Fetal Heart Beat detection based on Empirical Mode Decomposition, Signal Quality Indices and Correlation Analysis

The purpose of fetal monitoring during childbirth is the early recognition of any pathological conditions to guide a clinician in early intervention to avoid any complication in the health of the fetus. Non-Invasive Fetal Electrocardiography (NIFECG) represents an alternative fetal monitoring technique. The fetal ECG (fECG) derived from maternal thoracic and abdominal ECG recordings, provides an alternative to typical embryo monitoring means. In addition, it allows for long-term and ambulatory registrations that broaden the diagnostic capabilities for assessing the fetal health. However, in real situations, clear fECG is difficult to extract because it is usually overwhelmed by the dominant maternal ECG and other contaminated noise such as baseline wander and high-frequency interference. In this paper, a novel integrated adaptive methodology based on the combination of blind source separation, empirical mode decomposition, wavelet shrinkage denoising and correlation analysis, for the non-invasive extraction and processing of the FECG, is proposed. The methodology has been evaluated using both real and simulated recordings, and the obtained results indicate it efficiently.