Ultratrace eNose Sensing of VOCs toward Breath Analysis Applications Utilizing an eNose-Based Analyzer
Johannes Glöckler1, Carsten Jaeschke1, Marta Padilla2
1Institute of Analytical and Bioanalytical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89081 Ulm, Germany.
The iLovEnose electronic nose accurately detects ultratrace volatile organic compounds (VOCs) in simulated breath. This technology shows promise for future disease diagnostics using exhaled breath analysis.
Area of Science:
- Analytical Chemistry
- Biomedical Engineering
- Sensor Technology
Background:
- Volatile organic compounds (VOCs) in exhaled breath are potential biomarkers for disease detection.
- Accurate measurement of ultratrace VOCs is challenging, especially under humid conditions.
- Existing breath analysis methods may require complex sample handling.
Purpose of the Study:
- To demonstrate the capability of the novel iLovEnose system for measuring ultratrace VOCs in simulated human breath.
- To evaluate the performance of the iLovEnose using a combination of metal oxide (MOX) gas sensors.
- To assess the system's reliability for quantitative analysis of specific VOCs.
Main Methods:
- Utilized the iLovEnose, a test bed for gas sensors with three temperature-controlled compartments.
- Equipped the system with 11 MOX gas sensors of various base technologies.
- Analyzed six target VOCs at ultralow concentrations (0.075–3 ppm) under high humidity (90% RH) using randomized measurements.
- Applied partial least-squares regression for quantitative concentration estimation.
Main Results:
- The iLovEnose successfully discriminated between six different VOCs.
- The system provided reliable quantitative measurements of VOC concentrations.
- Performance was validated across multiple measurements over two weeks.
Conclusions:
- The iLovEnose system demonstrates feasibility for detecting and quantifying ultratrace VOCs in breath.
- This technology holds potential for non-invasive disease diagnostics and monitoring through exhaled breath analysis.
- Further development could lead to advanced clinical applications in personalized medicine.
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