High-tech toilet can detect deadly diseases just by listening to you go


It’s number two to none.

A new gripping piece of medical technology can detect fatal, fecal diseases inside a person just by listening to their symphonic sounds on the toilet, EurekAlert reported.

The “diarrhea detector,” as its so aptly dubbed, is a high-tech sound system that can indicate when an individual is battling severe bowel diseases like cholera — an illness that kills 150,00 annually.

This state of the fart device was invented by Maia Gatlin of the Georgia Institute of Technology, who recently presented “The feces thesis: Using machine learning to detect diarrhea” to the Acoustical Society of America.

Sound samples from each splendid session get transformed to an audio spectrogram. In a quick pinch, the “noninvasive” machine can isolate the tones of each potty user by the consistency of the sound waves from their endeavors. Urine is a much more constant sound whereas diarrhea — naturally — is extremely scattered.

The Diarrhea Detector is a new piece of tech that listens for severe bowel diseases.

The highly confidential diarrhea data is then processed through an algorithm for specific classification. It’s been properly tested to account for background noises “regardless of the sensor’s environment.”

“The hope is that this sensor, which is small in footprint and noninvasive in approach, could be deployed to areas where cholera outbreaks are a persistent risk,” Gatlin said.

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“The sensor could also be used in disaster zones (where water contamination leads to spread of waterborne pathogens), or even in nursing/hospice care facilities to automatically monitor bowel movements of patients.”

A roll of oilet paper on a toilet cover, concept for constipation and bowel movement.
“The hope is that this sensor, which is small in footprint and noninvasive in approach, could be deployed to areas where cholera outbreaks are a persistent risk,” inventor Maia Gatlin said.
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Gatlin’s next planned phase of the poo project is to “gather real-world acoustic data so that their machine learning model can adapt to work in a variety of bathroom environments.

“Perhaps someday, our algorithm can be used with existing in-home smart devices to monitor one’s own bowel movements and health!”



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