Design And Implementation Of Multi-parameter Detection And Health Management System

As China’s population ages,the incidence of senile diseases is rising and the number of people suffering from them is also increasing,putting great pressure on the medical system.With the rapid development of embedded technology,Internet of Things technology and medical sensor technology,medical model is changing from offline treatment to remote online monitoring.In this context,this system combines embedded technology and NB-IOT technology,and based on Ali Cloud platform,designed a multi-parameter detection and health management system,which can carry out remote monitoring of five physiological parameters of human heart rate,respiratory rate,blood pressure,oxygen saturation and body temperature and exercise state,which has high application value and social significance.The system is divided into three parts:physiological parameter acquisition terminal,Internet of Things cloud platform and mobile phone client.Physiological parameter acquisition terminal takes STM32L431RCT6 single chip microcomputer as the central controller.Based on Free RTOS embedded real-time operating system,it writes programs to realize the functions of parameter acquisition,data processing and data reporting.Among them,the data acquisition program realizes the microcontroller STM32L431RCT6 control sensor ADS1292R,MKB0805,MAX30102,MPU6050and temperature detection circuit to collect five physiological parameters and motion state of the human body,including ECG,respiration,blood pressure,oxygen saturation and body temperature.In the data processing program,the median filtering algorithm is used to filter the baseline drift in ECG and respiratory signals,the FIR low-pass filter is used with 5-point smooth filtering to filter the electromyographic interference in ECG signals,and the difference threshold method is used to realize R-wave positioning,so as to calculate the heart rate.In addition,the data processing program also calculates the acceleration vector module_,angular velocity vector module_and inclination Angleθto judge the fall.The data reporting program packages the data into JSON format and then uploads it to Alibaba Cloud platform via NB-IOT network.The Internet of Things cloud platform stores the data reported by the acquisition terminal and provides services to the mobile client.The mobile client is written under the Io T-Studio iot application development platform to provide users with real-time parameter display,historical parameter query,health services and other functions,so as to achieve health management.This system uses the latest NB-IOT technology based on 5G cellular network.Compared with traditional communication methods such as Bluetooth,ziggbee,WIFI and 4G,it does not need gateway networking and can directly connect with the cloud platform.Moreover,it has the advantages of wide coverage,low cost and power consumption.According to the test,the relative error of the four parameters detected by the system such as heart rate,respiratory rate,blood pressure and blood oxygen is less than or equal to 5%,the relative error of body temperature is less than or equal to1%,and the false positive rate of fall judgment is less than 8%.The accuracy is good,and the system is small in size,low in power consumption and good in real time,which has positive research significance for the development of telemedicine under the background of population aging.