Pediatric Respiratory Rate Estimation through Deep Neural Networks
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Author
Starkov, Pierre
Manzano, Sergio
Hugon, Florence
Braun, Fabian
Lemkaddem, Alia
Verjus, Christophe
Delgado-Gonzalo, Ricard
Solà, Josep
Gervaix, Alain
Benissa, Mohamed-Rida
DOI
Abstract
We 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.
Publication Reference
CSEM Scientific and Technical Report 2018, p. 82
Year
2018