Heart Artifact Removal in Electrohysterography Measurements Using Algebraic Differentiators

TL;DR

This paper introduces a novel algebraic differentiator-based method for removing ECG artifacts from electrohysterography signals, improving the accuracy of uterine contraction monitoring without needing auxiliary ECG references.

Contribution

The study develops a model-free, algebraic differentiator approach for ECG artifact removal in EHG signals, enhancing signal quality while preserving physiological features.

Findings

Effective ECG artifact suppression demonstrated on multichannel EHG recordings.

Outperforms traditional template subtraction methods in accuracy.

Preserves signal shape outside cardiac pulse locations.

Abstract

Electrohysterography (EHG) enables non-invasive monitoring of uterine contractions but can be contaminated by electrocardiogram (ECG) artifacts. This work presents an ECG removal method using algebraic differentiators, a control-theoretic tool for model-free derivative estimation, that preserves signal shape outside the detected cardiac pulse locations. The differentiator parameters are designed to simultaneously suppress slow physiological artifacts and powerline interference while maximizing output signal-to-noise ratio. Cross-channel clustering distinguishes cardiac pulses from localized artifacts, enabling accurate pulse subtraction without auxiliary ECG references. Implemented as a causal FIR filter, the method is validated on multichannel EHG recordings from female and male subjects and compared to the template subtraction method.