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 REVIEW ARTICLE
Year : 2020  |  Volume : 68  |  Issue : 1  |  Page : 26--34

Emerging Advanced Technologies Developed by IPR for Bio Medical Applications ‑.A Review


1 Institute for Plasma Research, Gandhinagar, Gujarat, India
2 Advanced Centre for Treatment, Research and Education in Cancer, TMC, Mumbai, Maharashtra, India
3 Department of Neurosurgery, AIIMS, New Delhi, India

Correspondence Address:
Dr. Alphonsa Joseph
Facilitation Centre for Industrial Plasma Technologies, IPR, A-10/B, Sector 25, GIDC Electronic Estate, Gandhinagar, Gujarat
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0028-3886.279707

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Over the last decade, research has intensified worldwide on the use of low-temperature plasmas in medicine and healthcare. Researchers have discovered many methods of applying plasmas to living tissues to deactivate pathogens; to end the flow of blood without damaging healthy tissue; to sanitize wounds and accelerate its healing; and to selectively kill malignant cancer cells. This review paper presents the latest development of advanced and plasma-based technologies used for applications in neurology in particular. Institute for Plasma Research (IPR), an aided institute of the Department of Atomic Energy (DAE), has also developed various technologies in some of these areas. One of these is an Atmospheric Pressure Plasma Jet (APPJ). This device is being studied to treat skin diseases, for coagulation of blood at faster rates and its interaction with oral, lung, and brain cancer cells. In certain cases, in-vitro studies have yielded encouraging results and limited in-vivo studies have been initiated. Plasma activated water has been produced in the laboratory for microbial disinfection, with potential applications in the health sector. Recently, plasmonic nanoparticle arrays which allow detection of very low concentrations of chemicals is studied in detail to allow early-stage detection of diseases. IPR has also been developing AI-based software called DeepCXR and AIBacilli for automated, high-speed screening and detection of footprints of tuberculosis (TB) in Chest X-ray images and for recognizing single/multiple TB bacilli in sputum smear test images, respectively. Deep Learning systems are increasingly being used around the world for analyzing electroencephalogram (EEG) signals for emotion recognition, mental workload, and seizure detection.






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