New Delhi: The Indian Institute of Technology (IIT) Jodhpur has devised a human breath sensor for measuring alcohol content in the breath and can be useful in drunk and driving cases. Also, it can be useful in detection of diseases like asthma, diabetic ketoacidosis, chronic obstructive disease, sleep apnea and cardiac arrest.
"With some changes in sensing layers and the use of an array of sensors (for Electronic Nose or Artificial Nose), and data analytics, it can also be very useful for characterisation of diseases, such as asthma, diabetic ketoacidosis, chronic obstructive pulmonary disease, sleep apnea, and cardiac arrest, where the person's breath volatile organic compounds are monitored," a statement from IIT Jodhpur said.
A breath analyzer is important in asthma management by monitoring the lung function and detecting changes in the inflammation of airway.
In view of the rising concerns about adverse impact of air pollution on human health and environment, there is always a need for an affordable, fast and non-invasive health monitoring device. This motivated researchers to come up with a breath sensor that is less costly than the existing sensors that are based on fuel cell-based technology or metal oxide technology.
According to Saakshi Dhanekar, Associate Professor, Department of Electrical Engineering, IIT Jodhpur, the existing breath analysers are either bulky or need a long preparation time and a heater resulting which, the power consumption of the device increases and has a long waiting time.
Nikhil Vadera, a PhD student at IIT Jodhpur said that the new sensor is similar to a plug-and play system and operates at room temperature. It functions on the principle of an electronic nose with room-temperature operable heterostructure (metal oxide with nano silicon), Vadera said.
Explaining the sensor's functioning, Vadera said that the sensors react with the alcohol in the sample. It then depicts a change in resistance that is proportional to the alcohol's concentration. Then the data is collected and processed using AI-based algorithms.
Finally, the various breath patterns are identified from the frequency and amplitude of the sensor's current change to the exposure to nose breath. It can distinguish between fast, normal and slow breathing.
The Biotechnology Ignition Grant Scheme (BIG), Biotechnology Industry Research Assistance Council (BIRAC), Science and Engineering Research Board (SERB),and the Ministry of Micro, Small, and Medium Enterprises (MSME) jointly funded the research.
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