Please use this identifier to cite or link to this item: https://repository.monashhealth.org/monashhealthjspui/handle/1/29409
Title: Acoustic analysis of neonatal breath sounds using digital stethoscope technology.
Authors: Malhotra A. ;Zhou L. ;Marzbanrad F.;Ramanathan A.;Fattahi D.;Pharande P.
Monash Health Department(s): Paediatric - Neonatal (Monash Newborn)
Institution: (Zhou, Pharande, Malhotra) Monash Newborn, Monash Children's Hospital, Melbourne, Australia (Zhou, Ramanathan, Malhotra) Department of Paediatrics, Monash University, Melbourne, Australia (Marzbanrad, Fattahi) Department of Computer Systems and Electrical Engineering, Monash University, Melbourne, Australia
Issue Date: 27-Feb-2020
Copyright year: 2020
Publisher: John Wiley and Sons Inc. (P.O.Box 18667, Newark NJ 07191-8667, United States)
Place of publication: United States
Publication information: Pediatric Pulmonology. 55 (3) (pp 624-630), 2020. Date of Publication: 01 Mar 2020.
Journal: Pediatric Pulmonology
Abstract: 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. Method(s): 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. Result(s): 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(s): 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.Copyright © 2020 Wiley Periodicals, Inc.
DOI: http://monash.idm.oclc.org/login?url=http://dx.doi.org/10.1002/ppul.24633
PubMed URL: 31917903 [http://www.ncbi.nlm.nih.gov/pubmed/?term=31917903]
ISSN: 8755-6863
URI: https://repository.monashhealth.org/monashhealthjspui/handle/1/29409
Type: Article
Subjects: birth weight
clinical article
cohort analysis
computer analysis
controlled study
feasibility study
female
frequency modulation
gestational age
male
medical technology
newborn
perinatal period
prematurity
priority journal
*stethoscope
*digital stethoscope
human
*abnormal respiratory sound
acoustic analysis
article
birth weight
computer analysis
frequency modulation
gestational age
medical technology
newborn
perinatal period
prematurity
stethoscope
digital stethoscope
abnormal respiratory sound
acoustic analysis
frequency modulation
gestational age
human
male
medical technology
newborn
perinatal period
prematurity
priority journal
female
clinical article
birth weight
Article
acoustic analysis
*abnormal respiratory sound
feasibility study
controlled study
computer analysis
cohort analysis
Type of Clinical Study or Trial: Observational study (cohort, case-control, cross sectional or survey)
Appears in Collections:Articles

Show full item record

Page view(s)

44
checked on Aug 30, 2024

Google ScholarTM

Check


Items in Monash Health Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.