Paper Title
Breath-Analysis: A Non Invasive Method For Detection of Diseases and Health Conditions Using Gas Sensors

Studies have shown a strong and essential correlation between volatile organic compounds and certain other gasesin exhaled breath and incidence of specific diseases thus offering strong potential for clinical diagnostic application using exhaled breath gas sensing and analysis. Breath analysis provides a non-invasive technique making it more agreeable and efficient compared to current invasive techniques such as blood or urine sampling. A handheld device which is cost effective, reliable and capable of early diagnosis of diseases and health conditions is needed. This technology should also be able tobe applicable in the diet and fitness domain by detecting Ketogenesis (fat burn). With the advent of MEMS technology, solid state sensors have become more and more common in sensor modules used to detect various gases. The readings obtained from the sensors on detection of the biomarkers can also be made more accurate by employing an Artificial Neural Network (ANN).Compact hardware housing, user friendly presentation of dataand server data storage should be developed in such a handheld device. These devices would make clinical diagnosis a rapid, non-invasive method adopted at the triage station in hospitals. In this paper the design, working and utility of a prototype handheld device is discussed. Keywords— Artificial Neural Network, Breath Analyser, Fat-burn, Ketogenesis, non-invasive, solid state sensors.