Adaptive filter application in fetal electrocardiography

Zhou, Xiaoqin; Engler, Peter E.; Coblentz, M.G.

doi:10.1109/cbms.1992.245033

Cited by 5 publications

(2 citation statements)

References 27 publications

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“…The LMS algorithm is an iterative technique for minimizing the mean square error (MSE) between the primary input and the reference signal [14]. The Adaptive Filter weights are updated by using the LMS algorithm.…”

Section: The Least Mean Square (Lms) Algorithmmentioning

confidence: 99%

Investigation of Adaptive Filtering for Noise Cancellation inECG signals

Behbahani

2007

Second International Multi-Symposiums on Computer and Computational Sciences (IMSCCS 2007)

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New generation of medical treatment has been supported by computerized processes. Signals recorded from the human body provide valuable information about the biological activities of body organs. The organs' characteristic topologies with temporal and spectral, properties, can be correlated with a normal or pathological function. In response to dynamic changes in the behavior of those organs, the signals exhibit timevarying, non-stationary responses. The signals are always contaminated by a drift and interference caused by several bioelectric phenomena, or by various types of noise, such as intrinsic noise from the recorder and noise from electrode-skin contact. In this paper we utilize Adaptive Filters for noise cancellation and analysis ECG signals.

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Section: The Least Mean Square (Lms) Algorithmmentioning

confidence: 99%

Investigation of Adaptive Filtering for Noise Cancellation inECG signals

Behbahani

2007

Second International Multi-Symposiums on Computer and Computational Sciences (IMSCCS 2007)

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“…Several methods are used in order to extract the fECG signal from the aECG, such as adaptive filtering method [13][14][15], genetic algorithm [16], Singular Value Decomposition (SVD) [11,17], independent component analysis (ICA) [18][19][20][21], and wavelet transform analysis [22,23]. Adaptive filters are divided into two groups, the stochastic gradient approach and the recursive least square algorithms [24].…”

Section: Introductionmentioning

confidence: 99%

Separation of the fetal heart signal in a synchronous network consisting of maternal and fetal hearts

Zandi-Mehran

Golpayegani

2023

Scientia Iranica

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This paper studies the heart's oscillation model to separate fetal and maternal ECGs from abdominal recordings. To this aim, two phases are designed. A Modified version of the Duffing-Van der Pol oscillator is considered a computational heart model in the modeling phase. To evaluate the interaction effects of the maternal and fetal heart and the differences and features of the fetal heart structure, the fetal heart model is Modified based on the maternal heart model. A nonidentical network is employed as an interactive network of the mother and the fetus's heart. Then the degree of the network synchronization is measured with the help of a pattern synchronization index of the non-identical network. An attempt is made to separate the fetal signal from the mother's in abdominal signals in the separation phase. Two problem-solving approaches are explained; the step-by-step mode that calculates the signal at any given moment and the construction of general equations. These approaches end up calculating the variables, which stand for maternal and fetal signal. That makes it possible to achieve the separation of maternal and fetal ECGs.

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Investigation of Fault-Tolerant Adaptive Filtering for Noisy ECG Signals

Zhang

2007

2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing

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Studies shows that Electrocardiogram (ECG) computer programs perform at least equally well as human observers in ECG measurement and coding, and can replace the cardiologist in epidemiological studies and clinical trials [1]. However, in order to also replace the cardiologist in clinical settings, such as for out-patients, better systems are required in order to reduce ambient noise while maintaining signal sensitivity. Therefore the objective of this work was to develop an adaptive filter to remove the contaminating signal in order to better obtain and interpret the electrocardiogram (ECG) data. To achieve reliability, the real-time computing systems must be fault-tolerant. This paper proposed a fault-tolerant adaptive filter for noise cancellation of ECG signals. Comparison of the performance and reliability of non-fault-tolerant and fault-tolerant adaptive filters are performed. Experimental results showed that the fault-tolerant adaptive filter not only successfully extract the ECG signals, but also is very reliable.

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Adaptive filter application in fetal electrocardiography

Cited by 5 publications

References 27 publications

Investigation of Adaptive Filtering for Noise Cancellation inECG signals

Investigation of Adaptive Filtering for Noise Cancellation inECG signals

Separation of the fetal heart signal in a synchronous network consisting of maternal and fetal hearts

Investigation of Fault-Tolerant Adaptive Filtering for Noisy ECG Signals

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