Key Takeaways<\/p>\n
A new AI bite counter might help fight childhood obesity<\/p>\n
The counter is being trained to count each bite a child takes during a meal or snack<\/p>\n
Eating faster increases a child\u2019s risk of obesity<\/p>\n
MONDAY, Oct. 20, 2025 (HealthDay News) \u2014 A new AI-driven bite counter is in development to help counter childhood obesity \u2013 potentially even tracking kids while they eat and urging them to slow down.<\/p>\n
The faster a child takes bites during a meal or snack, the greater their risk for developing obesity, researchers say.<\/p>\n
But studying different ways to help kids slow down at mealtime is time-consuming, because researchers must review videos and make note of each bite taken.<\/p>\n
To make larger studies possible, researchers developed an artificial intelligence (AI) called ByteTrack that is learning how to count children\u2019s bites during meals.<\/p>\n
The system is about 70% as accurate as human counters, according to a report published recently in the journal Frontiers in Nutrition<\/a>.<\/p>\n As it becomes more accurate, the AI could one day help researchers, parents and doctors identify when children need to slow down their eating.<\/p>\n \u201cWhen we eat quickly, we don\u2019t give our digestive track time to sense the calories,\u201d researcher Kathleen Keller<\/a>, chair of nutritional sciences at Pennsylvania State University, said in a news release.<\/p>\n \u201cThe faster you eat, the faster it goes through your stomach, and the body cannot release hormones in time to let you know you are full,\u201d she said. \u201cLater, you may feel like you have overeaten, but when this behavior repeats, faster eaters are at greater risk for developing obesity.\u201d<\/p>\n Bite rate has become a go-to measure of children\u2019s eating behaviors, said senior researcher Alaina Pearce<\/a>, a research data management librarian at Penn State.<\/p>\n \u201cBite rate is often the target behavior for interventions aimed at slowing eating rate,\u201d Pearce said in a news release. \u201cThis is because bite rate is a stable characteristic of children\u2019s eating style that can be targeted to reduce their eating rate, intake and ultimately risk for obesity.”<\/p>\n Researchers trained the AI on 1,440 minutes of videos from a government-funded study of overeating in children. The footage included 94 7- to 9-year-olds consuming four meals each on separate occasions.<\/p>\n The team counted bites for 242 videos, and used that information to train the AI model. They then tested the AI on 51 other videos.<\/p>\n The system was 97% successful as a human at identifying a child\u2019s face, but only 70% as successful in identifying every bite.<\/p>\n \u201cThe system was less accurate when a child\u2019s face was not in full view of the camera or when a child chewed on their spoon or played with their food, as often happens toward the end of a meal,\u201d lead researcher Yashaswini Bhat<\/a>, a doctoral student in nutritional sciences at Penn State, said in a news release.<\/p>\n \u201cAs one might imagine, this type of behavior is much more common among children than it is with adults,\u201d Bhat said. \u201cChewing on a utensil sometimes appeared to be a bite, and this complicated the task for the AI model.\u201d<\/p>\n The goal is to develop the AI to the point where it can accurately identify bites in real time, Bhat said.<\/p>\n \u201cOne day, we might be able to offer a smartphone app that warns children when they need to slow their eating so they can develop healthy habits that last a lifetime,\u201d Bhat said.<\/p>\n More information<\/p>\n