Heart Artifact Removal in Electrohysterography Measurements Using Algebraic Differentiators
This work addresses artifact removal in EHG measurements for improved monitoring of uterine contractions, presenting an incremental method that does not require auxiliary ECG references.
The paper tackled the problem of removing ECG artifacts from electrohysterography (EHG) signals to monitor uterine contractions non-invasively, using algebraic differentiators to preserve signal shape and suppress interference, and validated it on multichannel recordings with comparisons to template subtraction.
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.