Stroke is a leading cause of disability worldwide. Early recognition and treatment of stroke decreases the mortality and possibility of severe injury. A significant barrier to accurate diagnosis in neurological disease is that visualized deficits such as eye movement, facial weakness or limb incoordination can be difficult to quantify. Together with collaborators from Neurology at UVa, we are collecting quantitative data from a large patient cohort, as well as controls, and are developing biometric intelligent systems to more objectively quantify signs of stroke and ultimately deliver a low cost, early stroke risk assessment pervasive technology.