Literature DB >> 30307875

Advances in Acoustic Signal Processing Techniques for Enhanced Bowel Sound Analysis.

Gary Allwood, Xuhao Du, K Mary Webberley, Adam Osseiran, Barry James Marshall.   

Abstract

With the invention of the electronic stethoscope and other similar recording and data logging devices, acoustic signal processing concepts and methods can now be applied to bowel sounds. In this paper, the literature pertaining to acoustic signal processing for bowel sound analysis is reviewed and discussed. The paper outlines some of the fundamental approaches and machine learning principles that may be used in bowel sound analysis. The advances in signal processing techniques that have allowed useful information to be obtained from bowel sounds from a historical perspective are provided. The document specifically address the progress in bowel sound analysis, such as improved noise reduction, segmentation, signal enhancement, feature extraction, localization of sounds, and machine learning techniques. We have found that advanced acoustic signal processing incorporating novel machine learning methods and artificial intelligence can lead to better interpretation of acoustic information emanating from the bowel.

Entities:  

Mesh:

Year:  2018        PMID: 30307875     DOI: 10.1109/RBME.2018.2874037

Source DB:  PubMed          Journal:  IEEE Rev Biomed Eng        ISSN: 1937-3333


  9 in total

Review 1.  Artificial Intelligence in Endoscopy.

Authors:  Alexander Hann; Alexander Meining
Journal:  Visc Med       Date:  2021-11-01

2.  New Methods for the Acoustic-Signal Segmentation of the Temporomandibular Joint.

Authors:  Marcin Kajor; Dariusz Kucharski; Justyna Grochala; Jolanta E Loster
Journal:  J Clin Med       Date:  2022-05-11       Impact factor: 4.964

3.  Bowel Sounds Identification and Migrating Motor Complex Detection with Low-Cost Piezoelectric Acoustic Sensing Device.

Authors:  Xuhao Du; Gary Allwood; Katherine Mary Webberley; Adam Osseiran; Barry J Marshall
Journal:  Sensors (Basel)       Date:  2018-12-03       Impact factor: 3.576

4.  Noninvasive Diagnosis of Irritable Bowel Syndrome via Bowel Sound Features: Proof of Concept.

Authors:  Xuhao Du; Gary Allwood; K Mary Webberley; Andrisha-Jade Inderjeeth; Adam Osseiran; Barry James Marshall
Journal:  Clin Transl Gastroenterol       Date:  2019-03       Impact factor: 4.488

5.  Development of a bowel sound detector adapted to demonstrate the effect of food intake.

Authors:  Ning Wang; Alison Testa; Barry J Marshall
Journal:  Biomed Eng Online       Date:  2022-01-04       Impact factor: 2.819

Review 6.  Automated Bowel Sound Analysis: An Overview.

Authors:  Jan Krzysztof Nowak; Robert Nowak; Kacper Radzikowski; Ireneusz Grulkowski; Jaroslaw Walkowiak
Journal:  Sensors (Basel)       Date:  2021-08-05       Impact factor: 3.576

7.  iApp: An Autonomous Inspection, Auscultation, Percussion, and Palpation Platform.

Authors:  Semin Ryu; Seung-Chan Kim; Dong-Ok Won; Chang Seok Bang; Jeong-Hwan Koh; In Cheol Jeong
Journal:  Front Physiol       Date:  2022-02-14       Impact factor: 4.566

Review 8.  The Research and Development Thinking on the Status of Artificial Intelligence in Traditional Chinese Medicine.

Authors:  Nan Li; Jiarui Yu; Xiaobo Mao; Yuping Zhao; Luqi Huang
Journal:  Evid Based Complement Alternat Med       Date:  2022-05-02       Impact factor: 2.650

9.  Research on a Defecation Pre-Warning Algorithm for the Disabled Elderly Based on a Semi-Supervised Generative Adversarial Network.

Authors:  Yanbiao Zou; Shenghong Wu; Tie Zhang; Yuanhang Yang
Journal:  Sensors (Basel)       Date:  2022-09-05       Impact factor: 3.847

  9 in total

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