Artifact rejection and cycle detection in immature breathing: Application to the early detection of neonatal sepsis. (February 2015)

• Record Type: Journal Article
• Authors: Navarro, X.; Porée, F.; Beuchée, A.; Carrault, G.
• Is Part Of: Biomedical signal processing and control. Volume 16(2015)
• Page Start: 9
• Page End: 16
• Publication Date: 2015-02
• Subjects: Respiratory variability signal -- Premature infant -- Artifact removal -- Automated detection -- Logistic regression; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2014.10.007
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract : Highlights: A new framework to reject artifacts and detect breathing cycles is proposed for immature breathing from preterm infants acquired in neonatal intensive care units. An automatic detector of artifacts based on logistic regression has been implemented and validated. The clinical interest of this framework is illustrated by analyzing the obtained signals to detect neonatal sepsis. Abstract: This paper proposes a new framework to obtain quality respiratory variability signals from the raw breathing recorded in neonatal intensive care units (NICUs). It combines three consecutive blocks: an automatic rejection of artifacts, implemented by a logistic regression classifier, a two-step filtering process, and the identification of respiratory cycles, implemented by a peak detection algorithm. By means of a gold standard built from a preterm infants database, the performances of the first and third blocks have been evaluated. While the former obtains a 86% of specificity and sensitivity, the latter attains a respective 97%. The interest of our proposal in the clinical domain is illustrated by a promising application to detect promptly and non-invasively the presence of neonatal sepsis in the NICU.