WM-OA-ICOS Based Mid-infrared Dual-range Real-time Trace Sensor for Formaldehyde Detection in Exhaled Breath
Based on Wavelength Modulation Spectroscopy and Off-Axis Integrated Cavity Output Spectroscopy (WM-OA-ICOS), a highly sensitive dual-range real-time formaldehyde (CH 2 O) detection trace sensor was developed to detect CH 2 O in human exhaled breath, which can realize the early screening of lung canc...
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| Published in | IEEE sensors journal Vol. 23; no. 1; p. 1 |
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| Main Authors | , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1530-437X 1558-1748 |
| DOI | 10.1109/JSEN.2022.3210230 |
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| Summary: | Based on Wavelength Modulation Spectroscopy and Off-Axis Integrated Cavity Output Spectroscopy (WM-OA-ICOS), a highly sensitive dual-range real-time formaldehyde (CH 2 O) detection trace sensor was developed to detect CH 2 O in human exhaled breath, which can realize the early screening of lung cancer. And a 5.85 μm quantum cascade laser (QCL) and an off-axis integrated cavity were adopted. Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is applied to improve the signal-to-noise ratio (SNR), and the sensor is embedded with a high-precision concentration inversion algorithm. The reliability of the sensor was verified by experiments with interfering gases in exhaled breath, and the results showed the sensor has an excellent detection accuracy. The limits of detection (LoD) is ~140 parts per trillion (ppt) with an 88 s integration time by Allan-Werle deviation analysis. The experimental results of exhaled gas showed that the concentration of CH 2 O exhaled from different subjects was significantly different. Therefore, the sensor provides a promising way for real-time detection of CH 2 O concentration in human exhaled breath. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1530-437X 1558-1748 |
| DOI: | 10.1109/JSEN.2022.3210230 |