The Introduction Of The Morphological Parameters Of The Ecg Recognition Algorithm And Implementation

Electrocardiogram (ECG) is a synthetic reflection of the heart electricity on body surface. It is very valuable to analyze the ECG signal to diagnose the heart disease.With the extensive clinical applications of ECG, more and more research works have been emphasized on accurate and higher-speed ECG automatic classification methods with massive ECG data.In this thesis, first of all, the analysis and classification methods of ECG signal and the present status of automatic ECG analyzer are summarized. After that, the FIR digital filter based on window function is designed and tested through Matlab. It is faster, real-time and efficient.Later on, QRS detecting methods are studied. Two algorithms identifying QRS waves which were applied are analyzed.Then, Arrhythmias have been inevstiagetd deeply. Some familiar arrhythmias have been summarized, and thirteen criterions have been presented. Meanwhile, QRS morphology is considered as a kind of important parameter. Simulation results show the performance is better.Finally, component-based software development is introduced. It can effectively improve the speed and quality of the system development with high reusable possibility.Although the rate of ECG classification is acceptable, future work will be focused on improving the recognition rate.