Tech Could Treat Bad Eating Behaviors

//

Indeed, ear-based systems have already shown promise: Engineers at the Fraunhofer Institute of Photonic Microsystems, in Dresden, tested eight chew-detection algorithms using an in-ear microphone and recently reported 80 percent accuracy for most of them.

The other option is to adapt a photoplethysmogram — a device that detects a change in the volume of tissue by monitoring the way light is absorbed or reflected. The idea here is seeing if there is an unobtrusive spot on the body where the act of chewing produces a readable signal. The Swiss Center for Electronics and Microtechnology (CSEM), a Zurich-based partner in Splendid, is in charge of that aspect of the research.

Fast-Food Ads Still Failing Kids

The American Medical Association has chosen to classify obesity as a disease. This means 90 million people in the U.S. now have a "disease," when, a few days ago, they did not. As Laci tells us, this simple change in wording may have a huge impact.

Where on the body these sensors will go depends on the quality of the signals they achieve, says Delopoulos. “We want to be as invisible as possible,” he says. So they are investigating sensor designs that would go in the ear, sit behind the ear or hang from a necklace, among others.

The project will also include activity monitoring. As the 2014 Consumer Electronics Show (CES) indicated, there’s already a lot of commercially available activity trackers out there.

Delopoulos’ lab itself will be in charge of “signal understanding” — figuring out things like chew rate, meal duration, and other parameters from the signals they can extract from the new wearable sensors. Once they have those signals, they’ll develop the algorithms needed to tell whether a person is at risk for becoming obese, and if they’ve already been asked to modify their behavior, how well they are doing it.

Awesome Images Make You Feel Amazing: Photos

Getting all that into an unobtrusive wearable device wouldn’t have been easy five years ago, say Delopoulos. Android smartphones are now powerful enough to run the needed statistical learning algorithms. And those algorithms themselves are “much more mature now,” he says. “That’s due to research carried out in multimedia indexing and retrieval.”

They’ve got about a year and half to figure out the complete system, then it will be tested on high school kids at an international school in Sweden andyoung adults in The Netherlands.

DISCOVERYnewsletter
 
Invalid Email