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