Key result
JADE achieves higher fetal ECG extraction accuracy while FastICA processes low-quality signals faster.
Why the study?
Analyzing fetal ECG signals visually is challenging because recorded signals are mixed with weak fetal ECG, maternal ECG, and respiratory noise, requiring automated Blind Source Separation methods.
For extracting fetal ECG from mixed maternal signals, JADE provides higher accuracy, whereas FastICA offers faster computation and robustness to low-quality signals.
Answers are grounded in this paper and cite their sources.
Offers complementary options for fetal ECG extraction; leaves open prospective clinical validation before routine use.
Electrocardiogram (ECG) test is very important for fetus condition inspection so as to avoid stillbirth and neonatal death during pregnancy. It is well known and widely used as a medical tool as it is convenient and non-invasive. Nevertheless, analysing fetal ECG (FECG) signal by using naked eye is tedious as the observed signal is a mixed signal which consists of weak FECG, maternal ECG (MECG) and also other signals including mother’s respiratory noise. Hence, in this paper, Blind Source Separation (BSS) is used to extract the estimated desired signal i.e. FECG from the mixed signal. BSS is a well-known separation method that is able to extract desired signal without knowing any information of the source signal. The aim of this study is to elucidate the performance of BSS algorithms i.e. Fast Fixed-Point for Independent Component Analysis (FastICA), Joint Approximate Diagonalization of Eigenmatrix (JADE) and Principal Component Analysis (PCA) for FECG extraction. We integrate R-peak detection algorithm as a post-separation process to the BSS system in order to distinguish the estimated FECG and MECG for easier analysis process. Estimated signals are evaluated based on waveform characteristics observation and Signal-to Interference Ratio (SIR) parameter. We can conclude that JADE performance performs better in term of accuracy while FastICA is good in term of the computational time. However, FastICA manages to get comparable result as JADE after many fine-tuning steps and it is more flexible compared to JADE as it is not sensitive to low quality input signal.
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Ramli et al. (2020) studied Fetal ECG extraction. Blind Source Separation (BSS) algorithms (FastICA, JADE, PCA) vs. Comparison among algorithms was evaluated on Waveform characteristics observation and Signal-to Interference Ratio (SIR). JADE performed better in accuracy for fetal ECG extraction, while FastICA was faster and more flexible with low-quality input signals after fine-tuning.
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