‘Smart toilet’ monitors for signs of disease

It’s still early days, though, with a total of 21 participants having tested the toilet over the course of several months. To get a better feel for “user acceptance” more broadly, the team surveyed 300 prospective smart-toilet users. About 37% said they were “somewhat comfortable” with the idea, and 15% said they were “very comfortable” with the idea of baring it all in the name of precision health.

One of the most important aspects of the smart toilet may well be one of the most surprising — and perhaps unnerving: It has a built-in identification system. “The whole point is to provide precise, individualized health feedback, so we needed to make sure the toilet could discern between users,” Gambhir said. “To do so, we made a flush lever that reads fingerprints.” The team realized, however, that fingerprints aren’t quite foolproof. What if one person uses the toilet, but someone else flushes it? Or what if the toilet is of the auto-flush variety?

They added a small scanner that images a rather camera-shy part of the body. You might call it the polar opposite of facial recognition. In other words, to fully reap the benefits of the smart toilet, users must make their peace with a camera that scans their anus.

“We know it seems weird, but as it turns out, your anal print is unique,” Gambhir said. The scans — both finger and nonfinger — are used purely as a recognition system to match users to their specific data. No one, not you or your doctor, will see the scans.

By no means is this toilet a replacement for a doctor, or even a diagnosis, Gambhir said. In fact, in many cases, the toilet won’t ever report data to the individual user. In an ideal scenario, should something questionable arise — like blood in the urine — an app fitted with privacy protection would send an alert to the user’s health care team, allowing professionals to determine the next steps for a proper diagnosis. The data would be stored in a secure, cloud-based system. Data protection, both in terms of identification and sample analyses, is a crucial piece of this research, Gambhir said. “We have taken rigorous steps to ensure that all the information is de-identified when it’s sent to the cloud and that the information — when sent to health care providers — is protected under HIPAA,” he said, referring to the Health Insurance Portability and Accountability Act, which restricts the disclosure of health care records.

As Gambhir and his team continue to develop the smart toilet, they’re focusing on a few things: increasing the number of participants, integrating molecular features into stool analysis and refining the technologies that are already working. They’re even individualizing the tests deployed by the toilet. For example, someone with diabetes may need his or her urine monitored for glucose, whereas someone else who is predisposed to bladder or kidney cancer might want the toilet to monitor for blood.

Gambhir’s other goal is to further develop molecular analysis for stool samples. “That’s a bit trickier, but we’re working toward it,” Gambhir said. “The smart toilet is the perfect way to harness a source of data that’s typically ignored — and the user doesn’t have to do anything differently.”

Other Stanford co-authors of the paper are Diego Escobedo, an intern in the Molecular Imaging Program at Stanford; former postdoctoral scholar Andre Esteva, PhD; graduate students Alexander Lozano and Amin Aalipour, PhD; urology resident T. Jessie Ge, MD; graduate student Chengyang Yao; former Stanford graduate student Sunil Bodapati; Friso Achterberg, MD, and Jeesu Kim, PhD, visiting scholars of the Molecular Imaging Program at Stanford; research scientist Jung Ho Yu, PhD; undergraduate student Alexander Bhatt; Ryan Spitler, PhD, deputy director of the Precision Health and Integrated Diagnostics Center; and Shan Wang, PhD, professor of materials science engineering and electrical engineering.

Gambhir is a member of Stanford Bio-X, the Stanford Cardiovascular Institute, the Stanford Cancer Institute and the Wu Tsai Neurosciences Institute at Stanford.

Researchers from Seoul Song Do Hospital in South Korea, Case Western Reserve University School of Medicine, the University of Toronto, Leiden University in the Netherlands, Pohang University of Science and Technology in South Korea, and the Catholic University of Korea also contributed to this work.

This study was funded by the National Institutes of Health (grants UL1 TR001085 and T32 CA118681).