Prehospital Cerebrovascular Accident Detection using Artificial Intelligence Powered Mobile Devices

Cerebrovascular Accident (CVA) is the second leading cause of death in the world while also being the plurality cause of disability in adults. A definitive factor for survivability and successful recovery of a patient is the time passage from the onset of symptoms to the administration of medical treatment. This paper introduces Stroke Help, a mobile application utilizing various mobile technologies together with Artificial Intelligence algorithms in order to quickly detect CVA in either the user or someone the user is concerned about. The application implements the well known F.A.S.T. test making use of real-time face detection, speech recognition, and other artificial intelligence techniques applied over common sensors found in modern mobile phones. In addition of detecting whether there is a high probability a patient is suffering from a stroke, the application will calculate an approximated Japan Urgent Stroke Triage (JUST) score utilized in identifying the specific type of stroke, very important information for medical staff to potentially reduce the time required to evaluate the patient before beginning the appropriate treatment. We will also present additional crucial functionalities such as notifying contacts, identifying the closest clinics capable of treating CVA, making our solution a complete approach.