Denoising method for colonic pressure signals based on improved wavelet threshold.

IF 1.3 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Biomedical Physics & Engineering Express Pub Date : 2024-10-25 DOI:10.1088/2057-1976/ad81fc
Liu Cui, Zhisen Si, Kai Zhao, Shuangkui Wang
{"title":"Denoising method for colonic pressure signals based on improved wavelet threshold.","authors":"Liu Cui, Zhisen Si, Kai Zhao, Shuangkui Wang","doi":"10.1088/2057-1976/ad81fc","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":8896,"journal":{"name":"Biomedical Physics & Engineering Express","volume":" ","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomedical Physics & Engineering Express","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/2057-1976/ad81fc","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

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.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于改进小波阈值的结肠压力信号去噪方法
结肠蠕动压力信号有助于肠道疾病的诊断,但由于受到各种因素的干扰,很难反映结肠蠕动的真实情况。为解决这一问题,本文提出了一种基于离散小波变换的改进型小波阈值去噪方法。该算法能有效提取结肠蠕动压力信号并滤除噪声。首先,构建了具有三个形状调整因子的阈值函数,使函数具有连续性和更好的灵活性。然后,设计了一种基于不同分解级别的阈值计算方法。通过调整三个预设形状因子,确定合适的阈值函数,并通过分层阈值法实现结肠压力信号的去噪。此外,对颠簸信号的实验分析验证了所提出的去噪方法在处理非平稳信号时具有良好的可靠性和稳定性。最后,利用结肠压力信号验证了所提方法的去噪性能。实验结果表明,与其他方法相比,该方法在去噪和提取结肠蠕动压力信号方面表现更佳,有助于进一步识别和治疗结肠蠕动障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Biomedical Physics & Engineering Express
Biomedical Physics & Engineering Express RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
2.80
自引率
0.00%
发文量
153
期刊介绍: BPEX is an inclusive, international, multidisciplinary journal devoted to publishing new research on any application of physics and/or engineering in medicine and/or biology. Characterized by a broad geographical coverage and a fast-track peer-review process, relevant topics include all aspects of biophysics, medical physics and biomedical engineering. Papers that are almost entirely clinical or biological in their focus are not suitable. The journal has an emphasis on publishing interdisciplinary work and bringing research fields together, encompassing experimental, theoretical and computational work.
期刊最新文献
Dose compensation for decreased biological effective dose due to intrafractional interruption during radiotherapy: integration with a commercial treatment planning system. Open-window MSR Design with Active Magnetic Compensation Coil based on COMSOL Multiphysics. A new method to assess the performance of anti-scatter grids in x-ray projection imaging. Effect of tissue viscoelasticity on delivered mechanical power in a physical respiratory system model: distinguishing between airway and tissue resistance. Local field potential-based brain-machine interface to inhibit epileptic seizures by spinal cord electrical stimulation.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1