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Yes. Some smart toilets and toilet-mounted trackers use cameras or other sensors with algorithms to classify stool form and follow changes over time. That can help create a bowel log, but current evidence does not show that consumer devices diagnose disease or improve health outcomes. Whether one is useful depends on what it measures, how its claims were validated, its ongoing cost, and how it handles intimate data.

What an AI toilet actually measures

These systems do not analyze health in the abstract: they capture observable signals and use software to classify or summarize them. Stool trackers may assess color, consistency, or form, often using the Bristol Stool Form Scale, a visual classification system for stool shape and consistency.

Products and prototypes differ substantially. Stanford describes a research platform that combines camera-based stool classification with urine test strips for a 10-parameter urinalysis, computer vision to estimate urine flow and volume, sensors that record timing, and biometric identification to associate measurements with a user. Stanford says the prototype was tested with 21 subjects and reports a separate 300-respondent user-acceptance survey; these figures describe prototype and survey stages, not clinical efficacy. The platform description also mentions encrypted cloud storage. Stanford’s research-platform description does not establish that every commercial tracker has these capabilities.

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Other approaches use different signals. One feasibility study used a camera portal to image feces in a defined area of plumbing after flushing. A separate 2021 research paper described an image sensor for sample analysis and pressure sensors for identifying users. An image, a video stream, a pressure reading, and a urine test strip are not interchangeable: each captures different information, and each requires its own validation.

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What the evidence can—and cannot—say

A small real-world stool-form feasibility study

A study published in Neurogastroenterology & Motility in January 2025 (article date November 1, 2024) analyzed 474 bowel-movement images from six healthy volunteers over a mean of 10 months. For classifying abnormal stool form, its algorithm achieved 94% accuracy, 81% sensitivity, and 95% specificity. Those numbers describe performance on that study’s stool-form classification task in a small workplace installation. They are not diagnostic-accuracy figures for disease, nor evidence that the system will perform the same way in a larger or different population. The study report is a feasibility result, not a clinical diagnosis trial.

Simulated samples and exploratory monitoring

A 2021 AI-toilet paper reported neural-network performance using simulated stool types and quantities, and described a pressure-sensor approach to user identification. Performance on simulated material does not establish how well a system works with ordinary bowel movements in homes. The 2021 paper should be read in that context.

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A separate 2025 study analyzed 45 defecation events from 11 participants and reported exploratory measurements of defecation behavior. Its sample and stated purpose do not establish a consumer device’s ability to diagnose illness. The study abstract describes an exploratory line of work.

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Taken together, the evidence supports the possibility of automated stool-form tracking. It does not establish consumer smart toilets as validated diagnostic tests, prove that they detect cancer, or show that using one improves health outcomes at population scale. A flag or change in a log is not a diagnosis; discuss concerning symptoms with a qualified clinician rather than relying on an app interpretation.

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Who may find stool tracking useful

The clearest potential benefit is convenience: a device can keep a longitudinal record without requiring someone to log every bowel movement manually. That may be relevant to people asked by a clinician to keep a bowel log or to those managing digestive conditions, although the available evidence does not establish improved outcomes from using consumer trackers.

For a healthy person with regular bowel movements, the added value is less clear. Gastroenterologist Daniel Freedberg, quoted by WIRED’s September 3, 2026 report, questioned whether image-based AI adds meaningful new science for average users. A system that records patterns may be convenient, but more measurements do not automatically mean more useful medical information.

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Commercial devices: compare what is measured, validated, and charged

WIRED reported the following device prices and memberships on September 3, 2026. Treat them as date-stamped reported prices, not guaranteed current offers. The report described app-based summaries of stool and urine measures and devices that capture images or video directed into the bowl.

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Device Reported device price Reported recurring cost What to keep in mind
Kohler Health $449, as reported September 3, 2026 by WIRED $130 per year for a family membership, as reported September 3, 2026 by WIRED Ask which measurements and app features require membership and what image data are retained.
Throne $399, as reported September 3, 2026 by WIRED $70 per year for a membership, as reported September 3, 2026 by WIRED Check what the membership unlocks and how the device handles image or video data.

These prices alone do not determine which product is a better fit. Before buying, compare the sensor type, whether it captures still images or video, the specific output it provides, and whether any health-related claim has been tested on real-world samples for that use. A plan to detect blood in the future, as described in WIRED’s report, is developmental; it is not evidence that a device currently provides a validated screening test.

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Privacy questions to settle before installing one

Images and measurements from a toilet can reveal sensitive information. WIRED’s review of the companies’ policies described possible sharing with service providers and in legal or corporate situations, such as a merger or sale; the companies also stated restrictions on targeted advertising or selling health data. Policies and product practices can change, so read the current policy for the specific product rather than assuming those terms remain unchanged.

  • Does the device capture still images, video, or both, and when does capture begin?
  • Are raw images or video retained, for how long, and can you delete them?
  • Who can access the raw data and derived summaries, including household members and service providers?
  • What data may be shared in response to legal requests or a corporate transaction?
  • What features stop working if you cancel the membership?
  • Can you export your data in a usable format, or delete your account and its associated data?

Digital-rights advocate Lauren Hendry Parsons of the Mozilla Foundation advises consumers to understand what they share, how it is used, and whether the benefit justifies the trade-off. For a device that may record highly intimate images, those terms are part of the product—not an afterthought.

How to decide whether one makes sense

  1. Start with the need. If you have been asked to track bowel movements, consider whether automated logging would make the task easier. If you have no tracking need, identify what specific decision the device would help you make.
  2. Match the claim to the evidence. Stool-form classification is different from disease detection. Look for real-world participants, the size and duration of the study, and whether its reported accuracy measures the exact function being advertised.
  3. Check the full cost and data terms. Verify current pricing, membership requirements, image retention, sharing, deletion, and export before installation.
  4. Keep the device in its proper role. Treat its summaries as tracking information, not a diagnosis or a substitute for medical advice.

Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.

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