The goal of the project is to reduce the risk of Traumatic Brain Injury (TBI) through smart technology that collects sensory data to predict and characterize impacts in real-time, optimizes protective mechanisms based on impact characteristics (e.g., direction, velocity), and transmits final impact attributes to a database for further analysis and injury risk prediction. This technology will substantially improve TBI prevention and diagnosis in motor vehicle crashes, sports, and industrial accidents. The unique technology will leverage musculoskeletal and biomechanical computational models linking head linear and angular acceleration to brain deformation and injury. To accomplish this goal, fundamental research efforts include (1) real-time situational monitoring to predict when and how dangerous impacts are about to occur and (2) active prevention mechanisms in the form of anticipatory muscle activation and event-specific force damping bladders to reduce the risk of TBI due to impact. Initial evaluation of the technology will occur in a sports setting, but the integrated system will be widely applicable to multiple etiologies of TBI.
The core research team includes: Mark Minor (Principal Investigator) and co-investigators David Carrier, Brittany Coats, Andrew Merryweather and Neal Patwari.