Study On Two-stage Dynamic Cardiac Function Assessment Method

At present,the research focus of dynamic cardiac function only focuses on the cardiac function detection at the cardiac load stage,and the detection and judgment at the cardiac recovery stage can also reflect the state of cardiac function.In the process of heart rate recovery,the changes of electrocardiogram can also reflect the status of cardiovascular system.Therefore,the correlation between heart recovery and load stage is also of considerable research value.In this relationship,dynamic and real-time ECG(electrocardiogram)detection faces with many difficulties,including lightweight ECG waveform detection,two-stage cardiac function correlation parameter design and parameter reliability judgment.In this thesis,by mining the ECG parameters,the changes of the parameters in the process of exercise and recovery were studied,and the relationship between the two stages of exercise and recovery was found.The main work is as follows:1.Algorithm research of real-time monitoring of R wave of ECG signal.The electrocardiogram collected in the process of exercise is noisy and the cost of the computer electrocardiogram processing module is high.Based on the difficulties existing in the motion phase,this thesis proposes the real-time ECG detection and processing of the motion ECG signal through denoising,baseline processing and using the improved lightweight adaptive MMT based R wave detection algorithm.The accuracy of R wave of the algorithm reached 99.98% in the exercise test,and the sensitivity and positive predictive value in the detection of MIT-BIH arrhythmia database reached 99.70% and 99.93%,showing a high detection capability,and the detection results were satisfactory for subsequent studies.2.Correlation analysis of heart rate variability related parameters in two phases.Heart rate variability parameters reflect the ability of nerves to regulate and control the cardiovascular system.In this thesis,heart rate variability r MSSD,p NN50 and other parameters are used to evaluate the correlation between exercise and recovery.In a total of 50 groups of ECG data of 10 subjects,Pearson correlation was used to analyze the relationship between a single group of factors during exercise and recovery,and it was found that some parameters have a high correlation;using typical correlation analysis,the typical The correlation coefficient reduces the dimensionality of the parameter,and then analyzes its rule by linear fitting.It is found that the linear correlation after optimization has a maximum confidence level of 99%.3.Correlation analysis of ECG eigenvalue correlation parameters in two phases.The ECG characteristic value parameters reflect the basic condition of the heart.In this thesis,the parameters such as the QRS wave length,QRS wave area,and the difference between the adjacent T wave amplitude values of the ECG characteristic value are used to evaluate the correlation between the two phases of exercise and recovery.In a total of 50 groups of ECG data of 10 subjects,the Pearson correlation test was used to explore the correlation within a single group of factors,and it was found that each parameter of the single group of factors had a strong correlation during exercise and recovery.Using canonical correlation analysis,the canonical correlation coefficients were reduced to the parameters,and the law was analyzed by linear fitting.The linear correlation after optimization was found to have a 99% confidence level.Based on the physiological information reflected in the experimental data,this study studied the relationship between the cardiac movement stage and the recovery stage in the electrocardiogram.Among them,the R wave detection algorithm is accurate in positioning,which provides a guarantee for subsequent studies.In comparison of heart rate variability parameters and ECG eigenvalue parameters,it is found that the ECG eigenvalue related parameters have a better ability to show the correlation of human body in the process of exercise and recovery.This method provides a set of evaluation system for the relationship between cardiac function in the motion stage and cardiac function in the recovery stage and has a good application prospect in the non-invasive cardiac function detection.