SBIR Phase II: EEG-guided intelligent transcranial photobiomodulation to reduce symptoms of autism

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project involves developing a personalized home-based treatment for autistic children. Autism Spectrum Disorder is a common neurodevelopmental disorder requiring lifelong management. The prevalence rate is globally rising, with nearly 3% of U.S. children afflicted. A lack of clinically validated solutions places a heavy emotional and financial burden on families with annual costs of care projected to reach $461 billion by 2025. Autism currently has no approved medications or medical device treatments for core symptoms, and the only current treatment is intensive behavioral therapy. This project aims to develop an effective personalized treatment for improving communication, learning, and social skills, thereby increasing individual independence, create new employment opportunities, and reduce government spending on special education and support services. Additionally, it aims to enrich knowledge through personalization, monitoring, and data aggregation of neurological measures for further elucidating the mechanisms of autism and enhancing the efficacy of other therapies. This Small Business Innovation Research (SBIR) Phase II project aims to develop a non-invasive therapeutic brain stimulation medical device to improve the communication, responsiveness, and social integration of autistic children. The project's objectives are to finalize the current prototype into a manufacturing-ready product, and implement a platform for personalizing transcranial photobiomodulation (tPBM) treatment based on individual sensor derived patient characteristics. The proposed development consists of two main technological components - The first is a wearable device worn on a child’s head that delivers transcranial Photobiomoldulation (tPBM) therapy to reduce autism symptoms based on integrated electroencephalogram (EEG) measures - The second is a software and data platform providing analyzed reports to evaluate intervention efficacy and personalize treatment through machine learning. The anticipated technical results include completion of the final version of the device suitable for clinical adoption and future approval. 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.