R-peaks detection based on stationary wavelet transform
| Autor: | M. Merah, B.H. Larbi, T.A. Abdelmalik |
|---|---|
| Přispěvatelé: | Laboratoire Signaux et Images (LSI), Université des sciences et de la Technologie d'Oran Mohamed Boudiaf [Oran] (USTO MB), Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201 (LAMIH), Université de Valenciennes et du Hainaut-Cambrésis (UVHC)-Centre National de la Recherche Scientifique (CNRS)-INSA Institut National des Sciences Appliquées Hauts-de-France (INSA Hauts-De-France), Université Abdelhamid Ibn Badis de Mostaganem |
| Rok vydání: | 2015 |
| Předmět: |
Stationary wavelet transform
Health Informatics Signal [SPI.AUTO]Engineering Sciences [physics]/Automatic Electrocardiography QRS complex Humans Mathematics Decimation business.industry Detector Reproducibility of Results Wavelet transform Signal Processing Computer-Assisted Pattern recognition Computer Science Applications Maxima and minima Anomaly detection Artificial intelligence business Algorithms Software |
| Zdroj: | Computer Methods and Programs in Biomedicine Computer Methods and Programs in Biomedicine, Elsevier, 2015, 121 (3), pp.149-160. ⟨10.1016/j.cmpb.2015.06.003⟩ |
| ISSN: | 0169-2607 |
| DOI: | 10.1016/j.cmpb.2015.06.003 |
| Popis: | International audience; Automatic detection of the QRS complexes/R-peaks in an electrocardiogram (ECG) signal is the most important step preceding any kind of ECG processing and analysis. The performance of these systems heavily relies on the accuracy of the QRS detector. The objective of present work is to drive a new robust method based on stationary wavelet transform (SWT) for R-peaks detection. The decimation of the coefficients at each level of the transformation algorithm is omitted, more samples in the coefficient sequences are available and hence a better outlier detection can be performed. Using the information of local maxima, minima and zero crossings of the fourth SWT coefficient detail, the proposed algorithm identifies the significant points for detection and delineation of the QRS complexes, as well as detection and identification of the QRS individual waves peaks of the pre-processed ECG signal.Various experimental results show that the proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, achieving excellent performance on different databases, on the MIT-BIH database (Se = 99.84%, P = 99.88%), on the QT Database (Se = 99.94%, P = 99.89%) and on MIT-BIH Noise Stress Test Database, (Se = 95.30%, P = 93.98%). Reliability and accuracy are close to the highest among the ones obtained in other studies. Experiments results being satisfactory, the SWT may represent a novel QRS detection tool, for a robust ECG signal analysis. |
| Databáze: | OpenAIRE |
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