I-Corps: Remote wearable technology for mental health and treatment monitoring

The broader impact/commercial potential of this I-Corps project is the development of wearable technology to monitor symptoms and treatment responses in individuals with mental health conditions such as depression or stress disorders. Currently, subjective symptom monitoring through periodic questionnaires is the standard of practice in diagnosing and monitoring mental health conditions.

However, these tools are prone to biases and inaccuracies, leading to misdiagnosis and ineffective treatment. The proposed technology is a wearable sensor that offers an alternative by monitoring physical, biological, and digital markers. By collecting and analyzing multiple biometric data points, the proposed technology provides a comprehensive assessment, monitoring, and analysis of treatment responses, which may improve mental health monitoring and treatment.

This I-Corps project is based on the development of a sensor for gathering diverse biometric data using physiological and biological biomarkers to monitor mental health. The proposed technology is designed as a wearable technology that uses spectroscopy and machine learning to collect physiological characteristics such as heart rate, breathing rate, and body temperature.

The technology detects and quantifies specific biomarkers without the need for additional labeling agents or probes using optical sensing. The optical detection system measures changes in light properties, including absorption, scattering, or fluorescence, in the presence of target biomarkers. By collecting and analyzing multiple biometric data points, the technology enables comprehensive assessment, monitoring, and analysis of treatment responses.

The goal is to predict depression and stress levels and to advance personalized, data-driven approaches to treatment.

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.