Extraction of fetal electrocardiogram using H ∞ adaptive algorithms

Puthusserypady, Sadasivan

doi:10.1007/s11517-007-0235-5

Cited by 15 publications

(6 citation statements)

References 34 publications

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“…It is often necessary to analyse characteristics of the MECG and FECG to obtain corresponding prior or posterior information, so as to establish a basic function model to extract the FECG. At present, the single-channel methods include the template subtraction (TS) method [6][7][8][9][10], adaptive filtering [11][12][13], wavelet transform, Wigner-Ville distribution [14][15][16][17], S-transform [18], sequential total variation [19], adaptive neuro-fuzzy reasoning system, extended Kalman Filtering [20], etc. However, unreasonable ECG modeling or selection of a different base function may affect FECG extraction results, which often leads to distortion of extraction and loss of nonlinear and nonstationary characteristics.…”

Section: Introductionmentioning

confidence: 99%

An Instantaneous Correlation Coefficient and Simplified Coherent Averaging Method for Single-Channel Foetal ECG Extraction

Zhang¹,

Wei²

2020

Applied Sciences

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In this paper, an instantaneous correlation coefficient and simplified coherent averaging method for single-channel foetal ECG (FECG) extraction is proposed. The instantaneous correlation coefficient is used to determine the position of the R peak of the measured ECG signal, and the simplified coherent averaging method is used to extract the main information of the ECG signal. The loss of the nonlinear and nonstationary characteristics by coherent averaging is recovered by threshold processing of the residual signal. The FECG signal extraction is performed in three steps. In the first step, the main information of the maternal electrocardiogram (MECG) is extracted from the abdomen electrocardiogram (AECG) signal by means of the instantaneous correlation coefficient and simplified coherent averaging method, and then the noisy FECG is obtained by subtracting the MECG obtained by simplified coherent averaging from the AECG. The second step is to extract the main information of the FECG by applying the instantaneous correlation coefficient and simplified coherent averaging method to the noisy FECG. The remaining signal is obtained by subtracting the simplified coherent averaging FECG from the noisy FECG. Thirdly, the threshold method is utilised to remove MECG residual noise and random gross value noise from the remaining signal to extract the nonlinear and nonstationary information, and the final FECG extraction is obtained by adding the nonlinear and nonstationary information to the simplified coherent averaging FECG. The validity of the proposed method is verified by experiments using synthetic data and real database data. FECG extracted by the method has the advantages of clear QRS complex wave, reasonable enhancement of P wave and T wave morphology, and no loss of nonlinear and nonstationary characteristics.

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Section: Introductionmentioning

confidence: 99%

An Instantaneous Correlation Coefficient and Simplified Coherent Averaging Method for Single-Channel Foetal ECG Extraction

Zhang¹,

Wei²

2020

Applied Sciences

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“…Several methods for processing and extraction of fetal ECG signals have been proposed in the literature [10]. Adaptive filtering [3,11], single value decomposition (SVD) method [12], artificial neural network (ANN) [13], wavelet transform [14], kalman filter [15], fuzzy logic approach [16] and independent component analysis [17,18] are most suggested studies in literature. Each method proposed in the literature has some advantages and disadvantages.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Extraction of Fetal Electrocardiogram Signal with Adaptive Filtering Using Differential Evolution Algorithm

Koçkanat¹,

Kockanat²

2018

Cumhuriyet Science Journal

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Recent studies have demonstrated the advantages of fetal electrocardiogram (ECG) extraction and analysis. In this study, a new approach is proposed for fetal ECG signal extraction using differential evolution algorithm and adaptive filtering. The results obtained by the proposed approach are compared with the result of the adaptive method based on the least mean square method in the literature. According to the obtained results, the proposed approach gives better results in terms of fetal ECG signal extraction.

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“…Adaptive filtering [3,4] is a simple and fast approach for FECG extraction, and conventional adaptive filtering is based on training an adaptive filter to remove the MECG using a maternal reference signal. However, the fetal ECG extracted using this algorithm is still influenced by the maternal ECG and other disturbances.…”

Section: Introductionmentioning

confidence: 99%

Single-Lead Fetal ECG Extraction Based on a Parallel Marginalized Particle Filter

Zhao

Tong

Deng

et al. 2017

Sensors

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This paper presents a novel method for extracting the fetal ECG (FECG) from a single-lead abdominal signal. A dynamical model for a modified abdominal signal is proposed, in which both the maternal ECG (MECG) and the FECG are modeled, and then a parallel marginalized particle filter (par-MPF) is used for tracking the abdominal signal. Finally, the FECG and MECG are simultaneously separated. Several experiments are conducted using both simulated and clinical signals. The results indicate that the method proposed in this paper effectively extracts the FECG and outperforms other Bayesian filtering algorithms.

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Extraction of fetal electrocardiogram using H ∞ adaptive algorithms

Cited by 15 publications

References 34 publications

An Instantaneous Correlation Coefficient and Simplified Coherent Averaging Method for Single-Channel Foetal ECG Extraction

An Instantaneous Correlation Coefficient and Simplified Coherent Averaging Method for Single-Channel Foetal ECG Extraction

Analysis and Extraction of Fetal Electrocardiogram Signal with Adaptive Filtering Using Differential Evolution Algorithm

Single-Lead Fetal ECG Extraction Based on a Parallel Marginalized Particle Filter

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