Cardiovascular Event Risk Assessment Algorithm Based On JT Interval And Its Application

With the rapid growth of the social economy,people's life stress is getting bigger and bigger,and more and more people are beginning to suffer from cardiovascular and cerebrovascular diseases.The ventricular repolarization variability is associated with a variety of malignant heart diseases such as myocardial ischemia and hypertension,and most patients with high-risk arrhythmia can observe ventricular repolarization.Medical ventricular repolarization corresponds to the JT interval of surface ECG.JT interval analysis helps reduce the risk of illness and speed up the recovery process after disease diagnosis and treatment.China's current family medical environment is relatively poor: on the one hand,the per capita income level is relatively backward,while on the other hand,the population is large and the hospital resources are limited.Under this premise,designing an ECG-based ECG monitoring and early warning system is of great significance,not only for the monitoring of patients with heart disease,but also for real-time monitoring of patients after surgery.This paper first studies the preprocessing and feature extraction of ECG signals.The interference is removed by wavelet transform and median filtering.The QRS waveform localization algorithm of Pan &Tompkins is used to extract the QRS waveform,and the window search method is combined with the position field/magnitude/slope to locate the J point and the T wave start and end points and peak points.Get the JT related interval.Then,three algorithms were used to study the JT interval in various ECG databases.The JT-related interphase variability coefficient JTiCV was analyzed in 84 patients and 42 normal subjects.Among them,i={b,p,e} respectively represent the starting point,vertex and end point of T wave;analyze the time-frequency distribution of JT interval sequence of 33 patients and 13 normal people and according to frequency divide it into low frequency(LF),intermediate frequency(MF)and high frequency(HF)frequency bands;analysis of 12 lead data of 30 patients and 30 normal people,calculate their JTid.For the array with a small sample content,the two-side t-test comparing the two groups of sample means is used to calculate the treatment result and obtain the P value.When P<0.05,the mean value of the two test samples is considered to be significantly different.Statistical significance.Finally,by analyzing the above three algorithm parameters,the comprehensive evaluation criteria of cardiac event risk is proposed,which provides new clues and new ideas for determining cardiac events.The above three algorithms are deployed to the medical cloud platform(server),and a ECG monitoring and early warning system is built by using the Android smart phone,including the three parts of the ECG collection terminal,the medical cloud platform and the ECG monitoring system App.Data is transmitted between them via 4G network or WIFI.Users can view their ECG waveforms and test results by clicking Start Detection and Historical Data on the App.When the user's test results meet the comprehensive assessment criteria for cardiac event risk,the system will provide an alert.Finally,the actual monitoring experiment was carried out on the designed ECG monitoring system,and the monitoring results were analyzed and evaluated.This article can realize the monitoring of the JT interval of the user's ECG signal,timely discover the ventricular repolarization variation,and provide data support for clinical diagnosis.