The Research Of Exercise Ecg Modeling Theory And Applications

ECG (Electrocardiograph) is a curve produced by electronic device which records the changes of cardiac potential along with time passes, reflecting the biological potential variation of cardiac stimulation generation, conduction and recovery process. As ECG containing huge information of cardiac status, further research for ECG play an important role in diagnosis, treatment and prevention of cardiovascular disease and arrhythmia. In recent years, The application of ECG continues to broaden, it extends from diagnosis to monitoring treatment and prognosis analysis:(1) In the respect of diagnosis, ECG is a irreplaceable noninvasive method for diagnosis of arrhythmia, myocardial infarction, coronary heart disease;(2) In the respect of monitoring treatment, ECG is helpful for detection and treatment of congenital heart disease and myocarditis, and many experts draw ECG has important clinical value in the diagnosis of arrhythmia, by generalizing arrhythmia in24hours ambulatory electrocardiogram;(3) In clinical ECG is applied in risk prediction and evaluation of diagnosis and treatment.In short ECG has significant clinical research value, and deserves to take a further research for its unique advantage such Non-invasive and inexpensive.EECG (Exercise Electrocardiograph) is a method that induce myocardial ischemia by increasing the amount of cardiac stress, and further to induce the characteristics change of ischemic ECG R-wave amplitude, RR interval, ST segment period and heart rate. It can vividly reflect the cardiac symptoms of subjects in activities and stationary state, which in all can help doctors take quantitative examination for heart disease such as arrhythmias and myocardial ischemia. Meanwhile, EECG also applied in non-invasive cardiac function testing comprehensively like cardiac function assessment, evaluation of the efficacy of heart disease surgical therapy, determine physical therapy and exercise prescription. In EECG, QRS wave is a core characteristic wave. Every person has his own unique QRS, so it can be used in identification. The position of RR interval can be detected by QRS, and RR interval can determine human heart rate, ST-segment elevation and T wave parameters can be used to diagnosis and monitor myocardial infarction and be important basis item to assess pilot medical status.In summary, a further study of ECG has important theoretical and clinical significance. This paper focused on analysis method and application of EECG, and divided the paper into three parts:This first part discussed the analysis and application simulation of the noise in ECG The part elaborated several common methods of ECG analysis firstly; then a stationary wavelet transform denoising algorithm was put forward. Compared this algorithm with FIR low-pass filter, empirical mode decomposition (EMD) algorithm, and with the use of simulation of MTT/BIH ECG database, a sound denoising result was gained.The second part took a further research for detection of characteristics of ECG QRS complex. After analyzing the characteristic of threshold method and the quadratic spline wavelet transform algorithm, a new algorithm for detection of ECG QRS wave group was put forward----first derivative wavelet transform algorithm based on Gaussian function. The simulation results showed that the accuracy of detection of QRS complex using this algorithm is significantly improved compared with threshold method and quadratic spline wavelet transform algorithm.The third part carried out the experimental study of the EECG. Firstly, we collected the EECG data of50groups of college students in nine statue as the supine and upright,0-degree sitting posture,11-degree sitting posture,21-degree sitting posture, walking with speed of1m/s, running with speed of2m/s and walking with speed of1m/s after running by physiological signal telemetry. The noise in EECG was reduced comprehensively and the QRS wave group was detected.