A Baseline Wander Tracking System for Artifact Rejection in Long-Term Electrocardiography

Area of Science:

• Biomedical Engineering
• Signal Processing

Background:

• Long-term electrocardiogram (ECG) monitoring is crucial for diagnosing cardiac conditions.
• Physical activity introduces motion artifacts and baseline wander, degrading ECG signal quality.
• Existing methods struggle with strong baseline disturbances and analog front-end saturation.

Purpose of the Study:

• To present a novel algorithm, baseline wander tracking (BWT), for robustly handling baseline disturbances in long-term ECG signals.
• To enable accurate ECG reconstruction and filtering despite significant signal artifacts.
• To develop a method suitable for low-power, high-integration wearable ECG systems.

Main Methods:

• The baseline wander tracking (BWT) algorithm shifts the ECG signal's baseline to the center of the dynamic input range.
• Fast offset shifts generate steep signal portions, allowing offline reconstruction and filtering.
• Monte Carlo simulations were used to evaluate reconstruction errors and signal-to-error ratios.

Main Results:

• Reconstruction errors were primarily attributed to digital-to-analog converter (DAC) non-linearity.
• BWT demonstrated a higher signal-to-error ratio compared to traditional analog front-ends for signals >15 mV.
• The algorithm effectively suppresses electrode offset potentials without introducing prolonged transients.

Conclusions:

• BWT is a computationally efficient and memory-light algorithm suitable for long-term, low-power ECG recording.
• Its structural simplicity and DC coupling capability facilitate high integration in wearable devices.
• The method provides a reliable approach to mitigate motion artifacts and baseline wander in ambulatory ECG monitoring.