I-Corps: Automatic mood tracker that analyzes facial expressions and emotions against social media activity during social media engagement

The broader impact/commercial potential of this I-Corps project is the development of an accurate mood detection technology to address social media impacts on young adult patients' mental health. According to the National Institute of Mental Health, young adults aged 18-25-years had a higher incidence of mental illness (29.4%) compared to adults aged 26-49-years (25%) and those aged 50 and older (14.1%).

The proposed technology will focus on facial recognition and facial expression to track emotions using a software application. Non-contact sensors used to detect mood decline may have significant application to health and wellness. In addition, enabling biometrics such as facial recognition and facial expressions may have significant impact on education, marketing, and surveillance.

The proposed technology may address the problem for both the practitioners and their patients and provide a tool for impacting wellness and treatment.

This I-Corps project is based on the development of an automatic mood tracker that analyzes facial expressions and emotions during social media engagement. The proposed software accesses the end-users webcam (with their permission) and uses emotion artificial intelligence and machine learning algorithms to analyze facial micro-expressions. When a neutral or negative expression is emoted, the software captures screenshots of social media content and saves it onto the user’s dashboard for self-reflection.

In addition, the user’s emotions are analyzed in real time using facial expressions and averaged on the user’s dashboard as an emotional score for their daily mood.

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.