As of 2016, 93.3 million U.S. adults were obese, according to the CDC. That number equals 39.8% of Americans who are more prone than non-obese adults to heart disease, stroke, Type 2 diabetes, and some forms of cancer. Those conditions and diseases, taken as a group, are leading causes of premature death. There is no magic pill for obesity. Some patients choose gastric bypass surgery, but even that drastic procedure does not guarantee success.
One approach that works is to reduce the number of calories consumed, but patients often have trouble adhering to instructions to log their intake and calculate the totals. As a results, researchers have sought ways to automate the tracking of eating, such as a device that listens to what you eat.
Researchers from Rhode Island-based Miriam Hospital’s Miriam Weight Control and Diabetes Research group announced a $2.5 million grant from the National Institute of Health that will fund a clinical trial of the Automatic Ingestion Monitor (AIM), a wearable that monitors patient eating. The trial will test the AIM’s effectiveness with overweight and obese adults. Graham Thomas, Ph.D., a Miriam researcher, developed the patent-pending AIM with engineers at the University of Alabama, primarily Dr. Edward Sazonov. Thomas and Sazanov will be the principal investigators in the clinical study. (We first reported on the AIM more than five years ago, when it was a device that was worn on the ear like a hearing aid.)
The current AIM wearable clips to a patient’s glasses. It uses sensors that monitor chewing and a high-definition camera that photographs food. A processor in the device transmits images and data to the patient’s smartphone. An algorithm in a smartphone app triggers messages about eating behavior and suggests modifications as necessary.
During the four-year clinical trial, the researchers plan to use machine learning to create models of individual eating patterns. The devices will subsequently use the models to give patients personalized feedback. The study will focus on the effectiveness of individually-tailored feedback in modifying eating behaviors among obese and overweight patients.
