<p>Volatile organic compounds (VOCs) are endogenous byproducts
of metabolic pathways that can be altered by a disease or condition, leading to
an associated and unique VOC profile or signature. Current methodologies for
VOC detection include canines, gas chromatography-mass spectrometry (GC-MS),
and electronic nose (eNose). Some of the challenges for canines and GC-MS are
cost-effectiveness, extensive training, expensive instrumentation. On the other
hand, a significant downfall of the eNose is low selectivity. This thesis
proposes to design a breathalyzer using chemiresistive gas sensors that detects
VOCs from human breath, and subsequently create an interface to process and
deliver the results via Bluetooth Low Energy (BLE). Breath samples were
collected from patients with hypoglycemia, COVID-19, and healthy controls for
both. Samples were processed, analyzed using GC-MS and probed through
statistical analysis. A panel of 6 VOC biomarkers distinguished between
hypoglycemia (HYPO) and Normal samples with a training AUC of 0.98 and a
testing AUC of 0.93. For COVID-19, a panel of 3 VOC biomarkers distinguished
between COVID-19 positive symptomatic (COVID-19) and healthy Control samples
with a training area under the curve (AUC) of receiver operating characteristic
(ROC) of 1.0 and cross-validation (CV) AUC of 0.99. The model was validated
with COVID-19 Recovery samples. The discovery of these biomarkers enables the
development of selective gas sensors to detect the VOCs. </p><p><br></p><p>Polyethylenimine-ether functionalized gold nanoparticle
(PEI-EGNP) gas sensors were designed and fabricated in the lab and metal oxide
(MOX) semiconductor gas sensors were obtained from Nanoz (Chip 1: SnO<sub>2</sub> and Chip
2: WO<sub>3</sub>). These sensors were tested at different relative humidity (RH) levels,
and VOC concentrations. Contact angle which measures hydrophobicity, was 84°
and the thickness of the PEI-EGNP coating was 11 µ m. The PEI-EGNP sensor
response at RH 85% had a signal 10x higher than at RH 0%. Optimization of the
MOX sensor was performed by changing the heater voltage and concentration of
VOCs. At RH 85% and heater voltage of 2500 mV, the performance of the sensors
increased. Chip 2 had higher sensitivity towards VOCs especially for one of the
VOC biomarkers identified for COVID-19. PCA distinguished VOC biomarkers of
HYPO, COVID-19, and healthy human breath using the Nanoz. A sensor interface
was created to integrate the PEI-EGNP sensors with the printed circuit board
(PCB) and Bluno Nano to perform machine learning. The sensor interface can currently
process and make decisions from the data whether the breath is HYPO (-) or
Normal (+). This data is then sent via BLE to the Hypo Alert app to display the
decision.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/17139218 |
| Date | 20 December 2021 |
| Creators | Paula Andrea Angarita (11806427) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/Development_of_a_Sensor_System_for_Rapid_Detection_of_Volatile_Organic_Compounds_in_Biomedical_Applications/17139218 |
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