SBIR Phase II: Defining the Multimodal Signature of Stroke

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project falls within the scope of the grand challenges in health informatics. There are excellent protocols for the management and treatment of acute stroke, however, these protocols are only effective once patients have been admitted into the healthcare system. Ischemic stroke affects 700,000 Americans, costs approximately $33 billion annually, and is the fifth leading cause of death and a leading cause of disability in the US. Health care providers, however, have limited interaction with their patients, and these interactions occur in the highly constrained environment of the clinical setting. Physicians have limited control over patient behavior and limited tools to help patients recognize stroke symptoms outside the clinical setting. For patients with high stroke risk, there is currently no system available to monitor stroke symptoms and initiate a response in real-time. Thus, there is a need to monitor patients remotely, where the current systems for stroke response fail to provide coverage. The proposed solution will expand the provision of stroke symptom monitoring to the daily lives of patients. Tracking patients as they go through their daily lives will considerably enrich our knowledge of stroke and will allow extension to monitoring for other neurological and neuropsychiatric disorders and diseases. This Small Business Innovation Research (SBIR) Phase II project addresses the real-time detection of stroke. IV tissue plasminogen activator (tPA) has been an FDA approved therapy since 1995, yet only 5-10% of eligible patients receive this therapy. Arrival time in the emergency room after initial stroke symptoms is directly associated with better outcomes after tPA and endovascular therapy, with a time window of 4.5 hours and 24 hours for these treatments, respectively. Despite massive public health campaigns, identifying symptoms of stroke and activating emergency response systems remains a major challenge. The goal of this project is to develop and test a wearable and computational solution to effectively alert ischemic stroke victims and initiate emergency response in a timely manner. The solution consists of a cloud-based analysis system for real-time detection of stroke onset, enabled by body-worn sensors and a mobile app. Once deployed, the device is expected to dramatically improve stroke emergency response and increase the number of patients arriving in the hospital in time for IV tPA treatment and other reperfusion therapies. 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.