The federal government is developing a body mass index (BMI) detector intended to be available to every American "anywhere and anytime," according to a grant awarded by the National Science Foundation (NSF). The detector is expected to rely on the analysis of facial and body imagery.
The project has been awarded $200,113 thus far to create the system under the notion that too many obese individuals are unaware of their BMI.
"Body mass index (BMI) is a measure of the ratio between an individual's weight and height, which is an important parameter to characterize human bodies into four categories, i.e., underweight, normal, overweight, and obese," the grant states. "A high BMI value is associated with a higher risk for conditions such as type 2 diabetes, high blood pressure, cardiovascular disease, and certain cancers."
"The study of this project leads to development of an intelligent and computational system that can be used by everybody at anywhere and anytime," the grant adds. "The developed system enables people to [be] aware their BMI and understand the strongly correlated high risks of various diseases to combat overweight and obesity."
"The developed technology can also improve personal health care and quality of life, and public health surveillance," it added.
Guodong Guo, an assistant professor at the Department of Computer Science and Electrical Engineering at West Virginia University, is leading the project. Guo previously created a system that predicted BMIs from mug shots.
Guo said that his facial recognition BMI predictor could be used for online dating, so an individual can know the "state of health of people you might date."
The accuracy of BMI has been the subject of long debate, with some researchers arguing that BMI has little value because it cannot distinguish between fat and muscle. BMI screenings in schools have also been criticized as invasive. Mandatory screenings in Arkansas, California, Massachusetts, and Illinois have resulted in children being sent home with "fat letters."
The NSF project will develop a "low-cost, portable, reliable, and convenient BMI assessment system" off of Guo’s prior research that could use both two and three- dimensional images.
"The key research question is what kinds of features or patterns can be extracted from human face and body images to characterize the visual appearance related to BMI measure," the grant said. "In facial images, the study focuses on 2D facial feature representation and its robustness in order to build the mapping relation from face to BMI. In body images, the focuses are on 3D body shape analysis to connect to BMI measure."
"This research provides a theoretic foundation for developing a visual analysis system that can be deployed to provide convenient estimate of the BMI and related health conditions anywhere and anytime," the grant added.
The project, which only recently began on Sept. 1, received a grant for $200,113. Funding is estimated to continue until 2016.