基于ARMA-APARCH模型和神经网络分类的心电数据挖掘

ECG Mining based on ARMA-APARCH Model and Neural Networks Classification

对ECG信号建议了基于ARMA-APARCH模型的特征提取新方法。经过对ECG信号进行预处理后,采用神经网络分类对MIT-BIH数据集的三种ECG信号进行数据挖掘,统计表明基于ARMA-APARCH模型和神经网络分类的心电识别精度较高。

The new method of feature extraction of ECG signal is proposed based on ARMA-APARCH model.The new feature extraction method is used to cluster analysis of three kinds of ECG signals of MIT-BIH after preprocessing the ECG signal.Statistics show that the accuracy of clustering after feature extraction based on ARMA-APARCH model.