A robust fetal ECG detection method for abdominal recordings

Martens, Suzanne; Rabotti, C.; Mischi, Massimo; Sluijter, R.J.

doi:10.1088/0967-3334/28/4/004

Cited by 155 publications

(119 citation statements)

References 43 publications

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“…All these methods require a template for the mECG time course within one beat cycle estimated from the recorded signal; for this purpose, first the maternal R-peaks are detected in either the ADS or the standard mECG recording by applying some pattern recognition algorithm (Friesen et al, 1990); then, the mECG template is estimated from ADS signal segments around the detected R-peaks. Most of the methods apply some preprocessing steps to remove the baseline wander, the power line interference and the mECG (Taylor et al, 2003;Martens et al, 2007), indicating again the importance of providing valuable methods for noise removing and fECG extraction. An additional standard mECG recording in addition to the abdominal channels will contribute to a more precise detection of the mQRS complex.…”

Section: Signal Processing Methods To Extract the Fetal Ecg And The Umentioning

confidence: 99%

Prenatal Telemedicine – Advances in Fetal Monitoring

Ungureanu¹,

Gussi²,

Wolf³

et al. 2011

Advances in Telemedicine: Applications in Various Medical Disciplines and Geographical Regions

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Section: Signal Processing Methods To Extract the Fetal Ecg And The Umentioning

confidence: 99%

Prenatal Telemedicine – Advances in Fetal Monitoring

Ungureanu¹,

Gussi²,

Wolf³

et al. 2011

Advances in Telemedicine: Applications in Various Medical Disciplines and Geographical Regions

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“…On the other hand, fewer algorithms depend on the singlelead aECG signal; e.g., template subtraction (TS) [13,[23][24][25][26], and its variation based on singular value decomposition (SVD) or principal component analysis [27,28], the time-frequency analysis, like wavelet transform, pseudo-smooth Wigner-Ville distribution [29][30][31][32] (in practice, three aECG channels are averaged in [30]), and S-transform [33], sequential total variation [34], adaptive neuro-fuzzy inference system and extended Kalman filter [35], particle swarm optimization and extended Kalman smoother [36] state space reconstruction via lag map [37,38], etc. We refer the reader to, e.g., Sameni and Clifford [4] and Andreotti et al [39] for a more detailed review.…”

Section: Introductionmentioning

confidence: 99%

Extract Fetal ECG from Single-Lead Abdominal ECG by De-Shape Short Time Fourier Transform and Nonlocal Median

2017

Front. Appl. Math. Stat.

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The multiple fundamental frequency detection problem and the source separation problem from a single-channel signal containing multiple oscillatory components and a nonstationary noise are both challenging tasks. To extract the fetal electrocardiogram (ECG) from a single-lead maternal abdominal ECG, we need to solve both challenges. We propose a novel method to extract the fetal ECG from a single-lead maternal abdominal ECG, without any additional measurement. The algorithm is composed of three components. First, the maternal and fetal heart rates are estimated by the de-shape short time Fourier transform (STFT), which is a recently proposed nonlinear time-frequency analysis technique. The beat tracking technique is the second component which is applied to accurately obtain the maternal and fetal R peaks. The third component consists of establishing the maternal and fetal ECG waveforms by the nonlocal median. The algorithm is tested on two real databases with the annotation provided by experts (adfecgdb database and CinC2013 database) and a simulated database (fecgsym), and provides the state-of-the-art results. We conclude that with the proposed algorithm, the fetal ECG waveform and the fetal heart rate could be accurately obtained from the single-lead maternal abdominal ECG.

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“…Several FECG extraction approaches have produced interesting results: methods based on blind or semi-blind source separation techniques, independent component analysis ( ICA), [1], [2], principal component analysis (PCA) or singular value decomposition (SVD) [3], [4], [5]; average MECG subtraction [6], [7]; different variants of adaptive filters [8], [9], [10]; wavelet decomposition [11].…”

Section: Introductionmentioning

confidence: 99%

Técnicas BSS híbridas para extracción del ECG fetal usando un marco de referencia para pruebas de esfuerzo de algoritmos de extracción

Sarmiento-Álvarez

Millet-Roig

2017

ITECKNE Innovación E Investigación en Ingeniería

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Resumen− La electrocardiografía fetal no invasiva, usa electrodos superficiales puestos sobre el abdomen materno. El reto consiste en extraer la señal fetal de la mezcla abdominal. La Separación Ciega de Fuentes es una forma de hacerlo empleando ya sea ICA o PCA. Los algoritmos COMBI y MULTICOMBI ofrecen un novedoso esquema para combinar ICA y PCA. En este trabajo, se compara el desempeño de los algoritmos COMBI, MUL-TICOMBI, EFICA, WASOBI y los tradicionales JADE e ICA, usando un marco de referencia estándar para la realización de un análisis comparativo y pruebas regulatorias de algoritmos de extracción del electrocardiograma fetal no invasivo. Se usa la medida F1 que combina los picos detectados falsos negativos y falsos positivos para medir la precisión en la detección del complejo fetal QRS. Se llevan a cabo dos experimentos. Uno para determinar el valor de un parámetro de entrada requerido por los algoritmos WASOBI y COMBI, y otro para comparar el desempeño de los algoritmos empleando la medida F1. En el primer experimento se estableció que el orden AR requerido como entrada para COMBI es 10. En el segundo experimento, se obtuvo la precisión media total en la detección del QRS fetal (considerando todos los eventos no estacionarios). Los mejores desempeños en cada grupo fueron 96.4% para COMBI, 95.8% para EFI-CA, 95.2% para JADEICA, 94.6% para PCA, 93,6% para ICAdef, 92.9% para MULTICOMBI, 92,7 para ICAsym, y 89,7% para WASOBI.Palabras clave− FECG, ICA, PCA, pruebas de estrés.Abstract− The non-invasive foetal ECG makes use of surface electrodes placed onto the maternal abdomen. The challenge is to extract the foetal signal from the abdominal mixture. Blind source separation is one way to do this using either ICA or PCA algorithms. COMBI and MULTICOMBI algorithms offer novel schemes for combining ICA and PCA. In this work, the performance of the algorithms COMBI, MULTICOMBI, EFICA, WASOBI and traditional JADE and ICA algorithms are compared, using a standard framework for benchmarking and regulatory testing of NI-FECG extraction algorithms. We use the F1-measure combining true positive, false negative and false positive detected peak for measure the accuracy of FQRS detection. Two experiments were carried out. One to determine a WASOBI algorithm input parameter, also necessary in COMBI, and other to compare performance using F1 measure. In first experiment it was established that the AR order required as input for COMBI is 10. In second experiment, the overall median FQRS detection accuracies (i.e. considering all no stationary events) are obtained. For the best performing methods in each group were 96.4% for COMBI, 95.8% for EFICA, 95.2% for JADEICA, 94.6% for PCA, 93,6% for ICAdef,, 92.9% for MULTICOMBI, 92,7 for ICAsym, and 89,7% for WASOBI.

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A robust fetal ECG detection method for abdominal recordings

Cited by 155 publications

References 43 publications

Prenatal Telemedicine – Advances in Fetal Monitoring

Prenatal Telemedicine – Advances in Fetal Monitoring

Extract Fetal ECG from Single-Lead Abdominal ECG by De-Shape Short Time Fourier Transform and Nonlocal Median

Técnicas BSS híbridas para extracción del ECG fetal usando un marco de referencia para pruebas de esfuerzo de algoritmos de extracción

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