Clinical Development of a Tool for Optimized Self- and Hetero-diagnosis of Stroke Using Artificial Intelligence: Stage1- Collection of Video-clinical Data in a Pragmatic Situation.

The study authors aim to form a collection of video-clinical data in a pragmatic situation to enable the development of relevant AI algorithms (for both hetero- and self-diagnosis modes). The aim is to optimize management through early diagnosis (self- and hetero-diagnosis) and thus to reduce sequelae disability. The study authors hypothesize that some stroke patients will be able to successfully perform a self-test consisting of a few exercises dictated by an application on a smartphone or tablet and recorded on video.

Inclusion Criteria: * Patients treated in the emergency department or hospitalized in the NICU at the CHU de Nîmes for suspected stroke or transient ischemic attack in the acute phase (\