3/20/2023 0 Comments Baseline artifact meaningThe majority of baseline wander removal techniques have in common that they cancel the low frequency components of the ECG signal. Hence, baseline drift must be removed and, as a matter of fact, it is a standard signal processing step in many devices or postprocessing algorithms. The signals presented in this figure were retrieved from the Physionet database. The ST depression is reduced because of too strong filtering. (b) ECG recording with a clear ST depression before (blue) and after (red) high-pass filtering. Yet, the filtering process can modify the signal as seen in (b). The removal of this artifact is necessary when diagnosing a change in the ST segment. (a) ECG recording corrupted by baseline wander. However, the observation of those changes becomes difficult if the ECG baseline is not constant. This test should be terminated immediately if, among other criteria, significant ST changes appear in the ECG. The idea behind this procedure is to measure the response of the heart to exercise on a treadmill and to study coronary circulation in comparison to resting conditions. A further situation, where baseline wander becomes critical for the diagnosis of an ST change, is cardiac stress testing. This decision is often taken in a preclinical, out-of-hospital scenario with little or no infrastructural noise control. Therefore, even minor fluctuations in baseline can lead to the decision if a patient is classified as STEMI or non-STEMI and thus influence the therapeutic approach dramatically. The guidelines for diagnosis of myocardial ischemia are based on specific, small changes in the ST segment. Baseline wander is a low frequency artifact in the ECG that arises from breathing, electrically charged electrodes, or subject movement and can hinder the detection of these ST changes because of the varying electrical isoline (Figure 1(a)). Notorious changes in the ST segment (elevation or depression) are the most important ECG marker when dealing with acute coronary syndrome caused by ischemia or mycardial infarction. Even though all methods modify the ST segment up to some extent, they were all proved to be better than leaving baseline wander unfiltered. However, for medical applications, the Butterworth high-pass filter is the better choice because it is computationally cheap and almost as accurate. We found that the best performing method was the wavelet-based baseline cancellation. In the simulation study, we included a total of 5.5 million signals coming from 765 electrophysiological setups. We also created a realistic model of baseline wander to evaluate five filtering techniques commonly used in literature. In order to create the desired reference, we used a large simulation study that allowed us to represent the ischemic heart at a multiscale level from the cardiac myocyte to the surface ECG. For the purpose of finding the best suited filter for the removal of baseline wander, the ground truth about the ST change prior to the corrupting artifact and the subsequent filtering process is needed. Baseline wander is a typical artifact that corrupts the recorded ECG and can hinder the correct diagnosis of such diseases. The most important ECG marker for the diagnosis of ischemia or infarction is a change in the ST segment.
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