Investigation of blind source separation methods for extraction of fetal ECG

Ananthanag, K.V.K.; Sahambi, J. S.

doi:10.1109/ccece.2003.1226312

Cited by 16 publications

(11 citation statements)

References 14 publications

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“…In this line stands the FastICA algorithm [18] and EFICA [16]. ICA-based methods are the most used for the analysis of AECG [19], [20] because it is considered that the sources are predominantly non-Gaussian and statistically independent of one another.…”

Section: Blind Source Separationmentioning

confidence: 99%

Fetal electrocardiogram extraction using hybrid BSS technique: COMBI and MULTICOMBI algorithms

Sarmiento-Álvarez¹,

Millet-Roig²,

González-Salvador³

2014

Iteckne

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Abstract-In this paper, we use two algorithms for obtaining fetal ECG from abdominal ECG. The algorithms are MULTICOM-BI and COMBI, which are a combination of EFICA and WASOBI algorithms. The performance of the algorithms COMBI, MUL-TICOMBI, WASOBI, EFICA and traditional JADE algorithm are compared. A semi synthetic database and two actual databases are used to compare the performance of algorithms using as parameter the signal to error ratio SER. It is found that the COMBI and MULTICOMBI algorithms show better performance than the JADE, EFICA and WASOBI algorithms.Keywords-Abdominal ECG, COMBI, fetal ECG, MULTICOMBI, SER, SIR.Resumen-En este artículo se emplean dos algoritmos para obtener el ECG fetal a partir del ECG abdominal. Los algoritmos son MULTICOMBI and COMBI, los cuales son una combinación de los algoritmos EFICA y WASOBI. SE compara el desempeño de los algoritmos COMBI, MULTICOMBI, WASOBI, EFICA y el tradicional algoritmo de JADE. Para comparar el desempeño de los algoritmos se usa una base de datos semi-sintética y dos bases de datos reales usando como parámetro la relación señal a error SER. Se encuentra que los algoritmos COMBI y MULTICOMBI muestran mejor desempeño que los algoritmos JADE, EFICA y WASOBI.Palabras claves -Abdominal ECG, COMBI, fetal ECG, MULTI-COMBI, SER, SIR.

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Section: Blind Source Separationmentioning

confidence: 99%

Fetal electrocardiogram extraction using hybrid BSS technique: COMBI and MULTICOMBI algorithms

Sarmiento-Álvarez¹,

Millet-Roig²,

González-Salvador³

2014

Iteckne

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“…The basic assumption of ICA is "statistical independence" of the sources. Different bioelectric current sources correspond to different bioelectric mechanisms, and so without loss of generality we can assume them to be statistically independent [7].…”

Section: B Bss-ica Algorithm Approachmentioning

confidence: 99%

“…We therefore propose the use of synthetic data, which facilitates SNR as the objective measure to evaluate the schemes. For synthetic data, a MATLAB function [7], [13] has been developed to generate MECG, FECG, abdominal signal and three thoracic signals by taking two signals (101.dat and 102.dat) from MIT-BIH arrhythmia database [15]. To simulate noisy abdominal recording gaussian noise with different values of SN Rf n (FECG to gaussian noise ratio) has been added in clean abdominal recording.…”

Section: B Synthetic Signalsmentioning

confidence: 99%

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A novel approach to fetal ECG extraction and enhancement using blind source separation (BSS-ICA) and adaptive fetal ECG enhancer (AFE)

Gupta

Srivastava

Khandelwal

2007

2007 6th International Conference on Information, Communications &Amp; Signal Processing

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Eight out of one thousand born live infants have some form of heart defect, making it the single most common class of congenital abnormalities. Identification of these cases during early pregnancy reduces risks by timely treatment or planned de- livery. The non-invasive Fetal ECG (FECG) monitoring by means of abdominal surface electrodes provides valuable information about the cardiac electrical activity of fetus. In this paper, analysis and comparative study of Four channel Adaptive Maternal ECG Canceller-Adaptive Fetal ECG Enhancer (FAMC-AFE) and BlindSource Separation (BSS-ICA) methods are presented. Th-ese methods have been applied to real multichannel ECG recordings obtained from a pregnant woman's skin and synthetic biomedical signals. After investigation of the results the BSS-ICA AFE approach, proposed by us, has been shown to be superior for extraction and enhancement of fetal ECG compared to other BSS scheme.

