Since Alexander Cummings patented the toilet in 1775, many were the changes that this device would go through until it reached its final form.

Currently there are toilets of all kinds, but until now none had been created that had the ability to detect diseases like this one that we present below.

It is an initiative proposed by the research engineer from the Georgia Institute of Technology, Maia Gatlin who was given the task of creating a way to take advantage of artificial intelligence to detect diarrhea in people.

With the name of “The Feces Thesis: Using Machine Learning to Detect Diarrhea» Gatlin presented his project at the annual meeting of the Acoustical Society of America, where he explained how it can be done Using machine learning to detect diseases in the gut.

For this, a non-invasive microphone sensorso that with the help of artificial intelligence the infection can be recognized without the need to perform tests in a medical center to collect additional data.

To test the effectiveness of this method, Gatlin used the microphone and machine learning to detect diarrhea using audio files from online resources.

So for each audio sample of an excretion or bowel movement, a spectrogramwhich refers to the capturing a sound in an image.

Different types of excretion resulted in different characteristics present both in the audio and in the generated spectrogram.

So in regards to diarrheal tonethe researchers agreed that it produced a more random sound.

Once the spectrogram images were obtained, they were used as input for the machine learning algorithm, whose performance was put to the test. using data with and without background noisein order to guarantee a clean capture of the sound, so that it could later be interpreted by the sensor regardless of the environment.

Thanks to these results, Gatlin remains optimistic that this microphonic sensor can be implemented in places where the appearance of intestinal infections such as cholera is frequent.

In this regard, Gatlin expressed the following:

We hope this space-saving, non-invasive sensor can be deployed in areas where cholera outbreaks are a persistent risk.