信号(编程语言)
降噪
噪音(视频)
人工智能
模式识别(心理学)
计算机科学
图像(数学)
程序设计语言
作者
Liu Cui,Fan Yang,Kai Zhao,Yupeng Du
标识
DOI:10.4015/s1016237224500030
摘要
Colonic pressure is a principal parameter reflecting intestinal motility, and is also an important basis for diagnosing intestinal motility disorders. The physiological signals of the colon are mixed with the disturbing signals such as breathing and heartbeat due to the complex environment of the intestine. It is essential to find an effective method to reduce the noise in the signals. To solve this problem, a combined denoising method of colonic pressure signals is proposed in this paper, which combines the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and wavelet transform. In this method, colonic peristalsis pressure signal is first separated out by wavelet transform, then decomposed by CEEMDAN. According to pearson correlation coefficient, the high-frequency intrinsic mode functions (IMFs) with noise was selected and denoised by wavelet threshold. Finally, the signal was reconstructed by combining the reserved IMFs with the denoised IMFs. The validity of the proposed method is verified by the real colon pressure data collected by the wireless motility capsule in this paper. The experimental results show that the combined denoising method can deal with the noise better than the single denoising method on the premise of fully retaining the real components of the colonic pressure signal.
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