A compression system of ECG data based on neural network

The question of the ECG data compression is one of the most important subject in biosignal processing, If BP Artificial Neural Network is adopted to compress ECG data, the compression precision and the compression ratio are high, but the compression speed is low. The system we established improves the speed by taking some measures. The system adopts four filters to process ECG data for improving the quality of ECG signals, and adopts improved first difference algorithm to detect R points accurately and easily. These works benefit the following compression. During the compression, we combine BP algorithm with TP algorithm and establish a weight template library to improve the rate of compression. The compression precision and compression ratio con melt the requirement anti the processing of ECG data containing a few types of abnormal ECG waves is real time with the system.