Detection of Potential Breath Biomarkers CO, NO and H2S using FPGA based Electronic Nose

Carbon Monoxide (CO), Nitric Oxide (NO), and Hydrogen Sulfide (H 2 S) which are environmental pollutants are also gasotrans-mitters in the body. These gasses are present in elevated concentrations in asthma, chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS) and cystic fibrosis patients’ breath. Detection of these breath biomarkers in exhaled breath can be used as a point-of-care device for several conditions even when a patient cannot communicate with the caretakers like in pediatrics or intensive care units. Early and non-invasive detection of such diseases is very crucial to the treatment. This paper introduces the use of a Field Programmable Gate Array (FPGA) based electronic nose (e-nose) to detect CO, NO, and H 2 S as breath biomarkers. This non-invasive method aims to diagnose diseases by detecting low concentrations of these target gases (less than 5 parts per million (ppm)). We modify quartz tuning forks (QTF) with specific nanomaterials that react with the target gases, causing a sensor response. The gas reaction is based on the adsorption and desorption of gas molecules onto the surfaces of the nanomaterials, resulting in a change in the frequency of the QTF. The FPGA-based e-nose measures this frequency change with a resolution of 10 mHz and an acquisition time of 0.5 seconds. FPGA allows users to reconfigure the hardware to meet specific requirements, providing real-time data processing and more hardware programming flexibility than conventional microcontrollers and microprocessors. Machine learning algorithms can use the acquired data to predict whether a person is suffering from the disease. This sensor system could potentially diagnose the disease before it reaches a level of criticality. The FPGA’s parallel processing capabilities enable rapid and simultaneous analysis of sensor data with high resolution and sensitivity in biomarker detection. The system is calibrated using known concentrations of target gases. It can potentially improve individuals’ safety and health by facilitating proactive health monitoring and timely medical intervention.