Finding Morphology Points of Electrocardiographic-Signal Waves Using Wavelet Analysis
| Autor: | N. Yu. Zolotykh, Alexander V. Nikolskiy, Alena I. Kalyakulina, V. A. Moskalenko, M. V. Ivanchenko, I. I. Yusipov, Artem A. Kozlov |
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| Rok vydání: | 2019 |
| Předmět: |
Signal Processing (eess.SP)
Physics Nuclear and High Energy Physics Astronomy and Astrophysics Statistical and Nonlinear Physics Base (topology) Quantitative Biology - Quantitative Methods 01 natural sciences Signal Predictive value 010305 fluids & plasmas Electronic Optical and Magnetic Materials Wavelet FOS: Biological sciences Algorithmic efficiency 0103 physical sciences FOS: Electrical engineering electronic engineering information engineering Electrical Engineering and Systems Science - Signal Processing Electrical and Electronic Engineering 010306 general physics Sensitivity (electronics) Algorithm Quantitative Methods (q-bio.QM) |
| Zdroj: | Radiophysics and Quantum Electronics. 61:689-703 |
| ISSN: | 1573-9120 0033-8443 |
| DOI: | 10.1007/s11141-019-09929-2 |
| Popis: | A new algorithm has been developed for delineation of significant points of various electrocardiographic signal (ECG) waves, taking into account information from all available leads and providing similar or higher accuracy in comparison with other modern technologies. The test results for the QT database show a sensitivity above 97% when detecting ECG wave peaks and 96% for their onsets and offsets, as well as better positive predictive value compared to the previously known algorithms. In contrast to the previously published algorithms, the proposed approach also allows one to determine the morphology of waves. The segmentation mean errors of all significant points are below the tolerances defined by the Committee of General Standards for Electrocardiography (CSE). Comment: Submitted to Radiophysics and Quantum Electronics |
| Databáze: | OpenAIRE |
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