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Self-detection System for Type 2 Diabetes Mellitus by Aspiration of the Patient's Urinalysis

  • ,
  • Jean Meneses-Claudio
    ,
  • Milagros Vicuña-Ramirez
    ,
  • Yrene Uribe-Hernández
    ,
  • Juan Saberbein-Muñoz
    ,
  • Maria Salinas-Cruz
  • ,
  • Universidad Nacional Mayor de San Marcos
    ,
  • Universidad Científica del Sur
    ,
  • Universidad Nacional de Cañete
    ,
  • Universidad Nacional Enrique Guzmán y Valle
    ,
  • Business on Making Technologies
Research Output:
Contribution to journal
Article
Peer-review

Open access

Publication Information

Output type

Research Output:
Contribution to journal
Article
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 42-46 (5 pages)

Journal (Volume, Issue Number)

International Journal on Recent and Innovation Trends in Computing and Communication (Volume 11, Issue 4)

Publication milestones

  • Published - 04/2023

Publication status

Published - 04/2023

Publication IDs

  • Scopus: 85163607482

Abstract

Diabetes mellitus is a very silent disease, which, according to various studies, has been growing every year, among them are patients with type 2 diabetes mellitus that is characterized by why they do not produce enough insulin in their body, causing them to inject insulin in an uncontrolled way, caused discomfort by the number of times they inject. Some patients do not know if they have type 2 diabetes, and over time several inefficient and expensive diabetes screening systems have been developed, limiting their use by everyone. Similarly, if this disease is not detected in time, it can compromise other parts of the body so it is always necessary to control your eating habit, on the other hand, this type 2 disease can be detected in fasting of the patient. According to the problem exposed, in this research a self detection system of type 2 diabetes mellitus was carried out by aspirating a urinalysis to detect through the sweet smell of urine if the patient may have type 2 diabetes mellitus by means of gas sensors and carbon nanotubes fused by a microcontroller. Through the operation of the system, it was observed that the tests were performed with an efficiency of 98.99%, being an accepted value for a reliable and safe diabetes analysis, demonstrating that it can detect type 2 diabetes mellitus by asp hating the smell of urine.

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