AI system could help reduce childhood obesity risk
Faster eating and larger bite sizes are linked to obesity, and AI could help children develop healthier eating habits.
Researchers at Penn State have developed an AI model that measures children’s bite rate during meals, aiming to address a key risk factor for obesity. Eating quickly hinders fullness signals and, combined with larger bites, increases the risk of obesity.
The AI system, named ByteTrack, was trained using over 1,400 minutes of video from a study of 94 children aged seven to nine. It recognises children’s faces with 97% accuracy and detects bites about 70% as successfully as humans.
Although the system requires further refinement, the pilot study shows promise for large-scale research and potential real-world applications. With further training, ByteTrack could become a smartphone app alerting children when they eat too quickly to encourage healthier habits.
The research was funded by the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of General Medical Sciences, and Penn State’s computational and clinical research institutes.
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