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A compression system of ECG data based on neural network

机译:基于神经网络的心电数据压缩系统

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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 can meet the requirement and the processing of ECG data containing a few types of abnormal ECG waves is real time with the system.
机译:ECG数据压缩问题是生物信号处理中最重要的主题之一。如果采用BP人工神经网络对ECG数据进行压缩,则压缩精度和压缩率较高,但压缩速度较慢。我们建立的系统通过采取一些措施提高了速度。系统采用四个滤波器处理ECG数据,以提高ECG信号的质量,并采用改进的一阶差分算法准确,轻松地检测R点。这些工作有益于以下压缩。在压缩过程中,我们结合了BP算法和TP算法,并建立了权重模板库来提高压缩率。系统的压缩精度和压缩率可以满足要求,并且可以实时处理包含几种异常心电图波的心电图数据。

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