Acoustic analysis of neonatal breath sounds using digital stethoscope technology.


Journal

Pediatric pulmonology
ISSN: 1099-0496
Titre abrégé: Pediatr Pulmonol
Pays: United States
ID NLM: 8510590

Informations de publication

Date de publication:
03 2020
Historique:
received: 03 09 2019
accepted: 27 12 2019
pubmed: 10 1 2020
medline: 21 10 2020
entrez: 10 1 2020
Statut: ppublish

Résumé

There is no published literature regarding the use of the digital stethoscope (DS) and computerized breath sound analysis in neonates, despite neonates experiencing a high burden of respiratory disease. We aimed to determine if the DS could be used to study breath sounds of term and preterm neonates without respiratory disease, and detect a difference in acoustic characteristics between them. A commercially available DS was used to record breath sounds of term and preterm neonates not receiving respiratory support between 24 and 48 hours after birth. Recordings were extracted, filtered, and computer analysis performed to obtain power spectra and mel frequency cepstral coefficient (MFCC) profiles. Recordings from 26 term and 26 preterm infants were obtained. The preterm cohort had an average gestational age (median and interquartile range) of 32 (31-33) weeks and term 39 (38-39) weeks. Birth weight (mean and SD) was 1767 (411) g for the preterm and 3456 (442) g for the term cohort. Power spectra demonstrated the greatest power in the low-frequency range of 100 to 250 Hz for both groups. There were significant differences (P < .05) in the average power at low (100-250 Hz), medium (250-500 Hz), high (500-1000 Hz), and very high (1000-2000 Hz) frequency bands. MFCC profiles also demonstrated significant differences between groups (P < .05). It is feasible to use DS technology to analyze breath sounds in neonates. DS was able to determine significant differences between the acoustic characteristics of term and preterm infants breathing in room air. Further investigation of DS technology for neonatal breath sounds is warranted.

Sections du résumé

BACKGROUND
There is no published literature regarding the use of the digital stethoscope (DS) and computerized breath sound analysis in neonates, despite neonates experiencing a high burden of respiratory disease. We aimed to determine if the DS could be used to study breath sounds of term and preterm neonates without respiratory disease, and detect a difference in acoustic characteristics between them.
METHODS
A commercially available DS was used to record breath sounds of term and preterm neonates not receiving respiratory support between 24 and 48 hours after birth. Recordings were extracted, filtered, and computer analysis performed to obtain power spectra and mel frequency cepstral coefficient (MFCC) profiles.
RESULTS
Recordings from 26 term and 26 preterm infants were obtained. The preterm cohort had an average gestational age (median and interquartile range) of 32 (31-33) weeks and term 39 (38-39) weeks. Birth weight (mean and SD) was 1767 (411) g for the preterm and 3456 (442) g for the term cohort. Power spectra demonstrated the greatest power in the low-frequency range of 100 to 250 Hz for both groups. There were significant differences (P < .05) in the average power at low (100-250 Hz), medium (250-500 Hz), high (500-1000 Hz), and very high (1000-2000 Hz) frequency bands. MFCC profiles also demonstrated significant differences between groups (P < .05).
CONCLUSION
It is feasible to use DS technology to analyze breath sounds in neonates. DS was able to determine significant differences between the acoustic characteristics of term and preterm infants breathing in room air. Further investigation of DS technology for neonatal breath sounds is warranted.

Identifiants

pubmed: 31917903
doi: 10.1002/ppul.24633
doi:

Types de publication

Journal Article Observational Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

624-630

Informations de copyright

© 2020 Wiley Periodicals, Inc.

Références

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Auteurs

Lindsay Zhou (L)

Monash Newborn, Monash Children's Hospital, Melbourne, Australia.
Department of Paediatrics, Monash University, Melbourne, Australia.

Faezeh Marzbanrad (F)

Department of Computer Systems and Electrical Engineering, Monash University, Melbourne, Australia.

Ashwin Ramanathan (A)

Department of Paediatrics, Monash University, Melbourne, Australia.

Davood Fattahi (D)

Department of Computer Systems and Electrical Engineering, Monash University, Melbourne, Australia.

Pramodkumar Pharande (P)

Monash Newborn, Monash Children's Hospital, Melbourne, Australia.

Atul Malhotra (A)

Monash Newborn, Monash Children's Hospital, Melbourne, Australia.
Department of Paediatrics, Monash University, Melbourne, Australia.

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