Non-invasive Detection of Bowel Sounds in Real-life Settings Using Spectrogram Zeros and Autoencoding

I. Bilionis, G. Apostolidis, V. Charisis, C. Liatsos, L. Hadjileontiadis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Gastrointestinal (GI) diseases are amongst the most painful and dangerous clinical cases, due to inefficient recognition of symptoms and thus, lack of early-diagnostic tools. The analysis of bowel sounds (BS) has been fundamental for GI diseases, however their long-term recordings require technical and clinical resources along with the patientt's motionless concurrence throughout the auscultation procedure. In this study, an end-to-end non-invasive solution is proposed to detect BS in real-life settings utilizing a smart-belt apparatus along with advanced signal processing and deep neural network algorithms. Thus, high rate of BS identification and separation from other domestic and urban sounds have been achieved over the realization of an experiment where BS recordings were collected and analyzed out of 10 student volunteers.

Original languageBritish English
Title of host publication43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages915-919
Number of pages5
ISBN (Electronic)9781728111797
DOIs
StatePublished - 2021
Event43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, Mexico
Duration: 1 Nov 20215 Nov 2021

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Country/TerritoryMexico
CityVirtual, Online
Period1/11/215/11/21

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