Development of a Healthcare Monitoring Diabetes Mobile Application for Community

Author:

Bussaban Kanyarat1,Bussaban Kanyarat2,Ruksuntorn Nareenart3,Chutrtong Jaruwan1,Sangsuwan Chanyapat1

Affiliation:

1. Faculty of Science and Technology Suan Sunandha Rajabhat University Bangkok, THAILAND

2. Computer Science Program Suan Sunandha Rajabhat University Bangkok, THAILAND

3. Robotics Engineering program Faculty of Industrial Technology Suan Sunandha Rajabhat University Bangkok, THAILAND

Abstract

The purpose of this project is to develop the mobile application, by applied Machine learning, for analyzing, collecting, monitoring, and retrieving information between patients with diabetes especially diabetes type 2 and village public health volunteers and to study the impact of using mobile application based on self- learning and self-management in diabetes information. This is a research and development mobile application and the sample consisted of 30 diabetes patients and 5 village health volunteers participated in this research. The project has demonstrated the effectiveness of using mobile application to support patients and village health volunteers. The results showed that user satisfaction has a high level.

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference28 articles.

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2. Tunsuchart K, Lerttrakarnnon P, Srithanaviboonchai K, Likhitsathian S, Skulphan S. Type 2 Diabetes Mellitus Related Distress in Thailand. Int J Environ Res Public Health. 2020 Mar 30;17(7):2329. doi: 10.3390/ijerph17072329. PMID: 32235629; PMCID: PMC7177402.

3. Thailand, Diabetes report 200-2045: https://diabetesatlas.org/data/en/country/196/th.html

4. B. Sanguanprasit, P. Leerapan, and P. Taechaboonsermsak, “Village health volunteers as peer supports for glycemic control among type 2 diabetes patients in Thailand”, J Public Hlth Dev, vol. 14, no. 2, pp. 49–60, Sep. 2016.

5. Makroum MA, Adda M, Bouzouane A, Ibrahim H. Machine Learning and Smart Devices for Diabetes Management: Systematic Review. Sensors (Basel). 2022 Feb 25;22(5):1843. doi: 10.3390/s22051843. PMID: 35270989; PMCID: PMC8915068.

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