Early detection is crucial in preventing diseases caused by high blood glucose, cholesterol, and uric acid levels through routine examinations. However, current testing devices are invasive, uncomfortable, complex, and generate medical waste. Therefore, this study aimed to develop and design a non-invasive measurement tool for these three parameters using the MAX30102 sensor. This research applied the Research and Development (R&D) method using the ADDIE model, adapted to the laboratory testing stage. The infrared values measured by the MAX30102 sensor on the fingertip were converted into mg/dL for blood glucose, cholesterol, and uric acid using a linear regression method to form regression equations. The converted data were then compared with standard devices to assess their accuracy. Additionally, a moving average filter was applied to reduce noise, smooth the signal, and balance the response to data changes. The measurement results were displayed on an OLED screen, a smartphone application for monitoring history and providing health information, and a speaker announcing the result categories. The results of the study showed that the cholesterol measurement accuracy was 89.71%, with an error rate of 10.29%, the uric acid accuracy was 92.98%, with an error rate of 7.02%, and the blood glucose accuracy was 92.64%, with an error rate of 7.36%.
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