Vital Sign Monitoring in ICU Patients Based on MEWS (Modified Early Warning Score) with IOT (Internet of Things)

agus sukarno, Arief Marwanto, S. Alifah
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Abstract

Abstract Vital signs are signs that show important functions of the human body, from these signs can be known whether a person is relatively healthy, has a serious illness, or suffers from a life-threatening disorder. Vital signs are the value of physiological functions consisting of blood pressure, temperature, oxygen saturation, pulse and respiratory rate. Vital sign monitoring tools researchers used four parameters, namely blood preasure, heart rate, oxygen saturation, and body temperature. The tool uses the IoT (Internet of Things) system, where this tool uses sensors used, namely the DS18B20 temperature sensor, the Heart Rate sensor and the SPO2 MAX 30100 sensor, the OMRON HME-7130 sensor, the ESP 32 microcontroller as a data processor and Wi-Fi connection. The patient's vital condition data will be displayed on the android smartphone and on the mydevices.com WEB page. This tool is rule-based with a Modified Early Warning Score (MEWS) system to determine the status of patients and assist medical personnel in monitoring the vital parameters of patient signs in real time at each location and responding quickly and precisely so as to improve the quality of life of patients. Comparison using patient monitor tools, body temperature measurements produce the highest and lowest percentage of error that is 0.19% and 0.08% with an average temperature of 36.06oC and 35.96oC, then heart rate measurements obtained the highest and lowest percentage of errors of 0.08% and 0.3% with an average heart rate of 74 bpm and 87.3. Then the measurement of SpO2 obtained the highest and lowest percentage of error of 1% and 0% with an average SpO2 of 97% and 97.3%, then the NIBP measurement obtained the highest and lowest percentage of error systole / diastole of 7.4% / 7.2% with NIBP with an average systole / diastole of 109.6 / 64 mmHg and the lowest error percentage is 0.3% / 1.1% with an average NIBP of 125 / 62.3 mmHg. Data transmission to the internet using the cayene application on Android smartphones and WEB is greatly influenced by the quality of the connection from the internet network. Key words: Vital Signs, Modified Early Warning Score (MEWS), DS18B20, MAX 30100, ESP32 Microcontroller, IoT.
基于物联网改进预警评分(MEWS)的ICU患者生命体征监测
生命体征是显示人体重要功能的体征,从这些体征可以得知一个人是否相对健康、是否患有严重疾病或是否患有危及生命的疾病。生命体征是由血压、体温、血氧饱和度、脉搏和呼吸频率等生理功能组成的数值。生命体征监测工具的研究人员使用了四个参数,即血压、心率、血氧饱和度和体温。该工具使用IoT(物联网)系统,其中该工具使用传感器,即DS18B20温度传感器,心率传感器和SPO2 MAX 30100传感器,OMRON HME-7130传感器,ESP 32微控制器作为数据处理器和Wi-Fi连接。患者的生命状况数据将显示在安卓智能手机和mydevices.com网页上。该工具以规则为基础,采用修正预警评分(Modified Early Warning Score, MEWS)系统,确定患者的状态,协助医护人员实时监测各地点患者体征的重要参数,快速准确地做出反应,从而提高患者的生活质量。与使用患者监护工具进行比较,体温测量的最高和最低错误率分别为0.19%和0.08%,平均体温为36.06oC和35.96oC;心率测量的最高和最低错误率分别为0.08%和0.3%,平均心率为74 bpm和87.3。测血氧饱和度最高、最低误差分别为1%、0%,平均血氧饱和度为97%、97.3%;测血氧饱和度最高、最低误差分别为7.4%、7.2%,平均血氧饱和度为109.6 / 64 mmHg;测血氧饱和度最低为0.3%、1.1%,平均血氧饱和度为125 / 62.3 mmHg。使用Android智能手机和WEB上的cayene应用程序向互联网传输数据受到互联网连接质量的很大影响。关键词:生命体征,修正预警评分(MEWS), DS18B20, MAX 30100, ESP32单片机,物联网
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