Researchers
to test wearable device for weight loss
Brown University
 |
| Tonmoy Ghosh, a doctoral student at the University of Alabama, models a wearable, high-tech ingestion monitor that monitors food intake and may help users to lose weight. Photo courtesy the University of Alabama. |
Researchers at the Miriam Hospital
and Brown University, in collaboration with several other universities across
the country, will seek to answer that question in a clinical trial funded by a
$2.5 million grant from the National Institute of Health.
Graham Thomas, an associate
professor of psychiatry and human behavior (research) at Brown and a behavioral
scientist with the Miriam’s Weight
Control and Diabetes Research Center, is the project’s co-principal
investigator.
He will use an ingenious device developed in collaboration with researchers at the University of Alabama to test the technology with adults with overweight or obesity.
He will use an ingenious device developed in collaboration with researchers at the University of Alabama to test the technology with adults with overweight or obesity.
“The hope is that this technology
will give people a new, less burdensome way to monitor and take control of
their eating,” Thomas said.
The device, clipped to prescription
or nonprescription eyeglasses, includes a tiny, high-definition camera to
photograph food as well as sensors that monitor chewing.
The sensors accurately detect food intake and trigger the camera to record what was eaten and to measure when, how much and how fast the wearer eats.
The sensors accurately detect food intake and trigger the camera to record what was eaten and to measure when, how much and how fast the wearer eats.
Edward Sazonov, a professor of electrical and computer engineering at the University of Alabama and co-principal investigator, designed the patent-pending device, which he calls the Automatic Ingestion Monitor, or AIM.
“Changing eating behavior enough to
achieve and maintain long-term weight loss is elusive,” Sazonov said. “We’re
seeking to determine if a device that adapts to your individual eating habits
can change that.”
Thomas said that Sazonov was looking
to test his device and reached out to him about a collaboration because of his
expertise in the science of health behaviors.
“My work has focused on the use of
technology to understand and promote healthy behaviors, particularly those
related to obesity,” Thomas said.
“So this is right up my alley.”
The grant to the University of
Alabama, via the NIH’s National
Institute of Diabetes and Digestive and Kidney Diseases, will enable
the researchers to test the
device in a clinical trial over four years.
An initial round of funding was awarded this fall. About half of the patients enrolled in the study will be recruited in Rhode Island by Thomas.
An initial round of funding was awarded this fall. About half of the patients enrolled in the study will be recruited in Rhode Island by Thomas.
During the clinical trial, the
device’s built-in computer will communicate with the wearer’s smartphone and,
when necessary, trigger the phone to send carefully designed messages
suggesting modifications to the wearer’s eating behaviors.
Work by other researchers has shown
that tracking what you eat by hand is one of the most powerful strategies for
weight control, but it can be burdensome, tedious and error prone.
Electronic fitness trackers have proven popular, so for those open to a high-tech wearable method to help in modifying their behaviors, the device could prove effective.
Electronic fitness trackers have proven popular, so for those open to a high-tech wearable method to help in modifying their behaviors, the device could prove effective.
“The key to this particular
technology is to learn individual eating behaviors and then attempt to provide
personalized feedback to modify those behaviors,” Sazonov said.
Measuring food intake, which
previous studies show the technology can do accurately, is important. But it’s
only part of the story.
“The way you eat is as important as
what you eat,” Sazonov said.
“We are also looking at the rates of ingestion. We want to slow down and be more mindful about our eating. Every person is different in when they eat, what they eat, how much they eat and how long they eat. We use machine learning to create a model of these individual eating patterns. After we learn the individual eating patterns, we see how it can be manipulated by suggesting small changes to reduce the total amount of energy consumed.”
“We are also looking at the rates of ingestion. We want to slow down and be more mindful about our eating. Every person is different in when they eat, what they eat, how much they eat and how long they eat. We use machine learning to create a model of these individual eating patterns. After we learn the individual eating patterns, we see how it can be manipulated by suggesting small changes to reduce the total amount of energy consumed.”
Additional researchers on the
project include Megan McCrory of Boston University, Janine Higgins of
University of Colorado, and the University of Alabama’s Chris Crawford and
Jason Parton.
This story was adapted from a news story authored
by Richard Salit of the Miriam Hospital.
