Application of phonocardiography on preterm infants with patent ductus arteriosus

Balogh, A; Kovács, Ferenc

doi:10.1016/j.bspc.2011.05.009

Cited by 12 publications

(17 citation statements)

References 10 publications

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“…A number of attempts have been made to differentiate normal and abnormal heart sounds in an adult [ 20 , 34 ] and paediatric populations [ 21 ] with various algorithms developed and features investigated. A few attempts to address a similar problem in a neonatal population [ 23 , 24 ] have concluded that the PCG assessment with ML was possible with several statistically significant features identified. However, these studies have been performed on a small cohort of newborns, and a human reference point was not provided.…”

Section: Discussionmentioning

confidence: 99%

“…This shows the unrealistically good score, which will not be achieved in practice on unseen patients. In practice, the algorithm is expected to perform on unseen patients [ 18 , 21 , 22 , 23 , 24 , 34 ]. However, these results can indicate the performance of the model for patients with follow-ups.…”

Section: Discussionmentioning

confidence: 99%

“…A single recommendation has to be made for a patient who requires an algorithmic approach to aggregate over multiple information sources. Each feature was averaged across multiple cycles [ 23 ] to ensure that every cardiac cycle equally contributes to patient representation. Dynamic time warping has been used in [ 24 ], before feature extraction, to select the best-cycle to ensure that the chosen audio sample reflects the overall patient characteristics and does not contain outliers due to respiratory or movement artefacts, or other sources of occasional undesired noises.…”

Section: Discussionmentioning

confidence: 99%

“…Even fewer works have addressed the problem of automated interpretation of PCG in newborns. A statistical analysis of various features was performed towards automated detection of PDA murmur in a small cohort of 25 preterm infants [ 23 ]. Differentiation between healthy and pathological heart murmurs in newborns with a set of basic audio features, and an SVM classifier was performed with the main emphasis on automated PCG segmentation, denoising, and cycle selection [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

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A Framework for AI-Assisted Detection of Patent Ductus Arteriosus from Neonatal Phonocardiogram

et al. 2021

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The current diagnosis of Congenital Heart Disease (CHD) in neonates relies on echocardiography. Its limited availability requires alternative screening procedures to prioritise newborns awaiting ultrasound. The routine screening for CHD is performed using a multidimensional clinical examination including (but not limited to) auscultation and pulse oximetry. While auscultation might be subjective with some heart abnormalities not always audible it increases the ability to detect heart defects. This work aims at developing an objective clinical decision support tool based on machine learning (ML) to facilitate differentiation of sounds with signatures of Patent Ductus Arteriosus (PDA)/CHDs, in clinical settings. The heart sounds are pre-processed and segmented, followed by feature extraction. The features are fed into a boosted decision tree classifier to estimate the probability of PDA or CHDs. Several mechanisms to combine information from different auscultation points, as well as consecutive sound cycles, are presented. The system is evaluated on a large clinical dataset of heart sounds from 265 term and late-preterm newborns recorded within the first six days of life. The developed system reaches an area under the curve (AUC) of 78% at detecting CHD and 77% at detecting PDA. The obtained results for PDA detection compare favourably with the level of accuracy achieved by an experienced neonatologist when assessed on the same cohort.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Framework for AI-Assisted Detection of Patent Ductus Arteriosus from Neonatal Phonocardiogram

et al. 2021

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“…The mean (SD) difference between HR measurements by this digital stethoscope and ECG was 7.4 (24) beats min -1 . The digital stethoscope is more inaccurate compared to ECG and PO; however, it obtains an HR faster, with a median (IQR) time to the first HR display of 2 (1-7) s. Balogh and Kovács [40] also described a digital stethoscope that can be connected to a laptop which they used to assess parameters of patent ductus arteriosus in preterm infants. There are several new technologies on the horizon; however, before they can be translated into clinical routine they have to be vigorously studied.…”

Section: Potential Future Developmentsmentioning

confidence: 99%

Heart Rate Assessment Immediately after Birth

et al. 2015

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Background: Heart rate assessment immediately after birth in newborn infants is critical to the correct guidance of resuscitation efforts. There are disagreements as to the best method to measure heart rate. Objective: The aim of this study was to assess different methods of heart rate assessment in newborn infants at birth to determine the fastest and most accurate method. Methods: PubMed, EMBASE and Google Scholar were systematically searched using the following terms: ‘infant', ‘heart rate', ‘monitoring', ‘delivery room', ‘resuscitation', ‘stethoscope', ‘auscultation', ‘palpation', ‘pulse oximetry', ‘electrocardiogram', ‘Doppler ultrasound', ‘photoplethysmography' and ‘wearable sensors'. Results: Eighteen studies were identified that described various methods of heart rate assessment in newborn infants immediately after birth. Studies examining auscultation, palpation, pulse oximetry, electrocardiography and Doppler ultrasound as ways to measure heart rate were included. Heart rate measurements by pulse oximetry are superior to auscultation and palpation, but there is contradictory evidence about its accuracy depending on whether the sensor is connected to the infant or the oximeter first. Several studies indicate that electrocardiogram provides a reliable heart rate faster than pulse oximetry. Doppler ultrasound shows potential for clinical use, however future evidence is needed to support this conclusion. Conclusion: Heart rate assessment is important and there are many measurement methods. The accuracy of routinely applied methods varies, with palpation and auscultation being the least accurate and electrocardiogram being the most accurate. More research is needed on Doppler ultrasound before its clinical use.

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A Noninvasive Continuous Fetal Heart Rate Monitoring System for Mobile Healthcare Based on Fetal Phonocardiography

Zhang

Huang

et al. 2018

Internet of Things

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Application of phonocardiography on preterm infants with patent ductus arteriosus

Cited by 12 publications

References 10 publications

A Framework for AI-Assisted Detection of Patent Ductus Arteriosus from Neonatal Phonocardiogram

A Framework for AI-Assisted Detection of Patent Ductus Arteriosus from Neonatal Phonocardiogram

Heart Rate Assessment Immediately after Birth

A Noninvasive Continuous Fetal Heart Rate Monitoring System for Mobile Healthcare Based on Fetal Phonocardiography

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