A novel approach for phonocardiographic signals processing to make possible fetal heart rate evaluations

Chourasia, Vijay S.; Tiwari, Anil Kumar; Gangopadhyay, R.

doi:10.1016/j.dsp.2014.03.009

Cited by 38 publications

(20 citation statements)

References 31 publications

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“…Chourasia et al [2] depicted a non-intrusive, versatile, and reasonable antenatal care framework utilizing fetal phonocardiography (FPCG). The FPCG method can possibly allow minimal effort and long-term diagnostics to the underserved populace.…”

Section: Related Workmentioning

confidence: 99%

“…Monitoring of fetal heart rate (FHR) patterns is a method developed for fetal reconnaissance and offers vital data about the soundness of the unborn [2]. Securing of fetal electrocardiogram (fECG) becomes a demanding task because immediate contact over the fetus can cause shock [8].…”

Section: Introductionmentioning

confidence: 99%

“…Currently, fECG examination is utilized as a part of the clinical work-up to investigate heart rate and associated factors [8]. Quick FHR estimation by phonocardiography guarantees a precise estimation of beats and pulsation interval [2].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Efficient Adaptive Filter for Fetal ECG Extraction Using Neural Network

Kaleem¹,

Kokate²

2019

Journal of Intelligent Systems

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Fetal electrocardiogram checking is a strategy for acquiring critical data about the state of the fetus during pregnancy and labor. This is done by measuring electrical signals created by the fetal heart as measured from multichannel potential recordings on the mother’s body surface. In any case, extraction of fetal signal is difficult because the signal is marred by the mother’s heartbeat signal. Subsequently, in this paper, a powerful versatile filtering strategy is utilized to eliminate the mother’s heartbeat signal with the specific end goal of extricating the fetal signal. The proposed procedure was executed in the working stage of MATLAB and the execution results were investigated.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Efficient Adaptive Filter for Fetal ECG Extraction Using Neural Network

Kaleem¹,

Kokate²

2019

Journal of Intelligent Systems

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show abstract

“…Matched filtering or other denoising techniques can be used before the envelope detection and autocorrelation step to improve the accuracy of FHR measurement. Methods using S1 heart sound positions determines the FHR by locating the S1 heart sound in the signal [9,10,11,12]. The heart sounds are repetitive in nature, therefore a method which describes tracking these frequency repetition to determine the heart rate and tested in the noisy environment using the simulated data from the physionet is proposed by Tang.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Envelope Detection and Signal Normalization Methods for Foetal Heart Rate Extraction from Foetal Heart Sound

Arora

2018

2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)

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Foetal heart rate is an important indicator of foetal well-being which indicates fetal distress during antepartum and intrapartum period. This paper provides systematic comparison of four different methods envelope detection and four different methods of signal normalization to determine the fetal heart rate from fetal heart sound. To obtain the ground truth, each heart beat was manually identified by visualizing the sound recording on a computer screen. Four different measure of error are used compare various combinations of envelop detection and normalization methods. It is found that the homomorphic filtering gave highest accuracy. Choice of normalization methods did not affect accuracy measurement in most cases.

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“…This new technique makes long-term and frequent measurements of FHR possible. They detected the burst shaped heart sounds from signal envelope and estimated FHR via the time difference of heart sound occurrence [8][9][10][11][12][13][14][15][16]. Consequently, the accuracy of FHR estimation relies on heart sound detection rate.…”

Section: Introductionmentioning

confidence: 99%

Fetal Heart Rate Monitoring from Phonocardiograph Signal Using Repetition Frequency of Heart Sounds

Tang

Qiu

et al. 2016

Journal of Electrical and Computer Engineering

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As a passive, harmless, and low-cost diagnosis tool, fetal heart rate (FHR) monitoring based on fetal phonocardiography (fPCG) signal is alternative to ultrasonographic cardiotocography. Previous fPCG-based methods commonly relied on the time difference of detected heart sound bursts. However, the performance is unavoidable to degrade due to missed heart sounds in very low signal-to-noise ratio environments. This paper proposes a FHR monitoring method using repetition frequency of heart sounds. The proposed method can track time-varying heart rate without both heart sound burst identification and denoising. The average accuracy rate comparison to benchmark is 88.3% as the SNR ranges from −4.4 dB to −26.7 dB.

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A novel approach for phonocardiographic signals processing to make possible fetal heart rate evaluations

Cited by 38 publications

References 31 publications

An Efficient Adaptive Filter for Fetal ECG Extraction Using Neural Network

An Efficient Adaptive Filter for Fetal ECG Extraction Using Neural Network

Comparison of Envelope Detection and Signal Normalization Methods for Foetal Heart Rate Extraction from Foetal Heart Sound

Fetal Heart Rate Monitoring from Phonocardiograph Signal Using Repetition Frequency of Heart Sounds

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