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Sensors 2016, 16(8), 1337; doi:10.3390/s16081337

Factors Influencing Continuous Breath Signal in Intubated and Mechanically-Ventilated Intensive Care Unit Patients Measured by an Electronic Nose

1
Department of Intensive Care, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands
2
Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands
3
Department of Respiratory Medicine, Academic Medical Center, University of Amsterdam, Amsterdam 1100DD, The Netherlands
*
Author to whom correspondence should be addressed.
Academic Editors: Takeshi Onodera and Kiyoshi Toko
Received: 22 June 2016 / Revised: 15 August 2016 / Accepted: 17 August 2016 / Published: 22 August 2016
(This article belongs to the Special Issue Olfactory and Gustatory Sensors)
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Abstract

Introduction: 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. Conclusion: 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. View Full-Text
Keywords: electronic nose; exhaled breath; ICU; critical care; mechanically-ventilated; continuous; pre-processing; noise electronic nose; exhaled breath; ICU; critical care; mechanically-ventilated; continuous; pre-processing; noise
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MDPI and ACS Style

Leopold, J.H.; Abu-Hanna, A.; Colombo, C.; Sterk, P.J.; Schultz, M.J.; Bos, L.D.J. Factors Influencing Continuous Breath Signal in Intubated and Mechanically-Ventilated Intensive Care Unit Patients Measured by an Electronic Nose. Sensors 2016, 16, 1337.

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