ArticleNeurogastroenterology and motility2025
Long-term, automated stool monitoring using a novel smart toilet: A feasibility study.
Article in Neurogastroenterology and motility, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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6 authors.
Funding
Abstract
backgroundPatients' report of bowel movement consistency is unreliable. We demonstrate the feasibility of long-term automated stool image data collection using a novel Smart Toilet and evaluate a deterministic computer-vision analytic approach to assess stool form according to the Bristol Stool Form Scale (BSFS).
methodsOur smart toilet integrates a conventional toilet bowl with an engineered portal to image feces in a predetermined region of the plumbing post-flush. The smart toilet was installed in a workplace bathroom and used by six healthy volunteers. Images were annotated by three experts. A computer vision method based on deep learning segmentation and mathematically defined hand-crafted features was developed to quantify morphological attributes of stool from images. KEY
results474 bowel movements images were recorded in total from six subjects over a mean period of 10 months. 3% of images were rated abnormal with stool consistency BSFS 2 and 4% were BSFS 6. Our image analysis algorithm leverages interpretable morphological features and achieves classification of abnormal stool form with 94% accuracy, 81% sensitivity and 95% specificity.
conclusionsOur study supports the feasibility and accuracy of long-term, non-invasive automated stool form monitoring with the novel smart toilet system which can eliminate the patient burden of tracking bowel forms.
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