| ISSN |
2220-315x (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
| Copyright |
©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Engineering, Biomedical |
| Manuscript Type |
Basic Study |
| Article Title |
Artificial intelligence powered glucose monitoring and controlling system: Pumping module
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Sravani Medanki, Nikhil Dommati, Hema Harshitha Bodapati, Venkata Naga Sai Kowsik Katru, Gollapalli Moses, Abhishek Komaraju, Nanda Sai Donepudi, Dhnaya Yalamanchili, Jasti Sateesh and Pratap Turimerla |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Jasti Sateesh, PhD, Academic Research, Department of Electronics and Communication Engineering , Velagapudi Ramakrishna Siddhartha Engineering College, Kanuru, 340, Vijayawada 520007, Andhra Pradesh, India. sateeshjasti441@gmail.com |
| Key Words |
Diabetes; Hyperglycemia; Insulin; Micropump; Closed loop systems; AI automation |
| Core Tip |
This study describes an innovative diabetes management system that integrates real-time glucose monitoring with advanced artificial intelligence (AI) algorithms and closed-loop insulin delivery. This approach offers precise, personalized control of blood glucose levels, reducing the risk of complications. The simulations demonstrate the system's effectiveness in maintaining stable glucose levels, even in response to meals and exercise, thanks to the International Diabetes Federation controller and basal insulin dosage. Additionally, the study explores the use of ESP32 for monitoring input voltage levels to protect the system. Overall, this study provides a groundbreaking approach that combines AI, closed-loop control, and real-time monitoring to revolutionize diabetes care and improve patient outcomes. |
| Publish Date |
2024-03-19 14:54 |
| Citation |
Medanki S, Dommati N, Bodapati HH, Katru VNSK, Moses G, Komaraju A, Donepudi NS, Yalamanchili D, Sateesh J, Turimerla P. Artificial intelligence powered glucose monitoring and controlling system: Pumping module. World J Exp Med 2024; 14(1): 87916 |
| URL |
https://www.wjgnet.com/2220-315x/full/v14/i1/87916.htm |
| DOI |
https://dx.doi.org/10.5493/wjem.v14.i1.87916 |
