Detection of Hypoxic Symptoms System Based on Oxygen Saturation and Heart Rate Using Arduino Based Fuzzy Method

Iswanto, Prisma Megantoro
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引用次数: 6

Abstract

In the medical field, a device is needed to monitor the patient’s condition in a noninvasive manner that is, without injuring the patient. If ignored continues to lead to hypoxia can disrupt the function of the brain, liver, and other organs quickly. So that in this study a hypoxia early symptom detection tool that uses a noninvasive method by using a Max30100 sensor that is pinned to the fingertips can affect the results of the initial symptoms of hypoxia. To detect the initial symptoms of hypoxia in this tool the Sugeno fuzzy method is used so that the output is obtained according to the existing rules. The Sugeno fuzzy method will process data taken from the Max30100 sensor. 3 devices are in this device, the Arduino as the controller, the Max30100 sensor to get the input and Bluetooth for sending data to the smartphone. The software uses an APP inventor to program the Android application to display data. In this study, the test results obtained error in 2.96% for oxygen saturation and 2.86% for heart rate obtained. From the fuzzy method in 12 trials, the data obtained 100% accuracy and the Sugeno fuzzy method can process the input data.
基于氧饱和度和心率的缺氧症状检测系统的Arduino模糊方法
在医疗领域,需要一种以无创方式监测患者病情的设备,即不伤害患者。如果忽视持续导致缺氧,会很快破坏大脑、肝脏和其他器官的功能。因此,在本研究中,缺氧早期症状检测工具采用无创方法,通过将Max30100传感器固定在指尖上,可以影响缺氧初始症状的结果。为了检测该工具中缺氧的初始症状,使用了Sugeno模糊方法,以便根据现有规则获得输出。Sugeno模糊方法将处理从Max30100传感器获取的数据。该设备中有3个设备,Arduino作为控制器,Max30100传感器进行输入,蓝牙将数据发送到智能手机。该软件采用APP inventor对Android应用程序进行编程以显示数据。在本研究中,得到的血氧饱和度和心率的测试结果误差分别为2.96%和2.86%。在12次试验中,模糊法得到的数据准确率为100%,Sugeno模糊法可以对输入数据进行处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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