Screening for congenital heart diseases by murmurs using telemedical phonocardiography

Fodor, Gábor; Balogh, A; Hosszú, Gábor; Kovács, Ferenc

doi:10.1109/embc.2012.6347385

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…Kalman filtering (Adithya et al, 2017) needs accurate reference signal, as it has high computational complexity. Wavelet Transform (Kosa et al, 2008; Kovacs et al, 2011; Fodor et al, 2012; Adithya et al, 2017; Koutsiana et al, 2017), showed good performance in de-nosing noisy fPCG and analyzing the fetal heart sounds (fHS), but it lacks the ability to finely de-noise the overlapped frequency components. Independent Component Analysis (ICA) (Nigam and Priemer, 2004; Jimenez-Gonzalez and James, 2008; Jiménez-Gonzàlez and James, 2010; Jimenez and James, 2013) assumes source components as independent (which is hardly met in case of abdominal sources of sounds) and needs post processing with high computational complexity.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study on Fetal Heart Rates Estimated from Fetal Phonography and Cardiotocography

Ibrahim¹,

Awar

Balayah

et al. 2017

Front. Physiol.

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The aim of this study is to investigate that fetal heart rates (fHR) extracted from fetal phonocardiography (fPCG) could convey similar information of fHR from cardiotocography (CTG). Four-channel fPCG sensors made of low cost (<$1) ceramic piezo vibration sensor within 3D-printed casings were used to collect abdominal phonogram signals from 20 pregnant mothers (>34 weeks of gestation). A novel multi-lag covariance matrix-based eigenvalue decomposition technique was used to separate maternal breathing, fetal heart sounds (fHS) and maternal heart sounds (mHS) from abdominal phonogram signals. Prior to the fHR estimation, the fPCG signals were denoised using a multi-resolution wavelet-based filter. The proposed source separation technique was first tested in separating sources from synthetically mixed signals and then on raw abdominal phonogram signals. fHR signals extracted from fPCG signals were validated using simultaneous recorded CTG-based fHR recordings.The experimental results have shown that the fHR derived from the acquired fPCG can be used to detect periods of acceleration and deceleration, which are critical indication of the fetus' well-being. Moreover, a comparative analysis demonstrated that fHRs from CTG and fPCG signals were in good agreement (Bland Altman plot has mean = −0.21 BPM and ±2 SD = ±3) with statistical significance (p < 0.001 and Spearman correlation coefficient ρ = 0.95). The study findings show that fHR estimated from fPCG could be a reliable substitute for fHR from the CTG, opening up the possibility of a low cost monitoring tool for fetal well-being.

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Section: Introductionmentioning

confidence: 99%

A Comparative Study on Fetal Heart Rates Estimated from Fetal Phonography and Cardiotocography

Ibrahim¹,

Awar

Balayah

et al. 2017

Front. Physiol.

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Initial Field Test of a Cloud-Based Cardiac Auscultation System to Determine Murmur Etiology in Rural China

et al. 2017

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A system for collection, distribution, and long distant, asynchronous interpretation of cardiac auscultation has been developed and field-tested in rural China. We initiated a proof-of-concept test as a critical component of design of a system to allow rural physicians with little experience in evaluation of congenital heart disease (CHD) to obtain assistance in diagnosis and management of children with significant heart disease. The project tested the hypothesis that acceptable screening of heart murmurs could be accomplished using a digital stethoscope and internet cloud transmittal to deliver phonocardiograms to an experienced observer. Of the 7993 children who underwent school-based screening in the Menghai District of Yunnan Province, Peoples Republic of China, 149 had a murmur noted by a screener. They had digital heart sounds and phonocardiograms collected with the HeartLink tele auscultation system, and underwent echocardiography by a cardiology resident from the First Affiliated Hospital of Kunming Medical University. The digital phonocardiograms, stored on a cloud server, were later remotely reviewed by a board-certified American pediatric cardiologist. Fourteen of these subjects were found to have CHD confirmed by echocardiogram. Using the HeartLink system, the pediatric cardiologist identified 11 of the 14 subjects with pathological murmurs, and missed three subjects with atrial septal defects, which were incorrectly identified as venous hum or Still's murmur. In addition, ten subjects were recorded as having pathological murmurs, when no CHD was confirmed by echocardiography during the field study. The overall test accuracy was 91% with 78.5% sensitivity and 92.6% specificity. This proof-of-concept study demonstrated the feasibility of differentiating pathologic murmurs due to CHD from normal functional heart murmurs with the HeartLink system. This field study is an initial step to develop a cost-effective CHD screening strategy in low-resource settings with a shortage of trained medical professionals and pediatric heart programs.

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Prenatal identification of CHD murmur using four segment phonocardiographic signal analysis

Chourasia¹,

Chourasia²,

Mittra³

2016

Journal of Medical Engineering & Technology

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Congenital heart defects (CHD) are one of the utmost birth defects present in the neonatal after birth and a big challenge for the researchers to identify the structural abnormality during the antepartum period. An algorithm is presented here to identify the presence of CHD through foetal phonocardiographic (fPCG) signals. The recorded fPCG is decomposed using Daubechies4 wavelet with sub-level threshold to remove the noise in the signal. The Shannon energy is used to identify the different peaks of signals and then S1 and S2 according to the intervals between adjacent peaks. The signal is segmented into four important parts: S1, S1S2, S2 and S2S1. The FFT is used to identify the frequency component present in four segments which in turn indicates the presence of pathological murmur that may turn into CHD. The algorithm is tested on 25 samples with accuracy rate 88% in identifying the presence of a murmur.

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Screening for congenital heart diseases by murmurs using telemedical phonocardiography

Cited by 3 publications

References 15 publications

A Comparative Study on Fetal Heart Rates Estimated from Fetal Phonography and Cardiotocography

A Comparative Study on Fetal Heart Rates Estimated from Fetal Phonography and Cardiotocography

Initial Field Test of a Cloud-Based Cardiac Auscultation System to Determine Murmur Etiology in Rural China

Prenatal identification of CHD murmur using four segment phonocardiographic signal analysis

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