Rancang Bangun Alat Ukur Kadar Gula Darah, Kolestrol, dan Asam Urat Non-Invasif Berbasis Internet of Things (IoT) - Gusti, Agrippina Waya Rahmaning; Kemalasari; Rochmad, Mochammad; Az Zahro, Fatimah (AI Society & STMIK Indonesia, 2023)
Diabetes and cardiovascular disease are examples of non-communicable diseases with the highest prevalence. One way to prevent this deadly disease is by carrying out regular health checks. Blood sugar, cholesterol and uric acid level detection devices on the market are invasive, causing discomfort with needles when drawing blood. The aim of this research is to design a tool to measure blood sugar, cholesterol and uric acid levels non-invasively using the MAX30105 sensor. The MAX30105 sensor will read the infrared value on the fingertip which is then converted into a calculation of blood sugar, cholesterol and uric acid values using the linear regression method. This method will compare the IR value from the sensor output with the results of invasive readings of glucose, cholesterol and uric acid levels to form a regression equation. The measurement data will then be sent via WiFi to the application for easy reading. Based on the experimental results, the accuracy value for glucose reading was 91.44%, cholesterol 84.94% and uric acid 84.91%. More sample variations are needed to map variables that can cause errors in reading values. Apart from that, the amount of light and finger placement procedures also need to be considered to get better accuracy.