ArticleSensors (Basel, Switzerland)2022
Automated Bowel Sound and Motility Analysis with CNN Using a Smartphone.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- A CNN-MAMBA-Based Framework for Salient Bowel Sound Detection and Gastrointestinal Health Assessment.Sensors (Basel, Switzerland) · 2026Article
- Deep learning-based detection of bowel sound events in continuous recordings.Scientific reports · 2026Article
- Clinical Applications and Mathematical Models of Bowel Sounds.Biomedicines · 2026Review
- A Two-Step Sensor Fusion Methodology to Assess Damage on Drone Propellers by Audio and Radar Measurements.Sensors (Basel, Switzerland) · 2026Article
- Review
- Behavioral and human-computer interaction requirements for a candidate abdominal-sound-enabled dietary self-regulation system: a two-phase study in Taiwanese university students.Frontiers in nutrition · 2026Article
- Context-aware digital nutrition and abdominal acoustic feedback in Taiwanese university students: a 12-week single-arm field intervention and a separate 4-week randomized feasibility pilot.Frontiers in nutrition · 2026Article
- Benchmarking machine learning for bowel sound pattern classification - From tabular features to pretrained models.PloS one · 2026Article
- Gastrointestinal emergencies and monitoring in preterm infants: a review.Annals of medicine · 2025Review
- Prospects of AI-Powered Bowel Sound Analytics for Diagnosis, Characterization, and Treatment Management of Inflammatory Bowel Disease.Medical sciences (Basel, Switzerland) · 2025Review
- Explainable ResNet-long short-term memory model for the classification of bowel sounds frequency based on multifeature fusion.The Journal of international medical research · 2025Article
- Disease Prediction Using Machine Learning on Smartphone-Based Eye, Skin, and Voice Data: Scoping Review.JMIR AI · 2025Review
- Article
- Low-cost and convenient screening of disease using analysis of physical measurements and recordings.PLOS digital health · 2024Review
- Article
- Non-Invasive Sensors Integration for NCDs with AIoT Based Telemedicine System.Sensors (Basel, Switzerland) · 2024Article
- Bat2Web: A Framework for Real-Time Classification of Bat Species Echolocation Signals Using Audio Sensor Data.Sensors (Basel, Switzerland) · 2024Article
- Enhancing bowel sound recognition with self-attention and self-supervised pre-training.PloS one · 2024Article
- Experimental Investigation of Acoustic Features to Optimize Intelligibility in Cochlear Implants.Sensors (Basel, Switzerland) · 2023Article
- Design and Development of a Non-Contact ECG-Based Human Emotion Recognition System Using SVM and RF Classifiers.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bowel sound (BS) is receiving more attention as an indicator of gut health since it can be acquired non-invasively. Current gut health diagnostic tests require special devices that are limited to hospital settings. This study aimed to develop a prototype smartphone application that can record BS using built-in microphones and automatically analyze the sounds. Using smartphones, we collected BSs from 100 participants (age 37.6 ± 9.7). During screening and annotation, we obtained 5929 BS segments. Based on the annotated recordings, we developed and compared two BS recognition models: CNN and LSTM. Our CNN model could detect BSs with an accuracy of 88.9% andan F measure of 72.3% using cross evaluation, thus displaying better performance than the LSTM model (82.4% accuracy and 65.8% F measure using cross validation). Furthermore, the BS to sound interval, which indicates a bowel motility, predicted by the CNN model correlated to over 98% with manual labels. Using built-in smartphone microphones, we constructed a CNN model that can recognize BSs with moderate accuracy, thus providing a putative non-invasive tool for conveniently determining gut health and demonstrating the potential of automated BS research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.