Carolina Ruiz, left, and Bengisu Tulu, are two of the developers of the smartphone app SlipBuddy, which integrates behavioral strategies and technologies like mobile devices, machine learning and text mining to help users avoid overeating. Source: Worcester Polytechnic Institute (WPI)As the season of indulgences heads into full swing, take heart in knowing that help resisting all those yummy treats may be just around the corner.
Researchers at Worcester Polytechnic Institute (WPI) and the University of Connecticut (UConn) are collaborating on a promising smartphone app aimed at helping users manage their overeating challenges in three key ways: by tracking eating patterns, providing interventions and helping change behavior.
The WPI/UConn research report noted that a user study of 16 participants, all over the age of 18, overweight and not necessarily trying to lose weight, showed positive results. At the end of the month-long pilot, nine of the participants lost an average of five pounds, three weighed the same and four gained an average of two pounds.
The research team's three-pronged approach, including assistance in changing the user's behavior, is an important differentiator from the nearly 29,000 weight-related apps on the market.
The app, called SlipBuddy, tracks stress and eating, and functions as a personalized intervention system. Built through the integration of behavioral strategies and technologies like mobile devices, machine learning and text mining, the work is aimed at helping users identify what triggers them to overeat and offering new stimuli that trigger healthy behaviors. When the app predicts that the likelihood of overeating is high, it suggests interventions — for example, taking a walk, turning off the TV or engaging in other activities that can help users reduce stress without resorting to eating.
"Mobile technology, which is ubiquitous today, has the capacity to deliver evidence-based weight loss interventions with lower cost and user burden than traditional intervention models," said Carolina Ruiz, associate professor of computer science at WPI and one of the project's principal investigators.
"I'm very hopeful that what we're doing will make a big difference," said Bengisu Tulu, associate professor in WPI's Foisie Business School and also a principal investigator on the project. "Most weight loss apps are all about tracking something — tracking your calories, tracking your blood glucose, tracking your steps. This goes beyond that. We're using machine learning to make this about intervention."
"It's not an easy thing to build," noted Tulu. "Most weight-loss apps are developed by technologists, with not enough input from clinical psychologists or psychiatrists. The task is not trivial. We're working out how to integrate clinical tools into our app. It's an open question we're trying to find answers to."
The researchers are currently working on enhancing the app's graphical user interface, integrating more intervention tools into the system and fine-tuning the machine learning algorithms. A larger user study is expected later in 2018.
The app was built for the Android platform, but eventually will be available for iOS devices, as well. While it is still in the research phase, the researchers say the app could be ready for release as early as 2019.
A paper on the research was recently presented at the annual symposium for the American Medical Informatics Association, a nonprofit organization that focuses on the development of information technology to benefit healthcare. Read more about Slipbuddy here.
