Fugl-Meyer Assessment is one of the most commonly used methods in stroke impairment evaluation. However, Fugl-Meyer assessment needs guidance and grading from professional rehabilitation medical doctors. Therefore, there are challenges in stay-home Fugl-Meyer assessment. In this paper, we present a system that can make Fugl-Meyer assessment from videos taken by common cameras. The proposed system consists of two modules: A motion data capture module for fetching motion data in Euler Angles from videos and a Fugl-Meyer assessment module for grading through motion data from the former module. Experimental tests are conducted on the Human 3. 6 M dataset and demonstrate that our video-based Fugl-Meyer assessment system performs well in accuracy and covers most of the test items in Fugl-Meyer assessment table.