基于视频的自动Fugl-Meyer评估方法研究

Automatic Fugl-Meyer assessment based on videos

Fugl-Meyer量表是目前临床使用最多的脑卒中感知运动损伤评定方法之一,但由于Fugl-Meyer量表的动作指导和评分都需要专业的康复师参与,Fugl-Meyer评估难以在居家条件下进行。为此,提出了一种基于视频的Fugl-Meyer评估系统。该系统由运动数据获取模块和Fugl-Meyer评估模块两个模块组成。运动数据获取模块可以从视频中获取欧拉角格式的运动数据;Fugl-Meyer评估模块会根据运动数据获取模块输出的数据与Fugl-Meyer量表评分形成的映射关系给出评估结果。该系统允许用户使用最常见的相机进行居家Fugl-Meyer评估。在Human 3.6M数据集上进行了实验,实验结果表明本文系统评估准确且能覆盖Fugl-Meyer量表中的绝大多数测试项目。

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.