Ecg Automatic Analysis Techniques

Cardiac diseases are one of the major diseases that harm human's health. The analysis of ECG is very important for clinical diagnosis of cardiac diseases. The application of computers for accurate and automatic cardiac disease diagnoses has been a hotspot to researchers at home and abroad. Therefore, it is very significant to explore even more accurate and higher-speed automatic ECG analysis method.When detecting and processing ECG signals, first we use the improved adaptive filter to eliminate the power-line interference in ECG signals. It can track the varieties of power-line interference's frequency and range automatically, has very good adaptability. When processing and analyzing QRS waves, then we detect the characteristic points or QRS waves in the method of five-point difference and threshold, pick up the characteristic information. We get some parameters of ECG by filtering the signals and detecting QRS complex and T waves. Then we use these parameters to analyze 12 kinds of arrhythmia in the logic decision-making method. At the same time, we use the information of T waves detected to analyze the ST segment of ECG, obtain voltage and slope of ST segment.The fetal Electrocardiogram (FECG) visualizes the electrical physiological activity of a fetal heart. However the components of the original signals obtained from the abdominal lead are very complex and disturbed heavily by an additive mixture of undesired disturbances, especially the maternal ECG(MECG), which makes it very difficult to extract ideal fetal heartbeat signal. Therefore I have done some work in the research on how to extract FECG accurately and effectively from the mixture signal of human.After developing the system, we test the performance of system's the automatic functions of software, and the testing results satisfy the requests of design. Moreover we do some experiments with the help of volunteers to test the system. The results of experiments show the system has achieved the requests of design.