Key result
A wavelet transform-based algorithm was effective for distinguishing normal ECGs from those with myocardial ischemic episodes using data from the European ST-T change database.
Why the study?
Can a wavelet transform-based algorithm effectively detect myocardial ischemic episodes from ECG signals?
Can a wavelet transform-based algorithm effectively detect myocardial ischemic episodes from ECG signals?
A wavelet transform-based algorithm can effectively distinguish ischemic from normal ECG patterns.
Hypothesis-generating for wavelet-based ischemia detection; requires prospective validation before clinical adoption.
In this paper, we propose an algorithm for detection of myocardial ischemic episodes from electrocardiogram (ECG) signal using the wavelet transform technique. The algorithm was tested on data from the European ST-T change database. Results show that this algorithm is effective for distinguishing normal ECGs from ischemic. We developed a method that uses wavelets for extracting ECG patterns that are characteristic for myocardial ischemia.
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Mohammad Karimi Moridani (2009) studied Myocardial ischemia. Wavelet transform algorithm vs. Normal ECGs was evaluated on Detection of myocardial ischemic episodes. A wavelet transform-based algorithm was effective for distinguishing normal ECGs from those with myocardial ischemic episodes using data from the European ST-T change database.
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