SBIR Phase I: Biometric Wearable Device for Real-Time Mental Health Intervention of Anxiety

Award ID: 2112055

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to utilize artificial intelligence for mental health interventions, with an initial application of college students. Over 60% of U.S. college students suffer stress and anxiety that can manifest in physical symptoms such as palpitations, chest pressure, stomach aches, muscular tension, diarrhea/constipation, and fatigue. The significant negative impact of stress and anxiety affects learning, development, and social engagement, and ultimately can contribute to destructive behaviors such as drug and alcohol use. This project proposes an intelligent, personalized digital health technology that integrates biometrics for automated, early detection of increasingly stressed states as a cost-effective way to inform interventions and improve college retention. This application can be expanded to other populations for improved mental health outcomes. This Small Business Innovation Research (SBIR) Phase I project improves mental health through integration of wearable biometric sensors, artificial intelligence (AI), and a user interface to guide both automated and interactive psychotherapy interventions. A wearable wrist band device will passively capture biosignals to detect signals of anxiety to inform an automated analysis. The app can then provide varying levels of alerts and intervention as appropriate for the magnitude of the event. This can be used for mental health monitoring broadly. 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