Design And Implementation Of Remote Health Monitoring System Based On Wearable Device

In recent years,more and more people have realized the importance of health,and the attention on health is no longer limited to the prevention and treatment of diseases,but more concerned about the monitoring of health in daily life.Traditional medical health monitoring equipment is not suitable for real-time monitoring of personal health because of the need for medical equipment and the difficulty of operation for non-medical personnel.People are increasingly inclined to adopt portable intelligent wearable devices to collect physical signs data.With the rapid development of wireless communication technology,chip technology and sensor technology,it provides technical support for health monitoring auxiliary system.In this context,this paper designed a wearable device-based remote health monitoring system to monitor respiratory rate,heart rate and body surface temperature.First,a chest strap device is designed to judge the physical condition based on the monitored human-related data and alarm.This system selects MPU-6050 inertial sensor,BMD101 ECG sensor and DS18B20 temperature sensor to be installed on the chest strap device to collect respiratory rate,heart rate and body surface temperature respectively.After the collected data is processed,it is sent to the server for processing and storage through the NB-IoT module.Family members or doctors can view the relevant physical signs data and physical health assessment results through the mobile APP to realize real-time health monitoring.Secondly,on the basis of studying the principle of the filtering algorithm,the Kalman filtering algorithm is applied to the respiratory rate calculation of this system,that is,the filtering algorithm is applied to the three-axis acceleration and three-axis angular velocity obtained by the sensor,and the three-axis acceleration and three-axis angular velocity are reduced.The measurement error of angular velocity improves the measurement accuracy of respiratory rate.Finally,the remote server was built,and the relevant server data management software and mobile APP were designed and implemented to realize human-computer interaction and facilitate family members,doctors and other relevant personnel to query the health status of the tested person in real time through the mobile APP.The test results of this system show that adding Kalman filter algorithm can greatly improve the accuracy of respiration rate measurement.The difference between the respiratory rate,heart rate and body surface temperature measured by this system and the comparison test is about 3.81%,0.84%and 0.28%,respectively,which can be used for daily health monitoring.The system has practical significance for the health monitoring of the elderly living alone,the daily health management of patients with chronic diseases,the health monitoring of outdoor adventurers during exploration and the health monitoring of soldiers on the battlefield and other occasions.