Development of an Affordable Internet of Things-Based Bowel Sound Monitoring System for Analysing Gut Health

Abstract

Traditional approaches are frequently intrusive or subjective, making the objective evaluation of gastrointestinal (GI) health a major clinical challenge. In this work, a low-cost, non-invasive Internet of Things (IoT)-based system for the realtime monitoring of bowel sound frequencies is developed and validated. The system uses an Arduino-based microcontroller to condition and process the abdominal acoustic signals that are recorded by a high-sensitivity Knowles condenser microphone. Twenty male subjects (ages 18 to 24) with a range of Body Mass Index (BMI) classifications were used to gather data on various meal types (solid, semi-solid, and liquid) and timings. Significant pre-meal frequency peaks that indicate the cephalic phase of digestion and a distinctive post-meal "dip-and-rise" pattern that reflects acoustic muffling followed by the reflex of gastrocolic. Especially in subjects who were overweight, solid meals produced greater frequency spikes than liquid meals. There was a lot of variation between people, which suggested that there were different acoustic signatures; however, these patterns were affected by BMI. The results suggest that a person's acoustic signature could be a valuable biomarker for digestive function and reveal that the system could be a viable tool for long-term monitoring of gut health in a personalized way.