Various ECG enhancement algorithms, including a filter bank-based approach, were reviewed and compared for their performance in overcoming baseline wander and electromyogram noise during stress tests.
This article reviews published ECG enhancing techniques to overcome baseline wander and electromyogram-induced noise during stress testing.
There are two predominant types of noise that contaminate the electrocardiogram (EGG) acquired during a stress test: the baseline wander noise (BW) and electrode motion artifact, and electromyogram-induced noise (EMG). BW noise is at a lower frequency, caused by respiration and motion of the subject or the leads. The frequency components of BW noise are usually below 0.5 Hz, and extend into the frequency range of the ST segment during a stress test. EMG noise, on the other hand, is predominantly at higher frequencies, caused by increased muscle activity and by mechanical forces acting on the electrodes. The frequency spectrum of the EMG noise overlaps that of the ECG signal and extends even higher in the frequency domain. In this article, the authors review some of the published ECG enhancing techniques to overcome the noise problems, and compare their performance on stress ECG signals under adverse noise scenarios. They also describe the filter bank-based ECG enhancing algorithm.
Afonso et al. (Mon,) conducted a review in Stress ECG noise. ECG enhancement algorithms was evaluated on Performance on stress ECG signals under adverse noise scenarios. Various ECG enhancement algorithms, including a filter bank-based approach, were reviewed and compared for their performance in overcoming baseline wander and electromyogram noise during stress tests.
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