mSTROKE: a crowd-powered mobility towards stroke recognition

Abstract

We demonstrate a crowd-powered model for the early diagnosis of stroke using a mobile device. The simple approach consists of monitoring the subject's health in three simple steps including the smile test for facial weakness, raising hands test for arm weakness and speech test for slurring of speech. Our demonstrated system shows a performance accuracy of 87.5% over a total number of 40 test cases.