Matrix analysis
Discrete-time signal processing (2nd ed.)
Discrete-time signal processing (2nd ed.)
Convex Optimization
Advanced Methods And Tools for ECG Data Analysis
Advanced Methods And Tools for ECG Data Analysis
ECG signal denoising and baseline wander correction based on the empirical mode decomposition
Computers in Biology and Medicine
Filter design for cancellation of baseline-fluctuation in needle EMG recordings
Computer Methods and Programs in Biomedicine
Eye Movement Analysis for Activity Recognition Using Electrooculography
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast ECG baseline wander removal preserving the ST segment
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies
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Baseline wander is a low-frequency additive noise affecting almost all bioelectrical signals, in particular the ECG. In this paper, we propose a novel approach to baseline wander estimation and removal for bioelectrical signals, based on the notion of quadratic variation reduction. The quadratic variation is meant as a measure of variability for vectors or sampled functions, and is a consistent measure in this regard. Baseline wander is estimated solving a constrained convex optimization problem where quadratic variation enters as a constraint. The solution depends on a single parameter whose value is not critical, as proven by a sensitivity analysis. Numerical results confirm the effectiveness of the approach, which outperforms state-of-the-art algorithms. The algorithm compares favorably also in terms of computational complexity, which is linear in the size of the vector to detrend. This makes it suitable for real-time applications as well as for applications on devices with reduced computing power, such as handheld devices.