Denoising method for colonic pressure signals based on improved wavelet threshold

被引:0
|
作者
Cui, Liu [1 ]
Si, Zhisen [1 ]
Zhao, Kai [2 ]
Wang, Shuangkui [1 ]
机构
[1] Shanghai Inst Technol, Dept Comp Sci & Informat Engn, Shanghai 201418, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Shanghai 200240, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
colonic pressure signals; wavelet denoising; threshold function; hierarchical thresholding;
D O I
10.1088/2057-1976/ad81fc
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
The colonic peristaltic pressure signal is helpful for the diagnosis of intestinal diseases, but it is difficult to reflect the real situation of colonic peristalsis due to the interference of various factors. To solve this problem, an improved wavelet threshold denoising method based on discrete wavelet transform is proposed in this paper. This algorithm can effectively extract colonic peristaltic pressure signals and filter out noise. Firstly, a threshold function with three shape adjustment factors is constructed to give the function continuity and better flexibility. Then, a threshold calculation method based on different decomposition levels is designed. By adjusting the three preset shape factors, an appropriate threshold function is determined, and denoising of colonic pressure signals is achieved through hierarchical thresholding. In addition, the experimental analysis of bumps signal verifies that the proposed denoising method has good reliability and stability when dealing with non-stationary signals. Finally, the denoising performance of the proposed method was validated using colonic pressure signals. The experimental results indicate that, compared to other methods, this approach performs better in denoising and extracting colonic peristaltic pressure signals, aiding in further identification and treatment of colonic peristalsis disorders.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] ECG signals Denoising Method Based on Improved Wavelet Threshold Algorithm
    Zhang Lin
    Lin Jia-lun
    Li Xiao-ling
    Wang Wei-quan
    PROCEEDINGS OF 2016 IEEE ADVANCED INFORMATION MANAGEMENT, COMMUNICATES, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IMCEC 2016), 2016, : 1779 - 1784
  • [2] An improved wavelet adaptive logarithmic threshold denoising method for analysing pressure signals in a transonic compressor
    Meng, Bo
    Li, Zhiping
    Wang, Haihui
    Li, Qiushi
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2015, 229 (11) : 2023 - 2030
  • [3] Improved Threshold Denoising Method Based on Wavelet Transform
    Cui Huimin
    Zhao Ruimei
    Hou Yanli
    2012 INTERNATIONAL CONFERENCE ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING (ICMPBE2012), 2012, 33 : 1354 - 1359
  • [4] A WAVELET DENOISING METHOD BASED ON THE IMPROVED THRESHOLD FUNCTION
    Wang, Jian-Fei
    2014 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION (ICWAPR), 2014, : 70 - 74
  • [5] Improved Threshold Denoising Method Based on Wavelet Transform
    Zhao Rui-mei
    Cui Hui-min
    2015 7th International Conference on Modelling, Identification and Control (ICMIC), 2014, : 114 - 117
  • [6] A Wavelet Denoising Method Based on Improved Threshold and Autocorrelation
    Qian, Ying
    PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC), 2018, : 4058 - 4063
  • [7] Improved wavelet threshold denoising method for magnetic field signals of magnetic targets
    Lu, Binjie
    Zhang, Xiaobing
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2025, 36 (03)
  • [8] Image denoising method based on improved wavelet threshold algorithm
    Zhu, Guowu
    Liu, Bingyou
    Yang, Pan
    Fan, Xuan
    MULTIMEDIA TOOLS AND APPLICATIONS, 2024, 83 (26) : 67997 - 68011
  • [9] Research on signal denoising method based on improved wavelet threshold
    Li, Xinxin
    Zeng, Liansun
    PROCEEDINGS OF 2023 7TH INTERNATIONAL CONFERENCE ON ELECTRONIC INFORMATION TECHNOLOGY AND COMPUTER ENGINEERING, EITCE 2023, 2023, : 857 - 861
  • [10] Gamma spectrum denoising method based on improved wavelet threshold
    Xie, Bo
    Xiong, Zhangqiang
    Wang, Zhijian
    Zhang, Lijiao
    Zhang, Dazhou
    Li, Fusheng
    NUCLEAR ENGINEERING AND TECHNOLOGY, 2020, 52 (08) : 1771 - 1776