Exhaled breath acetone has been identified as a diabetes biomarker for non-invasive diagnosis. Its detection using biosensors features many advantages over the conventional means. This paper reviews recent literature on the detection of exhaled breath acetone and acetone vapour for diabetic interest. The biosensors have been classified based on their transduction methods. Performance characteristics of the biosensors have been explored for comparison. The future trends are also highlighted.

Acetone vapor sensing is important for environmental monitoring and non-invasive screening of diabetes mellitus (DM). Inhaling higher than 176 parts per million (ppm) acetone concentrations affects the respiratory system, while acetone in exhaled breath correlates with blood glucose and exhaling more than 1.8 ppm indicates the person is in danger of DM. DM is currently diagnosed invasively by measuring glucose level in blood, which is painful, and therefore inconvenient. This paper reports MEMS sensor device functionalized with blend of Chitosan/Polyethylene glycol polymers for acetone vapor sensing for possible non-invasive screening of diabetes. The sensor was experimentally tested using synthetic acetone vapor, and found to give linear response for 0.05-5 ppm acetone in air, with a sensitivity of 21 mV/ppm, good repeatability, response, and reversibility. Cross-sensitivity for 2-propanol and methanol was examined, where the responses of the sensor to 1 ppm concentration in air of these two analytes were found to be 24% and 33%, respectively, less compared to its response to the same concentration of acetone.

This work describes the fabrication and characterization of a Micro-Electro-Mechanical System (MEMS) sensor for gas sensing applications. The sensor is based on standard PolyMUMPs (Polysilicon Multi-Users MEMS Process) technology to control the temperature over the sensing layer. Due to its compact size and low power consumption, micro-structures enable a well-designed gas-sensing-layer interaction, resulting in higher sensitivity compared to the ordinary materials. The aim of conducting the characterization is to compare the measured and calculated resistance values of the micro-heater and the temperature sensor. The temperature coefficient of resistance (TCR) of the temperature sensor has been estimated by raising and dropping the temperature throughout a 25–110 °C range. The sensitivity of these sensors is dependent on the TCR value. The temperature sensor resistance was observed to rise alongside the rising environmental temperatures or increasing voltages given to the micro-heater, with a correlation value of 0.99. When compared to the TCR reported in the literature for the gold material 0.0034 °C${}^{-1}$, the average TCR was determined to be 0.00325 °C${}^{-1}$ and 0.0035 °C${}^{-1}$, respectively, indicating inaccuracies of 4.6% and 2.9%, respectively. The variation between observed and reported values is assumed to be caused by the fabrication tolerances of the design dimensions or material characteristics.

Diabetes is currently screened invasively by measuring glucose concentration in blood, which is inconvenient. This paper reports a study on modeling and simulation of a CMOS-MEMS sensor for noninvasive screening of diabetes via detection of acetone vapor in exhaled breath (EB). The sensor has two structures: movable (rotor) and fixed (stator) plates. The rotor plate is suspended on top of the stator by support of four flexible beams and maintaining certain selected initial gaps of 5, 6, 7, 8, 9, 10, or 11 μm to form actuation and sensing parallel plate capacitors. A chitosan polymer of varied thicknesses (1–20 μm) is deposited on the rotor plate and modeled as a sensing element for the acetone vapor. The minimum polymer coating thickness required to detect the critical concentration (1.8 ppm) of acetone vapor in the EB of diabetic subjects is found to be 4–7 μm, depending on the initial gap between the rotor and stator plates. However, to achieve sub-ppm detection limit to sense the acetone vapor concentration (0.4–1.1 ppm) in the EB of healthy people, up to 20 μm polymer thickness is coated. The mathematically modeled results were verified using the 2008 CoventorWare simulation software and a good agreement within a 5.3% error was found between the modeled and the simulated frequencies giving more confidence in the predicted results.