Study On Design And Implementation Of Dynamic ECG Monitoring Software Based On Android Phone

Cardiovascular disease is a serious threat to human health,the world's annual population of about 17 million people died of cardiovascular disease,known as the number one killer of human health.In the Influences of smoking,obesity,stress,lack of exercise and other factors,the number of patients with cardiovascular disease continues to rise.Traditional electrocardiogram(ECG)analysis has been unable to meet the needs of long-term management of cardiovascular disease.With the development of micro processing technology,the emergence of portable and wearable dynamic ECG equipment provides a solution to this problem.Nowadays,there still are many problems of single function,bad user experience,unprofessional product,complicated operating environment in the wearable ECG monitoring products on the market.In this paper,we designed a dynamic ECG monitoring system based on Android,which can provide users with intimate family ECG monitoring service.The main contents of this paper are as follows:(1)According to the noise characteristics of dynamic ECG,this paper analysis the five commonly used filter algorithm.And three adaptive filter,fast FIR filter and fast median filter are designed,which are simple,high signal-to-noise ratio and real-time performance.The MIT/BIH arrhythmia database of Massachusetts Institute of Technology was used as the analysis object,which verified the validity,accuracy and efficiency of the algorithm.(2)For this problem of the high signal-to-energy ratio of the QRS wave of ECG,we designed modified difference algorithm based on the ADT and retrospective check.This algorithm included the initial double thresholds,adaptive threshold dynamic update,zero extreme points,refractory period and retrospective check processing methods,which effectively improve the location accuracy of R wave on the dynamic ECG.In addition,the maximum value of zero crossing detection algorithm based on the window search method is designed for the P wave and T wave,which are difficult to detect.Finally,nine ECG characteristic parameters have important medical value are extracted.(3)As to this problem of the symptoms of myocardial ischemia and arrhythmia,In this paper,two kinds of ECG recognition algorithms,FCM fuzzy clustering algorithm and logical branching algorithm,are compared from four aspects: complexity,adaptability,robustness and recognition effect.And we presented a FCM fuzzy clustering algorithm based on five kinds of abnormal templates,which can effectively achieve the goal of the dynamic ECG system for the analysis of cardiac anomalies.(4)In the aspect of software development of the dynamic ECG monitoring system based on Android,the low-power Bluetooth communication mode was used to dock the small wearable hardware ECG acquisition terminal.Due to the application of the Bluetooth communication mode,we realized dynamic ECG monitoring system of low power consumption,invisibility and sustainability.Dynamic ECG drawing based on standard ECG drawings,the interface can be freely enlarged,while the ECG data storage using the "212" standard format.The function of the dynamic ECG monitoring system is continuously optimized as well as the user interface aesthetic and the interactive experience of the users.(5)In the aspects of the two core functions of the system's real-time heart rate and heart rhythm analysis,we designed the code for 15 healthy subjects and 7 kinds of arrhythmia ECG to detect the R wave and the heart rhythm.From the results of the actual total number of heartbeat,false_chaeck or drop heartbeat number,test heartbeat number,heartbeat detection accuracy and the actual test results and analysis of arrhythmia,verify the stability and effectiveness of the core function of dynamic ECG monitoring system.