"Human behavior is inherently multi-modal, and individuals use eye gaze, hand gestures, facial expressions, body posture, and tone of voice along with speech to convey engagement and regulate social interactions"
We will develop novel computational methods for measuring and analyzing the behavior of children and adults during face-to-face social interactions. Social behavior plays a key role in the acquisition of social and communicative skills during childhood. Children with developmental disorders, such as autism, face great challenges in acquiring these skills, resulting in substantial lifetime risks.
Direct observation of a child by highly trained specialists is an important step in assessing risk for developmental disorders, but this approach cannot be easily scaled to the large number of individuals needing evaluation and treatment. For example, autism affects 1 in 110 children in the U.S., with a lifetime cost of care of $3.2 million per person. By developing methods to automatically collect fine-grained behavioral data, this project will enable large-scale objective screening and more effective delivery and assessment of therapy.
Going beyond the treatment of disorders, this technology will make it possible to automatically measure behavior over long periods of time for large numbers of individuals in a wide range of settings. Many disciplines, such as education, advertising, and customer relations, could benefit from a quantitative, data-drive approach to behavioral analysis.
Our multidisciplinary research team consists of computer scientists, engineers, and psychologists from nine institutions. Our collaborators include major autism research centers in Atlanta, Boston, Pittsburgh, Urbana-Champaign, and Los Angeles.
Georgia Tech is the lead institution in a $10 million, five year award from the National Science Foundation's Expeditions in Computing Program. The project title is Computational Behavioral Science: Modeling, Analysis, and Visualization of Social and Communicative Behavior.