Comparison of Baseline Wander Removal Techniques considering the Preservation of ST Changes in the Ischemic ECG: A
Gustavo Lenis1, Nicolas Pilia1, Axel Loewe1
1Karlsruhe Institute of Technology (KIT), Institute of Biomedical Engineering (IBT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany.
Insights
This study simulated ECG signals to evaluate baseline wander removal filters. Wavelet-based cancellation performed best, but Butterworth high-pass filters offer a practical, accurate alternative for medical use.
Area of Science:
- Cardiovascular physiology
- Biomedical signal processing
Background:
- ST segment changes on ECG are crucial for diagnosing ischemia and infarction.
- Baseline wander is a common artifact that can obscure ST segment analysis, hindering accurate diagnosis.
Purpose of the Study:
- To identify optimal filtering techniques for removing baseline wander from ECG signals.
- To establish a ground truth for ST segment changes before and after artifact removal.
Main Methods:
- A large-scale simulation study encompassing 5.5 million signals from 765 electrophysiological setups.
- Multiscale modeling of the ischemic heart, from myocyte to surface ECG.
- Realistic baseline wander modeling to evaluate five common filtering techniques.
Main Results:
- Wavelet-based baseline cancellation demonstrated superior performance in simulation.
- Butterworth high-pass filters were identified as a computationally efficient and nearly as accurate choice for medical applications.
- All evaluated filtering methods proved superior to unfiltered signals, despite minor ST segment modifications.
Conclusions:
- Effective baseline wander removal is critical for accurate ECG interpretation in ischemic heart disease.
- Wavelet and Butterworth filters offer viable solutions for mitigating baseline wander artifacts.
- Simulations provide a robust method for evaluating ECG signal processing techniques.
Abstract:
The most important ECG marker for the diagnosis of ischemia or infarction is a change in the ST segment. Baseline wander is a typical artifact that corrupts the recorded ECG and can hinder the correct diagnosis of such diseases. 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. 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. We also created a realistic model of baseline wander to evaluate five filtering techniques commonly used in literature. In the simulation study, we included a total of 5.5 million signals coming from 765 electrophysiological setups. We found that the best performing method was the wavelet-based baseline cancellation. However, for medical applications, the Butterworth high-pass filter is the better choice because it is computationally cheap and almost as accurate. Even though all methods modify the ST segment up to some extent, they were all proved to be better than leaving baseline wander unfiltered.
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