Iterative method to derive an approximate matched filter template for fetal electrocardiogram signals

Area of Science:

• Biomedical Engineering
• Signal Processing

Background:

• Fetal electrocardiogram (FECG) signals extracted from the maternal abdomen suffer from low signal-to-noise ratios.
• Accurate R-wave detection in FECG is crucial for fetal monitoring but challenging due to signal degradation.

Purpose of the Study:

• To develop and evaluate an iterative digital filtering method for R-wave detection in simulated FECG signals.
• To assess the performance and noise resilience of the proposed method compared to traditional matched filtering.

Main Methods:

• A digital low-pass filter with a triangular impulse response was applied to simulated FECG complexes.
• An average of detected R-wave locations was used as an adaptive template for subsequent filtering iterations.
• The iterative approach was compared against a pure matched filter in terms of R-wave detection accuracy.

Main Results:

• The iterative filtering method demonstrated competitive effectiveness in detecting R-wave locations.
• The technique's performance was evaluated under increasing levels of signal noise.
• The proposed method showed resilience to noise, maintaining detection accuracy.

Conclusions:

• The iterative filtering technique offers a viable and robust alternative for R-wave detection in low-SNR FECG signals.
• This method provides an effective approach for FECG analysis without requiring prior knowledge of the QRS complex shape.
• The study highlights the potential of adaptive filtering for improving fetal monitoring diagnostics.