Rhode Island Hospital Tests mHealth Wearable to Track Eating Habits

A Rhode Island hospital is launching a pilot program to determine whether an mHealth wearable can help users lose weight.

Researchers the The Miriam Hospital, part of the Lifespan Health System, will be using an mHealth device called the Automatic Ingestion Monitor. Developed at the University of Alabama, the AIM attaches to a user’s eyeglasses and monitors eating habits, including what kinds of foods are eaten, how much, how often and how fast.

“Ultimately, we hope that it will be a tool for patients to use to improve their eating habits,” says Graham Thomas, PhD, a behavioral scientist at the Providence-based hospital’s Weight Control and Diabetes Research Center and an associate professor of psychology and human behavior at Brown University. “The information that the AIM collects could be shared with care providers to help them evaluate their progress towards goals for diet and eating, and identify problematic eating behaviors.”

Funded by a $2.5 million grant from the National Institutes of Health, the clinical trial aims to test whether telemedicine technology can help care providers remotely monitor the eating habits of patients dealing with weight issues. Armed with that data, providers could conceivably improve care management for a wide range of chronic issues, including obesity, diabetes, heart disease, high blood pressure and even behavioral health concerns.

Alongside Thomas, the study includes researchers at the University of Alabama, Boston University and the University of Colorado.

“The key to this particular technology is to learn individual eating behaviors and then attempt to provide personalized feedback to modify those behaviors,” said Edward Sazarov, a professor of electrical and computer engineering at the University of Alabama who created the device and is a co-principal investigator with Thomas, in a press release.

“The way you eat is as important as what you eat. We are also looking at the rates of ingestion,” he added. “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.”

The digital health platform captures data from the device and stores it in the user’s smartphone, where it can be retrieved and viewed by both the user and care providers. The platform can also be programmed to deliver messages to the user about eating behaviors.

“Current programs aimed at improving diet and eating behavior largely require the patient to maintain total vigilance of their eating, often requiring them to accurately track how much they are eating,” says Thomas, who is recruiting roughly half of the patients for the study. “This technology has the potential to relieve much of that burden and provide the patient with more accurate information than they could collect themselves. Having accurate information on one’s behavior is critical for making healthy changes to those behaviors.”

A key challenge in mHealth studies that use wearables centers on whether the technology is unobtrusive and fits into the user’s everyday lifestyle. Thomas said this study will focus on the effects of technology on behaviors, while a long-term goal would be to continue making the technology smaller and less noticeable to improve user engagement.