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‘Smart toilet’ can detect signs of disease, scientists claim

Getty Images/iStockphoto
Getty Images/iStockphoto

A new “smart toilet” can detect signs of various diseases in a person’s stool and urine, a team of American researchers have claimed.

A team at Stanford University’s School of Medicine in California has invented a device that fits inside a toilet and uses motion-sensing technology in addition to cameras and test strips to analyse what is inside the toilet and send the data to a secure server.

The server will then be able to identify individuals who suffer from a range of conditions, such as irritable bowel syndrome, prostate cancer or kidney failure in addition to seven other illnesses.

It does this by putting the urine through a physical and molecular analysis while the stool is assessed based on its physical characteristics.

In order to differentiate between users, the technology uses scans of fingerprints and images of the anus.

Thus far, the gadget has been tested on 21 people as part of a study published in the journal Nature Biomedical Engineering.

But further research on more individuals is needed before the researchers can say for certain that their toilet system will be effective.

According to lead author of the initial study, Dr Sanjiv Gambhir, professor and chair of radiology at Stanford University’s School of Medicine, his smart toilet concept has been in the works for more than 15 years.

“When I’d bring it up, people would sort of laugh because it seemed like an interesting idea, but also a bit odd,” he said.

The benefit of having a smart toilet, Gambhir added, is that unlike wearable tech, it cannot be taken off.

“Everyone uses the bathroom – there’s really no avoiding it – and that enhances its value as a disease-detecting device.”

As for the system’s unusual way of differentiating between users, Gambhir said: ”We know it seems weird, but as it turns out, your anal print is unique.

“The scans – both finger and nonfinger – are used purely as a recognition system to match users to their specific data.”

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