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“…In transabdominal potential recordings, the lowpower FECG is hidden in a mixture of several high-power sources, mainly ascribable to the maternal physiological interferences (ECG, EMG, respiration) and to the instrumental noises. It is well known that the original sources cannot be separated using traditional frequency domain filters due to the spectral overlap between the different sources [2]. The only methods giving recognized good results are based on adaptive filtering or Blind Source Separation (BSS) algorithms, the latter usually providing better results than the former at the expenses of an increased complexity [3].…”

Section: Introductionmentioning

confidence: 99%

A DSP algorithm and system for real-time fetal ECG extraction

Pani

Argiolas

Raffo

2008

2008 Computers in Cardiology

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Fetal ECG (FECG) IntroductionNon-invasive FECG aims to provide ECG traces representing the fetal heart activity in early and late pregnancy comparable with those achievable on adult subjects. Even with all the limitations posed by the indirect recording [1], a morphological analysis can be carried out to identify fetal pathologies and set up a therapeutic intervention in time. In transabdominal potential recordings, the lowpower FECG is hidden in a mixture of several high-power sources, mainly ascribable to the maternal physiological interferences (ECG, EMG, respiration) and to the instrumental noises. It is well known that the original sources cannot be separated using traditional frequency domain filters due to the spectral overlap between the different sources [2]. The only methods giving recognized good results are based on adaptive filtering or Blind Source Separation (BSS) algorithms, the latter usually providing better results than the former at the expenses of an increased complexity [3].To cope with the lack of real-time ICA algorithms able to provide results with a quality comparable with the batch ones, we developed a block-on-line algorithm, OL-JADE, based on the famous JADE algorithm [4], able to give the same quality of the original batch algorithm joined with the tracking ability of an on-line one. Since this kind of processing is targeted for real-time clinic examinations, we also proposed a real-time implementation on a floating point DSP [5]. The critical issue of the algorithm is the permutation ambiguity (due to the mathematical formulation of the problem) since it may lead to a blockby-block scrambling of the separated sources. In this paper this problem, partially addressed in the formulation of the on-line algorithm, is studied on real mixtures, providing further information and possible solutions, along with comparisons with the original batch approach. MethodsICA aims to find a linear transformation that minimizes the statistical dependence between the components of a random vector. When it represents the mixture of more unknown independent source signals, and the mixing process is also unknown, ICA can be used to find a good estimate of the sources, thus acting as a BSS algorithm.OL-JADE is a block-on-line version of the famous JADE [4] algorithm, which consists of a Second Order Statistics (SOS) stage providing centering and whitening of the original signal mixtures, followed by a Higher Order Statistics (HOS) stage. Whitening decorrelates and orthogonalizes the original mixtures, reducing the number of parameters to estimate, so that only a rotation, provided by the HOS stage, is then required to identify the independent sources [6]. JADE is a batch algorithm, working on a segment of data of interest containing enough statistical information on the independent components to perform the separation. This means that both the SOS and HOS stages are performed off-line. The HOS stage obtains higher-order independence by multiplying decorrelated mixtures by an orthogonal rotation ...

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Investigation of blind source separation methods for extraction of fetal ECG

Cited by 16 publications

References 14 publications

Fetal electrocardiogram extraction using hybrid BSS technique: COMBI and MULTICOMBI algorithms

Fetal electrocardiogram extraction using hybrid BSS technique: COMBI and MULTICOMBI algorithms

A novel approach to fetal ECG extraction and enhancement using blind source separation (BSS-ICA) and adaptive fetal ECG enhancer (AFE)

A DSP algorithm and system for real-time fetal ECG extraction

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