Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)

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Automated Detection of Tuberculosis Based on Cantilever Biosensor

Authors
Bali Thorat1, *, Mukti Jadhav2
1Department of Computer Science, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India
2Department of Computer Science, Shri. Shivaji Science and Arts College, Chikhali, India
*Corresponding author. Email: balithorat@gmail.com
Corresponding Author
Bali Thorat
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-196-8_3How to use a DOI?
Keywords
Tuberculosis; Cantilever; Biosensor; Simulation; MEMS; Antigen; Antibody
Abstract

Mycobacterium Tuberculosis is one of the most hazardous disease. Universally millions of people are suffering from this dangerous disease. Number of detection techniques are available, but due to its complex structure this infectious disease not get diagnose easily and within time. To prevent spreading the bacteria and to stop mortality there is a huge requirement to build an automated and easy technique which can detect tuberculosis at a developing phase. The purpose of the article is to design and simulate the cantilever biosensor for detection of tuberculosis. Micro cantilever biosensor are designed with cylindrical and rectangular shape with silicon substrate. The cantilever surface is coated with antibodies and when patient sample is placed on it, the antigen-antibody gets binds together. When targeted antigen-antibody binds together stress generated and it forms deflection. The displacement achieved by Cylindrical-shape was 2.06 × 106 µm and rectangular-shape was 1.2 × 1026 µm for 100N load force correlates to 28.228 × 10–24 kg weight of antigen. From both the model maximum displacement were recorded and considered the rectangular-shape model as the leading model for tuberculosis detection.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
Series
Advances in Intelligent Systems Research
Publication Date
10 August 2023
ISBN
978-94-6463-196-8
ISSN
1951-6851
DOI
10.2991/978-94-6463-196-8_3How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Bali Thorat
AU  - Mukti Jadhav
PY  - 2023
DA  - 2023/08/10
TI  - Automated Detection of Tuberculosis Based on Cantilever Biosensor
BT  - Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
PB  - Atlantis Press
SP  - 14
EP  - 22
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-196-8_3
DO  - 10.2991/978-94-6463-196-8_3
ID  - Thorat2023
ER  -