New Smartphone App Could Prevent Overeating
App known as SlipBuddy uses machine learning to discover the eating patterns and Predicts eating trouble spots.
Researchers from Worcester Polytechnic Institute (WPI) and the University of Connecticut (UConn) have developed an app known as SlipBuddy, which is focused on assisting users to manage overeating by tracking eating patterns, providing interventions, and helping change behavior. Study included 16 overweight participants with 18 age and not necessarily trying to lose weight. Nine participants were observed to lose an average of five pounds, three weighed the same, and four gained an average of two pounds.
The drawback with most weight-loss apps is that they are burdensome to use and don’t focus on actually trying to change the user’s behavior. SlipBuddy is a personalized intervention system, which is built through the integration of behavioral strategies and technologies such as mobile devices, machine learning, and text mining. This app is expected to help users in identifying factor triggering overeating. It recognizes unhealthy behaviors and it reminds users to keep accountable to a buddy that suggests better behaviors in a nonjudgmental way. Users are asked to check in three times a day to note their stress levels, fatigue, and hours of sleep, and whenever they feel they have overeaten.
According to Weight Management Market report published by Coherent Market Insights, obesity can lead to severe disorders such as diabetes and cardiovascular problems, which can affect ability of individual to maintain healthy life. Advances in technology such as use of health monitoring apps can help to maintain healthy lifestyle in obese patients. As the app collects information the system uses machine learning to find patterns that can be used to predict when the user is likely to overeat.
The app uncovers user-specific triggers, like late-night eating, watching TV, or sleepless nights. When the app predicts that the likelihood of overeating is high, it suggests interventions, for instance, 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 Ruiz, associate professor of computer science at WPI.
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