An adaptive integrated algorithm for noninvasive fetal ECG separation and noise reduction based on ICA-EEMD-WS

Liu, Guangchen; Luan, Yihui

doi:10.1007/s11517-015-1389-1

Cited by 49 publications

(39 citation statements)

References 39 publications

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“…These components include the electromyographic signal, residual noise and artefacts. Among the different approaches proposed for fECG extraction, BSS is one of the most commonly applied [24,25,26,27,28,29,40]. It attempts to decompose the multichannel abdominal mixture into the different components i.e., mECG, fECG and noise.…”

Section: Methodsmentioning

confidence: 99%

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A Combined Independent Source Separation and Quality Index Optimization Method for Fetal ECG Extraction from Abdominal Maternal Leads

Billeci

Varanini

2017

Sensors

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The non-invasive fetal electrocardiogram (fECG) technique has recently received considerable interest in monitoring fetal health. The aim of our paper is to propose a novel fECG algorithm based on the combination of the criteria of independent source separation and of a quality index optimization (ICAQIO-based). The algorithm was compared with two methods applying the two different criteria independently—the ICA-based and the QIO-based methods—which were previously developed by our group. All three methods were tested on the recently implemented Fetal ECG Synthetic Database (FECGSYNDB). Moreover, the performance of the algorithm was tested on real data from the PhysioNet fetal ECG Challenge 2013 Database. The proposed combined method outperformed the other two algorithms on the FECGSYNDB (ICAQIO-based: 98.78%, QIO-based: 97.77%, ICA-based: 97.61%). Significant differences were obtained in particular in the conditions when uterine contractions and maternal and fetal ectopic beats occurred. On the real data, all three methods obtained very high performances, with the QIO-based method proving slightly better than the other two (ICAQIO-based: 99.38%, QIO-based: 99.76%, ICA-based: 99.37%). The findings from this study suggest that the proposed method could potentially be applied as a novel algorithm for accurate extraction of fECG, especially in critical recording conditions.

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Section: Methodsmentioning

confidence: 99%

“…Commonly used approaches are PCA or SVD [24,25] and Independent Component Analysis (ICA) [26,27,28]. …”

Section: Introductionmentioning

confidence: 99%

A Combined Independent Source Separation and Quality Index Optimization Method for Fetal ECG Extraction from Abdominal Maternal Leads

Billeci

Varanini

2017

Sensors

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“…In this section, we introduce our method on ECG preprocessing and enhancement. The task in this procedure is to split the ECG waves into segments according to the cardiac cycle [28] and then take them as data points for training our models. As described in Section 1, QRS complex is responsible for the activities of ventricular depolarization and repolarization, it has morphologically higher amplitude and sharper peak than other components such as P-wave and T-wave.…”

Section: Ecg Preprocessing and Enhancementmentioning

confidence: 99%

Electrocardiogram Recognization Based on Variational AutoEncoder

Chen¹,

Meng²,

Qing³

2018

Machine Learning and Biometrics

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Subtle distortions on electrocardiogram (ECG) can help doctors to diagnose some serious larvaceous heart sickness on their patients. However, it is difficult to find them manually because of disturbing factors such as baseline wander and high-frequency noise. In this chapter, we propose a method based on variational autoencoder to distinguish these distortions automatically and efficiently. We test our method on three ECG datasets from Physionet by adding some tiny artificial distortions. Comparing with other approaches adopting autoencoders [e.g., contractive autoencoder, denoising autoencoder (DAE)], the results of our experiment show that our method improves the performance of publically available on ECG analysis on the distortions.

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“…The main one is low signal to noise ratio. Fetal noninvasive ECG extraction from maternal abdominal wall requires blind source separation and adaptive noise cancellation techniques application in the software [ 7 – 11 ]. Most of the fetal noninvasive ECG databases were obtained by magnetocardiographic registration.…”

Section: A Due Diagnosticmentioning

confidence: 99%

The Use of Fetal Noninvasive Electrocardiography

Лахно

2016

Scientifica

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Preeclampsia (PE) is one of the severe complications of pregnancy that leads to fetal deterioration. The aim was to survey the validity of fetal distress diagnostics in case of Doppler ultrasonic umbilical vein and arteries blood flow velocity investigation and ECG parameters analysis obtained from maternal abdominal signal before labor in preeclamptic patients. Fetal noninvasive ECG and umbilical arterial and venous Doppler investigation were performed in 120 patients at 34–40 weeks of gestation. And 30 of them had physiological gestation and were involved in Group I. In Group II 52 pregnant women with mild-moderate PE were observed. 38 patients with severe PE were monitored in Group III. The most considerable negative correlation was determined in pair Apgar score 1 versus T/QRS (R = −0.50; p < 0.05). So the increased T/QRS ratio was the most evident marker of fetal distress. Fetal noninvasive ECG showed sensitivity of 96.6% and specificity of 98.4% and, therefore, was determined as more accurate method for fetal monitoring.

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An adaptive integrated algorithm for noninvasive fetal ECG separation and noise reduction based on ICA-EEMD-WS

Cited by 49 publications

References 39 publications

A Combined Independent Source Separation and Quality Index Optimization Method for Fetal ECG Extraction from Abdominal Maternal Leads

A Combined Independent Source Separation and Quality Index Optimization Method for Fetal ECG Extraction from Abdominal Maternal Leads

Electrocardiogram Recognization Based on Variational AutoEncoder

The Use of Fetal Noninvasive Electrocardiography

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