Literature DB >> 20172793

Digestive activity evaluation by multichannel abdominal sounds analysis.

Radu Ranta1, Valérie Louis-Dorr, Christian Heinrich, Didier Wolf, François Guillemin.   

Abstract

This paper introduces a complete methodology for abdominal sounds analysis, from signal acquisition to statistical data analysis. The goal is to evaluate if and how phonoenterograms can be used to detect different functioning modes of the normal gastrointestinal tract, both in terms of localization and of time evolution during the digestion. After the description of the acquisition protocol and the employed instrumentation, several signal processing steps are presented: wavelet denoising and segmentation, artifact suppression, and source localization. Next, several physiological features are extracted from the processed signals issued from a database of 14 healthy volunteers, recorded during 3 h after a standardized meal. Data analysis is performed using a multifactorial statistical method. Based on the introduced approach, we show that the abdominal regions of healthy volunteers present statistically significant phonoenterographic characteristics, which evolve differently during the normal digestion. The most significant feature allowing us to distinguish regions and time differences is the number of recorded sounds, but important information is also carried by sound amplitudes, frequencies, and durations. Depending on the considered feature, the sounds produced by different abdominal regions (especially stomach, ileocaecal, and lower abdomen regions) present a specific distribution over space and time. This information, statistically validated, is usable in further studies as a comparison term with other normal or pathological conditions.

Mesh:

Year:  2010        PMID: 20172793     DOI: 10.1109/TBME.2010.2040081

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  8 in total

1.  Spectral analysis of bowel sounds in intestinal obstruction using an electronic stethoscope.

Authors:  Siok Siong Ching; Yih Kai Tan
Journal:  World J Gastroenterol       Date:  2012-09-07       Impact factor: 5.742

2.  Non-invasive algorithm for bowel motility estimation using a back-propagation neural network model of bowel sounds.

Authors:  Keo-Sik Kim; Jeong-Hwan Seo; Chul-Gyu Song
Journal:  Biomed Eng Online       Date:  2011-08-10       Impact factor: 2.819

3.  The potential of computerised analysis of bowel sounds for diagnosis of gastrointestinal conditions: a systematic review.

Authors:  Andrisha-Jade Inderjeeth; K Mary Webberley; Josephine Muir; Barry J Marshall
Journal:  Syst Rev       Date:  2018-08-17

4.  An in vitro acoustic analysis and comparison of popular stethoscopes.

Authors:  Daniel Weiss; Christine Erie; Joseph Butera; Ryan Copt; Glenn Yeaw; Mark Harpster; James Hughes; Deeb N Salem
Journal:  Med Devices (Auckl)       Date:  2019-01-15

5.  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

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.  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

8.  Recording and Analysis of Bowel Sounds.

Authors:  Daniel Zaborski; Miroslaw Halczak; Wilhelm Grzesiak; Andrzej Modrzejewski
Journal:  Euroasian J Hepatogastroenterol       Date:  2016-07-09
  8 in total

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