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ECG beat classification using discrete wavelet coefficients

机译:使用离散小波系数的心电图心跳分类

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In this work we have developed a new approach to identify different types of electrocardiogram (ECG) beats using discrete wavelet transform (DWT) coefficients. The purpose of the study is to develop a simple algorithm for the diagnosis of some cardiac abnormalities. Five types of cardiac phenomena are considered and for each of these some particular records from the MIT-BIH Arrhythmia Database are selected. For these records DWT coefficients up to level 4 are calculated in the Matlab 7.4.0 environment, using different types of mother wavelets. The maximum value of the approximation coefficients of level 4 is selected as the indicating parameter, which is used to distinguish between different abnormalities. A comparison is made between the performances of different types of mother wavelets to select the mother wavelet providing the best result.
机译:在这项工作中,我们开发了一种使用离散小波变换(DWT)系数来识别不同类型的心电图(ECG)搏动的新方法。该研究的目的是开发一种用于诊断某些心脏异常的简单算法。考虑了五种心脏现象,并从MIT-BIH心律失常数据库中为每种特定的特定记录进行了选择。对于这些记录,使用不同类型的母子波在Matlab 7.4.0环境中计算了高达4级的DWT系数。选择等级4的近似系数的最大值作为指示参数,其用于区分不同的异常。比较不同类型的母小波的性能,以选择提供最佳结果的母小波。

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