Matrix analysis
Enhancing the precision of ECG baseline correction selective filtering and removal of residual error
Computers and Biomedical Research
Convex Optimization
Advanced Methods And Tools for ECG Data Analysis
Advanced Methods And Tools for ECG Data Analysis
Total Removal of Baseline Drift from ECG Signal
ICCTA '07 Proceedings of the International Conference on Computing: Theory and Applications
ECG signal denoising and baseline wander correction based on the empirical mode decomposition
Computers in Biology and Medicine
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Baseline wander removal is an unavoidable preprocessing step in ECG signal analysis. Unfortunately, the in-band nature of this kind of noise makes its removal difficult without affecting ECG waveform, in particular the ST segment. This is a portion of the ECG with high clinical relevance, as it is related to the diagnosis of acute coronary syndromes. The ST segment is highly susceptible to distortion when baseline removal is performed affecting the low-frequency region of ECG spectrum, where are concentrated the harmonic components that mainly contribute to the shape of the ST segment. In this paper, we propose to tackle the problem of baseline removal from a different perspective, considering the quadratic variation as an alternative measure of variability not directly related to the frequency domain. In this regard, we recently proposed a novel baseline removal algorithm based on quadratic variation reduction. In this paper, we assess its performance with respect to the distortion of the ST segment comparing it to state-of-the-art algorithms. Simulation results confirm the effectiveness of the approach based on quadratic variation reduction. Our algorithm outperforms state-of-the-art algorithms tailored to minimize distortion of the ST segment. Moreover, it compares favorably also in terms of computational complexity, which is linear in the size of the vector to detrend. This makes it suitable also for real-time applications.