An improved morphological approach to background normalization of ECG signals
| Autor: | A. Finkelstein, K. Ibrahim, Qinghua Wu, P. Sun, A.M. Weindling |
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| Rok vydání: | 2003 |
| Předmět: |
Male
Quality Control Computer science Structuring element Speech recognition Biomedical Engineering Normalization (image processing) Mathematical morphology Models Biological QT interval Signal Electrocardiography QRS complex Reference Values Distortion Humans Waveform Computer Simulation cardiovascular diseases Stochastic Processes business.industry Emphasis (telecommunications) Infant Newborn Signal Processing Computer-Assisted Pattern recognition Nonlinear Dynamics Female Artificial intelligence Artifacts business Algorithms Infant Premature |
| Zdroj: | IEEE Transactions on Biomedical Engineering. 50:117-121 |
| ISSN: | 0018-9294 |
| DOI: | 10.1109/tbme.2002.805486 |
| Popis: | This paper describes an improved morphological approach to remove baseline wander from neonatal electrocardiogram (ECG) signals, with particular emphasis on preserving the ST segment of the original signal. The algorithm consists of two stages of morphological processing. First, the QRS complex and impulsive noise component due to skeletal muscle contractions etc., are detected and removed from the input signal. Second, the corrected QT interval (QTc) and RR interval are used to determine a structuring element. With this structuring element, the same morphological operation as in the first stage is then applied to the QRS-removed signal to obtain and remove the baseline wander. The performance of the algorithm is evaluated with simulated and real ECGs. Compared with an existing morphological method, there is a substantial improvement, especially in reducing distortion of the baseline waveform within the PR and QT intervals. |
| Databáze: | OpenAIRE |
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