Related Experiment Video
Updated: Jul 29, 2025
08:23
Real-time Breath Analysis by Using Secondary Nanoelectrospray Ionization Coupled to High Resolution Mass Spectrometry
Published on: March 9, 2018
9.0K
Electronic Nose Development and Preliminary Human Breath Testing for Rapid, Non-Invasive COVID-19 Detection.
Jing Li1, Ami Hannon1, George Yu2
1NASA Ames Research Center, Moffett Field, California 94035, United States.
ACS Sensors
|May 24, 2023
Summary
A novel electronic nose (E-Nose) system rapidly screens for COVID-19 by detecting volatile organic compounds (VOCs) in breath. Preliminary tests show a 79% accuracy rate, with potential for improved diagnostics when combined with other symptoms.
Area of Science:
- Biomedical Engineering
- Nanotechnology
- Infectious Disease Diagnostics
Background:
- The COVID-19 pandemic necessitates rapid and accessible diagnostic tools.
- Existing diagnostic methods like RT-PCR can be time-consuming and resource-intensive.
- Volatile organic compounds (VOCs) in human breath offer a potential non-invasive biomarker for various health conditions, including infections.
Purpose of the Study:
- To adapt and validate a spaceflight-proven electronic nose (E-Nose) for rapid, on-site COVID-19 screening.
- To assess the E-Nose system's ability to detect COVID-19 infection by analyzing VOC patterns in exhaled breath.
- To evaluate the preliminary diagnostic accuracy of the E-Nose system in distinguishing between COVID-19 positive and negative individuals.
Main Methods:
- Development of a hand-held E-Nose prototype featuring 64 nanomaterial-based sensing elements for VOC detection.
- Integration of data acquisition electronics, a smart tablet with a control application, and a breath sampling fixture.
- Deployment of "leave-one-out" cross-validation techniques for training and analysis of sensor response data from 63 participants.
- Comparison of E-Nose results with RT-PCR confirmed COVID-19 status.
Main Results:
- The E-Nose system demonstrated high sensitivity in detecting VOCs at parts-per-billion levels with excellent repeatability (0.02%) and reproducibility (1.2%).
- The prototype achieved a 79% correct identification rate in discriminating between COVID-19 positive and negative breath samples.
- Measurement electronics provided accuracy and signal-to-noise ratios comparable to benchtop instrumentation.
Conclusions:
- The adapted E-Nose technology shows promise as a rapid, non-invasive screening tool for COVID-19 infection.
- Combining E-Nose data with other non-invasive metrics like body temperature and symptoms, analyzed via machine learning, is expected to enhance diagnostic accuracy.
- Further clinical validation, design refinement, and mass manufacturing are crucial for widespread deployment in various settings.
