Publications [#383806] of Kyle J. Lafata

Papers Published

1. Zhou, J; Luo, Y; Darcy, JW; Lafata, KJ; Ruiz, JR; Grego, S, Long-term, automated stool monitoring using a novel smart toilet: A feasibility study., Neurogastroenterology and motility, vol. 37 no. 1 (January, 2025), pp. e14954 [doi]
   (last updated on 2026/02/08)

   Abstract:
   

   Background

   Patients' 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).

   Methods

   Our 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 results

   474 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.

   Conclusions

   Our 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.