A Pt/Pd-Decorated SnO <sub>2</sub> -Based Electronic Nose for High-Precision Breath Analysis in Diagnosing SIBO
, CO, ethanol, and acetone, the system provides a more informative diagnostic profile than conventional single-marker tests. Furthermore, the electronic nose employs dual operating temperatures (135 and 190 °C) to enhance gas discrimination. Machine learning-assisted signal processing further optimizes the system's ability to differentiate gases, enabling more accurate detection in clinical settings. It achieves a 93% classification accuracy and a mean squared error of 0.78 for gas concentration estimation. Importantly, the system was validated using real clinical breath samples collected after lactulose ingestion, where SIBO patients exhibited markedly elevated responses (7.62-18.77) compared to healthy individuals (2.45-4.91). This clinically validated, multi-gas platform offers improved accuracy and practical potential for SIBO diagnosis.
Authors
- Ping Guo (ORCID: https://orcid.org/0000-0002-9759-1622)
- Guohua Cai
- Xuyang An (ORCID: https://orcid.org/0000-0001-9195-0420)
- Yinhua Hu (ORCID: https://orcid.org/0009-0006-2717-9778)
- Xinxin He (ORCID: https://orcid.org/0000-0003-2965-4094)
- Tiezhu Liu
- Tong Zhang
- Yanjie Chu
- Shuai Liang
Institutions
- Harbin Medical University (CN)
- Harbin Institute of Technology (CN)
- Second Affiliated Hospital of Harbin Medical University (CN)
- Microsystems (United Kingdom) (GB)
- Tang Hospital (CN)
Publication Details
- Journal
- ACS Sensors
- Published
- 2026-04-13
- DOI
- https://doi.org/10.1021/acssensors.6c00086
- Primary Topic
- Advanced Chemical Sensor Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Key Research and Development Program of Heilongjiang
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Natural Science Foundation of Chongqing
- National Key Research and Development Program of China