Abstract
ObjectiveBowel sounds (BS) carry useful information about gastrointestinal condition and feeding status. Interest in computerized bowel sound-based analysis has grown recently and techniques have evolved rapidly. An important first step for these analyses is to extract BS segments, whilst neglecting silent periods. The purpose of this study was to develop a convolutional neural network-based BS detector able to detect all types of BS with accurate time stamps, and to investigate the effect of food consumption on some acoustic features of BS with the proposed detector.ResultsAudio recordings from 40 volunteers were collected and a BS dataset consisting of 6700 manually labelled segments was generated for training and testing the proposed BS detector. The detector attained 91.06% and 90.78% accuracy for the validation dataset and across-subject test dataset, respectively, with a well-balanced sensitivity and specificity. The detection rates evaluated on different BS types were also satisfactory. Four acoustic features were evaluated to investigate the food effect. The total duration and spectral bandwidth of BS showed significant differences before and after food consumption, while no significant difference was observed in mean-crossing rate values.ConclusionWe demonstrated that the proposed BS detector is effective in detecting all types of BS, and providing an accurate time stamp for each BS. The characteristics of BS types and the effect on detection accuracy is discussed. The proposed detector could have clinical application for post-operative ileus prognosis, and monitoring of food intake.
Highlights
Bowel sounds (BS) or gut noises are the rumbling, gurgling or whining noises, produced by the movement of food, liquids and gases through the intestine
We demonstrated that the proposed BS detector is effective in detecting all types of BS, and providing an accurate time stamp for each BS
Two sensors were placed on the participant abdomen, one on the right lower quadrant (RLQ) and another on the left upper quadrant (LUQ)
Summary
Bowel sounds (BS) or gut noises are the rumbling, gurgling or whining noises, produced by the movement of food, liquids and gases through the intestine. Bowel sounds can be used in the prognosis and diagnosis of gastrointestinal conditions. The location, intensity and pitch of the sounds are all considered clinically important [1]. Wang et al BioMedical Engineering OnLine (2022) 21:1 bowel sounds after surgery can indicate an ileus (lack of propulsive movement) before the patient starts vomiting or complaining of abdominal pain. Recent increases in computer processing power and improvements in data analysis bring the potential to employ bowel sound computational analysis to improve evaluation of gastrointestinal conditions [2] or feeding status [3, 4]. Predicting whether a patient will suffer from ileus after abdominal surgery can prevent complications in those affected, and allows unaffected patients to move through the post-operative feeding stages quickly, freeing up space in hospitals
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
