算法
降噪
阈值
计算机科学
阶跃检测
自适应滤波器
信号(编程语言)
心磁图
噪音(视频)
滤波器(信号处理)
人工智能
计算机视觉
物理
量子力学
图像(数学)
程序设计语言
作者
Ming‐Yuan Chen,Cheng Qian,Gaofeng Xie,Keyan Zhao,Yizhuo Zhou,Baolin Xing,S. Q. Tang,Ruiqi Wang,Junping Duan,Jiayun Wang,Binzhen Zhang
标识
DOI:10.1016/j.bspc.2023.105681
摘要
In the diagnosis and treatment of cardiac diseases, magnetocardiography (MCG) technology is characterized by non-invasive, non-contact, and high precision. Therefore, it has currently become a research hotspot in the field of new medical technologies. However, due to the weak signal of the magnetocardiography, the noise needs to be filtered after acquisition. In this paper, an optimized variational mode decomposition algorithm based on the improved threshold method and the improved whale optimization algorithm (WOA) is proposed to process the MCG signal. In order to improve the denoising accuracy, the improved whale optimization algorithm, VMD algorithm, and the improved threshold method are combined. Firstly, the correlation coefficients are obtained by the improved whale optimization algorithm to decompose the IMFs, then the baseline drift is removed by using the moving average method for the low-frequency IMFs, and then the improved thresholding algorithm is applied to each IMF. Finally, the denoised signal is obtained by integration. Experimental tests show that the algorithm has good denoising performance compared with similar algorithms and can filter environmental noise as much as possible without changing the original signal information. The proposed method has the highest Signal-to-Noise Ratio improvement (SNRimp) and Correlation Coefficient (CC) and the lowest Percentage Root Mean Square Difference (PDR). Also, the method is validated in real MCG signal processing. The proposed algorithm can be applied in the field of signal denoising, and it has a wide range of application backgrounds.
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