title: Factors Influencing Continuous Breath Signal in Intubated and Mechanically-Ventilated Intensive Care Unit Patients Measured by an Electronic Nose.
abstract: BACKGROUND
  Continuous breath analysis by electronic nose (eNose) technology in the intensive care unit (ICU) may be useful in monitoring (patho) physiological changes. However, the application of breath monitoring in a non-controlled clinical setting introduces noise into the data. We hypothesized that the sensor signal is influenced by: (1) humidity in the side-stream; (2) patient-ventilator disconnections and the nebulization of medication; and (3) changes in ventilator settings and the amount of exhaled CO₂. We aimed to explore whether the aforementioned factors introduce noise into the signal, and discuss several approaches to reduce this noise.
  
  
  METHODS
  Study in mechanically-ventilated ICU patients. Exhaled breath was monitored using a continuous eNose with metal oxide sensors. Linear (mixed) models were used to study hypothesized associations.
  
  
  RESULTS
  In total, 1251 h of eNose data were collected. First, the initial 15 min of the signal was discarded. There was a negative association between humidity and Sensor 1 (Fixed-effect β: -0.05 ± 0.002) and a positive association with Sensors 2-4 (Fixed-effect β: 0.12 ± 0.001); the signal was corrected for this noise. Outliers were most likely due to noise and therefore removed. Sensor values were positively associated with end-tidal CO₂, tidal volume and the pressure variables. The signal was corrected for changes in these ventilator variables after which the associations disappeared.
  
  
  CONCLUSIONS
  Variations in humidity, ventilator disconnections, nebulization of medication and changes of ventilator settings indeed influenced exhaled breath signals measured in ventilated patients by continuous eNose analysis. We discussed several approaches to reduce the effects of these noise inducing variables.
authors.affiliation: Department of Intensive Care, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands. j.h.leopold@amc.uva.nl.|Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands. j.h.leopold@amc.uva.nl.
authors.forename: Jan Hendrik
authors.initials: JH
authors.lastname: Leopold
authors.affiliation: Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands. a.abu-hanna@amc.uva.nl.
authors.forename: Ameen
authors.initials: A
authors.lastname: Abu-Hanna
authors.affiliation: Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands. colombo.cam@gmail.com.
authors.forename: Camilla
authors.initials: C
authors.lastname: Colombo
authors.affiliation: Department of Respiratory Medicine, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands. p.j.sterk@amc.uva.nl.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Sterk
authors.affiliation: Department of Intensive Care, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands. marcus.j.schultz@gmail.com.
authors.forename: Marcus J
authors.initials: MJ
authors.lastname: Schultz
authors.affiliation: Department of Intensive Care, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands. l.d.bos@amc.uva.nl.|Department of Respiratory Medicine, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands. l.d.bos@amc.uva.nl.
authors.forename: Lieuwe D J
authors.initials: LD
authors.lastname: Bos
mesh_terms: D000368:Aged; D001944:Breath Tests / Q000379:methods*; D062609:Electronic Nose; D005260:Female; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000379:methods*; D012121:Respiration, Artificial / Q000379:methods
keywords: ICU; continuous; critical care; electronic nose; exhaled breath; mechanically-ventilated; noise; pre-processing