We evaluated MEMS microsensor array with chemi-resistive elements for use as a non-invasive clinical diagnostic tool to detect the presence or absence of trace amounts of disease biomarkers in simulated breath samples. The microsensor environment was periodically altered between air (20% relative humidity) and simulated breath (77% nitrogen, 16% oxygen, 4% carbon dioxide, 2% water) samples creating a dynamic background. Acetone, a disease marker for diabetes, was spiked into select simulated breath samples at relevant concentrations (0.5 µmol/mol to 8 µmol/mol) to pose a diagnostic problem for the sensor array. Using standard statistical dimensionality reduction and classification algorithms, we compared the ability of a variety of sensing materials to detect and recognize the disease marker. Our analyses indicate that the porous, doped nanoparticle materials (antimony-doped tin oxide microshell films and niobium-doped titanium dioxide nanoparticle films) are best for the recognition problem (acetone present vs. absent), but that tungsten oxide and tin oxide films are better at the quantification task (high vs. low concentrations of acetone).
Citation: IEEE Sensors Journal
Pub Type: Journals
bioscience & health - diagnostics, chemistry - chemical analysis - gas phase sensing, nanotechnology - nanostructured materials