Towards Intelligent Fetal ECG Signal Extraction and Abnormal Heart Rate Detection from Maternal Signals

Electrical & Electronic Engineering

In monitoring fetal health, accurately assessing the fetal heart rate is crucial. However, extracting clear fetal ECG signals from the maternal abdomen, where electrodes are typically placed, presents challenges due to interference from maternal ECG signals and noise. This paper presents a straightforward method to overcome this challenge and obtain high-quality fetal ECG signals. The proposed method utilizes an LMS adaptive filter to effectively extract fetal ECG signals, resulting in accurate estimation of the fetal heart rate with minimal error. By setting appropriate threshold values and detecting R-R peaks, the fetal heart rate can be reliably determined, enabling the classification of abnormalities. The Pan & Tompkins algorithm is employed to detect QRS complexes, further refining the accuracy of the heart rate calculation. Through this approach, the fetal heart rate can be promptly assessed, allowing for immediate identification of both regular and irregular heart rhythms. This method offers a practical solution for real-time fetal monitoring, facilitating timely intervention when abnormalities are detected.

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