Self-detection System for Type 2 Diabetes Mellitus by Aspiration of the Patient's Urinalysis
Article Sidebar
Main Article Content
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 aspirating the smell of urine.
Article Details
References
P. J. Navarrete Mejía, F. A. Lizaraso Soto, J. C. Velasco Guerrero, and L. M. Loro Chero, “Diabetes mellitus and arterial hypertension as a risk factor for mortality in patients with Covid-19,” Revista del Cuerpo Médico Hospital Nacional Almanzor Aguinaga Asenjo, vol. 13, no. 4, pp. 361–365, Feb. 2020, doi: 10.35434/RCMHNAAA.2020.134.766.
A. López Casanova, R. Triana de la Paz, A. Ruiz Triana, N. Díaz Alfonso, and Y. Gutiérrez Escarrása, “Síndrome metabólico en pacientes diabéticos tipo 2,” Acta Médica del Centro, vol. 13, no. 3, pp. 284–296, Oct. 2019, doi: 10.1161/CIRCULATIONAHA.109.192644.
V. Reyes Alcázar, I. Carrillo Murcia, and J. J. Mira Solves, “Definition of indicators for type II diabetic patient-centered care,” J Healthc Qual Res, vol. 36, no. 6, pp. 345–354, Nov. 2021, doi: 10.1016/J.JHQR.2021.05.004.
C. Lazo and S. Durán Agüero, “The effect of diabetes mellitus diagnosis and its complication with eating disorders,” Revista chilena de nutrición, vol. 46, no. 3, pp. 352–360, Jun. 2019, doi: 10.4067/S0717-75182019000300352.
E. Ramón Arbués et al., “Prevalence of overweight/obesity and its association with diabetes,” Nutr Hosp, vol. 36, no. 1, pp. 51–59, Jan. 2019, doi: 10.20960/NH.1980.
F. López Simarro, E. Redondo Margüello, J. J. Mediavilla Bravo, T. Soriano Llora, J. Iturralde Iriso, and A. Hormigo Pozo, “Prevention and treatment of infectious diseases in diabetic patients,” Medicina de Familia. SEMERGEN, vol. 45, no. 2, pp. 117–127, Mar. 2019, doi: 10.1016/J.SEMERG.2018.07.007.
R. I. Benites Loja and M. A. Coral Ygnacio, “A review of system implementations for diabetes trend identification,” Interfases, no. 016, pp. 231–251, Dec. 2022, doi: 10.26439/INTERFASES2022.N016.5957.
R. Vinces Chong, O. Villamarin Vaca, A. Tapia Mieles, J. Gorozabel Alarcón, C. Delgado Gorozabel, and M. Vinces Zambrano, “Diabetes Mellitus y su grave afectación en complicaciones típicas,” Polo del Conocimiento: Revista científico - profesional, vol. 4, no. 2, pp. 181–198, 2019, doi: 10.23857/pc.v4i2.901.
V. L. Naranjo Aldas and J. M. Torres Torres, “Insulin therapy for the treatment of patients with type 2 diabetes mellitus,” Ciencia Latina Revista Científica Multidisciplinar, vol. 6, no. 5, pp. 2170–2204, Oct. 2022, doi: 10.37811/CL_RCM.V6I5.3244.
F. A. Trevizani, D. T. Doreto, G. S. Lima, and S. Marques, “Atividades de autocuidado, variáveis sociodemográficas, tratamento e sintomas depressivos entre idosos com Diabetes Mellitus,” Rev Bras Enferm, vol. 72, pp. 22–29, Dec. 2019, doi: 10.1590/0034-7167-2017-0579.
A. C. Mariño Jara, M. I. Vinces Zambrano, A. N. Pico Tagle, A. P. Morales Tipán, O. X. Ruiz Lara, and C. M. Chango Checa, “Factores de riesgo que inciden en la presencia de diabetes,” RECIMUNDO: Revista Científica de la Investigación y el Conocimiento, ISSN-e 2588-073X, Vol. 2, No. 4, 2018, págs. 189-238, vol. 2, no. 4, pp. 189–238, 2018, doi: 10.26820/recimundo/2.(4).octubre.2018.189-238.
A. A. O. Blanco, G. Q. Compeán, and L. M. T. Treviño, “Personalized Glucose Metabolism Modeling for Type 2 Diabetic Patients Using Evolutionary Algorithms,” Memorias del Congreso Nacional de Ingeniería Biomédica, vol. 8, no. 1, pp. 327–330, Nov. 2021, doi: 10.24254/CNIB.21.61.
A. Singh Gautam, S. Kumar Jana, and M. Pratim Dutta, “Automated diagnosis of diabetic retinopathy using image processing for non-invasive biomedical application,” 2019 International Conference on Intelligent Computing and Control Systems, ICCS 2019, pp. 809–812, May 2019, doi: 10.1109/ICCS45141.2019.9065446.
Y. Obeidat and A. Ammar, “A System for Blood Glucose Monitoring and Smart Insulin Prediction,” IEEE Sens J, vol. 21, no. 12, pp. 13895–13909, Jun. 2021, doi: 10.1109/JSEN.2021.3070706.
A. E. Omer, G. Shaker, and S. Safavi Naeini, “Wearable CSRR-based Sensor for Monitoring Glycemic Levels for Diabetics,” Proceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020, pp. 922–928, Oct. 2020, doi: 10.1109/BIBE50027.2020.00156.
T. H. Yew Ling, L. Jin Wong, and T. Shu Ming, “Wireless Blood Glucose Device with Database for Health Assessment and Monitoring,” 2019 7th International Conference on Smart Computing and Communications, ICSCC 2019, Jun. 2019, doi: 10.1109/ICSCC.2019.8843603.
M. M. A. Gutiérrez, A. P. Cantero, and L. C. Martínez, “Diagnostic and therapeutic protocol for diabetic nephropathy,” Medicine - Programa de Formación Médica Continuada Acreditado, vol. 13, no. 17, pp. 974–977, Oct. 2020, doi: 10.1016/J.MED.2020.09.023.