Software Design Of Multi-Terminal Remote ECG Monitoring System Based On.NET

Heart disease is a common disease of circulatory system,a serious threat to humans’ health and safety.ECG monitors,which are commonly used in hospitals,play a very important role there.But the distribution of instruments increases the workload of the medical staff.It may even happen that the medical staff cannot get the information in time and delay the timing of the treatment.Therefore,a monitoring system that can display patients’ electrocardiograms remotely and centrally on a screen has very practical significance and promotion value.Based on the.NET framework,this paper designs a monitoring system that can get access to various brands of ECG monitors and display the signals on a screen.ECG data can also be analyzed and stored in this system.The system mainly includes three parts:forwarding clients,display clients and a server.The forwarding clients are responsible for connecting the monitors and the server.The display clients are responsible for presenting the ECG data in real time and giving orders to the designated ECG monitors according to user’s operation.The server will use MySQL database to store information of patients and devices,and use binary files to save ECG data.Considering that there are various brands of ECG monitors on the market,this paper focuses on the scalability of the system and completes the following tasks besides the basic functions:1)A standardized,highly scalable architecture is designed.Based on the public features of different monitors,this paper designs highly generalized interfaces and parent classes,strictly follows the Dependence Inversion Principle(DIP),and uses design patterns such as Factory Pattern and Adapter Pattern,to lay foundations for the adaption of various brands of ECG monitors.2)A common communication process and a communication protocol are designed based on the workflow of different monitors.Forwarding clients resolve and re-package the data and then forwards it,when receiving the data sent by the monitors they connected with,so as to ensure that all the modules involved can ignore the differences between different types of instruments.In addition,this system also combines with Recurrent Neural Network(RNN)to detect Sleep Apnea Syndrome(SAS)at an accuracy of 84.38%.It can recognize SAS using heart rate sequences which can be got easily using ECG monitor.Therefore hardware requirements are greatly reduced when this algorithm is used.