基于奇异值选择和小波的心电信号提取方法

2023 International Conference on Pattern Recognition, Machine Vision and Intelligent Algorithms (PRMVIA) Pub Date : 2023-03-01 DOI:10.1109/PRMVIA58252.2023.00052

Fuyu Luo, Xue Han, Zihao Zhang, Ruigang Li, Huixi Wang, Fanrong Kong

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引用次数: 0

摘要

针对接收到的心电信号中存在的噪声，提出了一种基于奇异值选择和小波的心电信号提取方法。首先对心电信号进行奇异值分解，得到各奇异值对应的心电信号分量。然后利用奇异值最大值所对应的信号分量计算与其他分量的互相关系数。结合奇异值的累积贡献率，确定用于心电信号重构的奇异值个数。采用小波阈值降噪方法对最终确定的信号分量进行降噪。最后，通过重构信号分量得到去噪的心电信号。实验结果表明，该方法能够有效地抑制噪声并提取信号，与小波阈值法相比具有良好的降噪效果。

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ECG Signal Extraction Method Based on Singular Value Selection and Wavelet

Aiming at the noise of the received ECG signal, a extraction method of ECG signal based on singular value selection and wavelet is proposed. The singular value decomposition on the ECG signal is performed firstly, and the ECG signal component corresponding to each singular value is obtained. Then the signal component corresponding to the maximum singular value is used to calculate cross-correlation coefficients with other components. The cumulative contribution rate of singular values is combined to determine the number of singular values for ECG signal reconstruction. The wavelet threshold de-noising method is used to de-noise the final determined signal components. Finally, the de-noising ECG signal is obtained by reconstructing the signal components. The experimental results show that the method can suppress noise and extract signal effectively, and it has a good noise reduction effect compared with wavelet threshold method.

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来源期刊

2023 International Conference on Pattern Recognition, Machine Vision and Intelligent Algorithms (PRMVIA)

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