Application of Polynomial Regression Method in Non-invasive Measurement of Blood Sugar, Cholesterol, and Non-invasive Uric Acid Based on IoT

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Názov: Application of Polynomial Regression Method in Non-invasive Measurement of Blood Sugar, Cholesterol, and Non-invasive Uric Acid Based on IoT
Autori: Desi Rahmadaniar, Irma Salamah, Martinus Mujur Rose
Zdroj: Invotek: Jurnal Inovasi Vokasional dan Teknologi, Vol 24, Iss 3, Pp 187-196 (2025)
Informácie o vydavateľovi: Universitas Negeri Padang, 2025.
Rok vydania: 2025
Predmety: internet of things (iot), max30105 sensor, polynomial regression, non-invasive, T1-995, Education (General), L7-991, Technology (General)
Popis: Early disease avoidance depends much on health monitoring. However, the general examination methods still used today are invasive, namely, using a syringe to take blood samples. Many do not undergo routine examinations because this method is uncomfortable and expensive. In this study, the MAX30105 optical sensor is used as a non-invasive measuring device that can read the reflection of infrared light from the fingertip. After that, the second-order polynomial regression method is used to process the sensor data and determine the blood sugar, cholesterol, and uric acid levels. Using calibration data, this tool will change the reflected light signal into numbers for these three substances. The quantitative experimental method was conducted on 15 participants, The quantitative experimental method was carried out on 15 participants, the test results showed that blood sugar levels reached 91.50%, cholesterol levels reached 86.07%, and uric acid levels reached 89.33%. Real-time data transmission is carried out through the Adafruit IO platform, which was chosen for its accessibility and ease of integration. At the same time, a mobile application was developed using MIT App Inventor for user-friendly health data visualization. A preliminary Quality of Service (QoS) assessment showed an average data latency of 500–700 ms and a 97% transmission success rate via Wi-Fi. These results indicate that this device is reasonably practical and comfortable. However, several factors, such as skin thickness, finger position, and skin cleanliness, can affect the accuracy of the measurement results. Therefore, this tool cannot yet replace regular medical standards.
Druh dokumentu: Article
ISSN: 2549-9815
1411-3414
DOI: 10.24036/invotek.v24i3.1264
Prístupová URL adresa: https://doaj.org/article/33954405f99c4dffac7e1aac8cbc8a49
Rights: CC BY
Prístupové číslo: edsair.doi.dedup.....db95e8595dba1e854c4486d7d692e75f
Databáza: OpenAIRE
Popis
Abstrakt:Early disease avoidance depends much on health monitoring. However, the general examination methods still used today are invasive, namely, using a syringe to take blood samples. Many do not undergo routine examinations because this method is uncomfortable and expensive. In this study, the MAX30105 optical sensor is used as a non-invasive measuring device that can read the reflection of infrared light from the fingertip. After that, the second-order polynomial regression method is used to process the sensor data and determine the blood sugar, cholesterol, and uric acid levels. Using calibration data, this tool will change the reflected light signal into numbers for these three substances. The quantitative experimental method was conducted on 15 participants, The quantitative experimental method was carried out on 15 participants, the test results showed that blood sugar levels reached 91.50%, cholesterol levels reached 86.07%, and uric acid levels reached 89.33%. Real-time data transmission is carried out through the Adafruit IO platform, which was chosen for its accessibility and ease of integration. At the same time, a mobile application was developed using MIT App Inventor for user-friendly health data visualization. A preliminary Quality of Service (QoS) assessment showed an average data latency of 500–700 ms and a 97% transmission success rate via Wi-Fi. These results indicate that this device is reasonably practical and comfortable. However, several factors, such as skin thickness, finger position, and skin cleanliness, can affect the accuracy of the measurement results. Therefore, this tool cannot yet replace regular medical standards.
ISSN:25499815
14113414
DOI:10.24036/invotek.v24i3.1264