I-Corps: An Artificial Intelligence-Powered Mobile-Health Framework Providing Holistic Mental Health Support

The broader impact/commercial potential of this I-Corps project is the development of an artificial intelligence-powered web and mobile application for mental health support. Currently, the ability to deliver personalized, data-driven mental health care is a universal concern. The proposed technology is designed to provide real-time stress analysis, customized geotagged resources, streamlined data management, optimized mental health referrals matching, and mental health tracking over time. This is accomplished by offering services and securely linking users, employers, and community-based organizations (CBOs) based on users’ needs. The application may provide organizations with a cloud-integrated dashboard tracking health resources for their users (e.g., employees, students), while providing insights into the use of resources, such as community-based organizations. The applications include K-12 and higher education, corporate workplaces, military, hospitals, and public health departments. These customer segments could leverage the proposed technology to improve mental health outcomes. This I-Corps project is based on the development of a mobile and web application that leverages artificial intelligence (AI) technology to address the need for behavioral health solutions. Existing systems often fail to deliver timely, personalized support to individuals dealing with mental health issues, leading to ineffective interventions and worsening conditions. The proposed technology is designed to deliver real-time insights of a user’s mental health and stress levels, and offer an in-depth understanding of a user’s well-being. This may empower organizations, such as schools, healthcare organizations and corporations to tailor resources to support their users’ mental health needs. This research has identified a critical gap in the mental health support landscape, particularly with the lack of effective holistic and personalized treatment options. In addition, the proposed application is designed to deliver personalized mental health resources, analytics, and support to users. The technology integrates several intelligent frameworks that utilize natural language processing and machine learning techniques. The artificial intelligence resource matching framework may provide customized resources to users based on their input. The real-time stress analytics dashboard may offer insights into stress levels in real-time. The mental health disorder detection framework may enable potential early detection of these disorders. The proposed technology may be used to address the rising awareness of mental health. 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.