I-Corps: Translation potential of a mental health smart neurodiagnostic and neurointervention platform

Award ID: 2501451

This I-Corps project is based on the development of a mental health smart neurodiagnostic and neurointervention tool. Current diagnostic tools used to assess serious psychiatric disorders face challenges including the clinician's experience, the patient's willingness to disclose symptoms, the time and labor required, behavioral heterogeneity, and expense. This technology is a digital diagnostic and intervention platform that targets neurovascular dysfunction and its related neuromuscular dysfunction, sleep disturbances, impaired autonomous nervous system, and inflammation, which are the main factors in the development and progression of serious psychiatric disorders. The goal is to provide a digital set of quantitative physiological, neural, movement, psychological, and environmental measures of serious mental illness as well as to enhance access for early identification, treatment, and early preventive intervention of serious psychiatric disorders. This technology may reduce the delay in diagnosis of mental illness and improve patient outcomes by treating core psychiatric symptoms, improving neurovascular function and its related conditions. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a mental health smart neurodiagnostic and neurointervention platform. The platform targets the main neurophysiologic factors in the development and progression of serious mental illness including neurovascular dysfunction and its related neuromuscular dysfunction, sleep disturbances, impaired autonomous nervous system, and inflammation. The solution is based on a model for body-mind biology in development and progression of serious psychiatric disorders. It uses multi-faceted hardware, firmware, and software developed for active and passive data including audio-video of the face; video electroencephalogram (EEG); neurovascular functions; clinical phenotypes of psychiatric disorder; and a custom developed, web-based cloud for body-mind machine learning. In addition, the technology includes a digital reminder intervention and multi-faceted hardware, firmware, and software for augmented reality and neurostimulation intervention for serious mental illness. The digital machine learning algorithms for the identification of serious mental illness, their related psychosomatic disorders, and self-regulation flexibility with neurointerventions may reduce core psychiatric symptoms and treat underlying neurovascular dysfunction and associated psychosomatic disorders at the earliest stages. 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: Ruth Shuman