Abstract
This paper presents a new non-invasive deterministic algorithm of extracting the fetal Electrocardiogram (FECG) signal based on a new null space idempotent transformation matrix (NSITM). The mixture matrix is used to compute the ITM. Then, the fetal ECG (FECG) and maternal ECG (MECG) signals are extracted from the null space of the ITM. Next, MECG and FECG peaks detection, control logic, and adaptive comb filter are used to remove the unwanted MECG component from the raw FECG signal, thus extracting a clean FECG signal. The visual results from Daisy and Physionet real databases indicate that the proposed algorithm is effective in extracting the FECG signal, which can be compared with principal component analysis (PCA), fast independent component analysis (FastICA), and parallel linear predictor (PLP) filter algorithms. Results from Physionet synthesized ECG data show considerable improvement in extraction performances over other algorithms used in this work, considering different additive signal-to-noise ratio (SNR) increasing from 0 dB to 12 dB, and considering different fetal-to-maternal SNR increasing from −30 dB to 0 dB. The FECG detection of the NSITM is evaluated using statistical measures and results show considerable improvement in the sensitivity (SE), the accuracy (ACC), and the positive predictive value (PPV), as compared with other algorithms. The study demonstrated that the NSITM is a feasible algorithm for FECG extraction.
Highlights
The electrocardiogram (ECG) signal, in a non-invasive method, incorporates of the maternal ECG (MECG) signal, the fetal ECG (FECG) signal, and several sources of interference, such as power line interference, baseline wander, motion artifact, fetal brain activity, muscle artifact, as well as noise, such as instrumentation noise [1,2,3]
The visualization on the results indicates that the proposed null space idempotent transformation matrix (NSITM) algorithm, the principal component analysis (PCA) algorithm, the fast independent component analysis (FastICA), and parallel linear predictor (PLP) algorithms are effective in extracting the FECG and MECG signals from the ECG mixture
The proposed NSITM algorithm is effective in extracting the FECG and MECG signals from the ECG mixture
Summary
The electrocardiogram (ECG) signal, in a non-invasive method, incorporates of the maternal ECG (MECG) signal, the fetal ECG (FECG) signal, and several sources of interference, such as power line interference, baseline wander, motion artifact, fetal brain activity, muscle artifact, as well as noise, such as instrumentation noise [1,2,3]. FECG extraction and enhancement method requires the elimination of the MECG as well as optimal detection of the FECG. The frequencies of both signals are a few Hertz’s and are possibly overlapping. Separating them using the conventional linear filter fails. To address this problem, a large number of FECG extraction algorithms have been proposed over the past few decades. A large number of FECG extraction algorithms have been proposed over the past few decades Some of these algorithms were based on the blind source separation (BSS) or blind source extraction (BSE)
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