IIT Jodhpur Innovates Breath Sensor Technology

Researchers at the Indian Institute of Technology Jodhpur created the first ‘Made in India’ breath monitoring sensor for alcohol detection. Exhaled breath samples containing volatile organic compounds (VOCs) can serve as biomarkers to detect alcohol consumption and several other illnesses. The sensor's main job is to gauge how much alcohol is in the breath. Additionally, there is no need for additional batteries or setup time with the designed sensor. 

When a person's breath volatile organic molecules are tracked, this technique can be highly helpful in the diagnosis of conditions including asthma, diabetic ketoacidosis, chronic obstructive pulmonary disease, sleep apnea and cardiac arrest. 

Indian Institute of Technology Jodhpur researchers have developed the first ‘Make in India’ human breath sensor using metal oxides and nano silicon. The sensor measures the alcohol content in breath in drunk and driving cases, but with changes in sensing layers, sensors and data analytics, it can also be used to characterise diseases like asthma, diabetic ketoacidosis, chronic obstructive pulmonary disease, sleep apnea, and cardiac arrest. The sensor does not require additional batteries or setup time and can be used to diagnose conditions like asthma, diabetic ketoacidosis and chronic obstructive pulmonary disease.

Researchers at IIT Jodhpur have developed a breath VOC sensor and a breath monitoring sensor based on partially reduced graphene oxide, to address the growing need for a quick, affordable and non-invasive health monitoring device due to concerns about air pollution's impact on human health and the environment. 

A new electronic nose can monitor volatile organic compounds (VOC) in the environment and detect other breath biomarkers for disease by modifying sensors and machine learning algorithms. Current breath analysers are bulky and require long preparation and heater time, increasing power consumption and waiting times. The developed sensor operates at room temperature and is plug-and-play.

The device uses an electronic nose with a room-temperature operable heterostructure, reacting with alcohol in a sample, displaying a change in resistance proportional to alcohol concentration. Data collected is processed using machine learning algorithms to identify breath components and separate alcohol from volatile organic compounds.