Pediatric Respiratory Rate Estimation through Deep Neural Networks

Simple item page
dc.contributor.authorStarkov, Pierre
dc.contributor.authorManzano, Sergio
dc.contributor.authorHugon, Florence
dc.contributor.authorBraun, Fabian
dc.contributor.authorLemkaddem, Alia
dc.contributor.authorVerjus, Christophe
dc.contributor.authorDelgado-Gonzalo, Ricard
dc.contributor.authorSolà, Josep
dc.contributor.authorGervaix, Alain
dc.contributor.authorBenissa, Mohamed-Rida
dc.date.accessioned2025-11-11T15:37:45Z
dc.date.available2025-11-11T15:37:45Z
dc.date.issued2018
dc.description.abstractWe present results for respiratory rate determination using deep learning and classic machine learning and based on analysis of respiratory sounds recorded on 48 children less than 60 months old and presenting an acute lower respiratory infection (ALRI). The method has an overall rms error for determining respiratory rate of 0.02 (±0.86) breaths per 10 seconds.
dc.identifier.citationCSEM Scientific and Technical Report 2018, p. 82
dc.identifier.urihttps://hdl.handle.net/20.500.12839/1812
dc.titlePediatric Respiratory Rate Estimation through Deep Neural Networks
dc.typeCSEM Report
dc.type.csemdivisionsBU-D
dc.type.csemresearchareasDigital Health
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
2018_Starkov et al_Pediatric Respiratory Rate Estimation through Deep Neural Networks.pdf
Size:
209.84 KB
Format:
Adobe Portable Document Format
Download
Collections
Technical Marketing Material