Your browser doesn't support javascript.
loading
Denoising method for colonic pressure signals based on improved wavelet threshold.
Cui, Liu; Si, Zhisen; Zhao, Kai; Wang, Shuangkui.
Affiliation
  • Cui L; Department of Computer Science and Information Engineering, Shanghai Institute of Technology, 100 Haiquan Road, Fengxian District, Shanghai, Shanghai, 201418, CHINA.
  • Si Z; Department of Computer Science and Information Engineering, Shanghai Institute of Technology, 100 Haiquan Road, Fengxian District, Shanghai, Shanghai, 201418, CHINA.
  • Zhao K; Shanghai Jiao Tong University, 800 Dongchuan Rd., Shanghai, 200240, CHINA.
  • Wang S; Department of Computer Science and Information Engineering, Shanghai Institute of Technology, 100 Haiquan Road, Fengxian District, Shanghai, Shanghai, 201418, CHINA.
Article in En | MEDLINE | ID: mdl-39353466
ABSTRACT
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Biomed Phys Eng Express Year: 2024 Document type: Article Affiliation country: China Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Biomed Phys Eng Express Year: 2024 Document type: Article Affiliation country: China Country of publication: United kingdom