- Subjects :
- Signal processing
medicine.medical_specialty
Time Factors
Physiology
Surface Properties
Biomedical Engineering
Biophysics
Wavelet Analysis
F wave
TECNOLOGIA ELECTRONICA
Surface ecg
Electrocardiography
Wavelet
Physiology (medical)
Internal medicine
Atrial Fibrillation
medicine
Humans
Waveform morphology
Mathematics
medicine.diagnostic_test
ECG
Atrial fibrillation
Signal Processing, Computer-Assisted
medicine.disease
Fibrillatory wave regularity
Sample entropy
Time course
Cardiology
Subjects
Details
- ISSN :
- 13616579
- Volume :
- 33
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- Physiological measurement
- Accession number :
- edsair.doi.dedup.....a33d7bd23525683d4946c33b30d1fcb9