SBIR Phase I: A computer vision system for calorie tracking to encourage adherence to customized weight-loss regimens

Award ID: 2136886

The broader impact/commercial potential of this Small Business Innovation Research Phase I project is to help the 60% of the 21 million African American women in the US who are overweight or obese, increasing their risk for diabetes and cardiovascular disease in greater severity than the general population. This project overcomes barriers to weight management in African American women through its customized data library. The proposed automated food tracker is combined with a social network function to incentivize new users to engage with the application. These features provide a powerful tool for the user to achieve a healthy body mass index and maintain health over a lifetime. The proposed project is a mobile weight-loss management application to help African American manage diet and track physical activity. It helps women build their knowledge of proper nutrition and follow a healthy lifestyle, thereby improving adherence rates for diet and exercise regimens. The application's innovation is to automate the tracking of food intake from the users with image recognition and machine learning algorithms. This innovation creates a unique data set for foods common in the African American community, labeling the carbohydrates, calories, proteins, fats, and serving size. This automatic process provides a framework that eliminates the barriers created by the manual calculations that current solutions require. Furthermore, it will incorporate a game-like interface to increase engagement for better long-term weight management outcomes. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Alastair Monk