电子测量与仪器学报

沈子祺,谢文军,刘晓平.基于视频的自动 Fugl-Meyer 评估方法研究[J].电子测量与仪器学报,2022,36(2):1-11

基于视频的自动 Fugl-Meyer 评估方法研究

Automatic Fugl-Meyer assessment based on videos

DOI：

英文关键词:deep learning human pose estimation Fugl-Meyer assessment

基金项目:国家重点研发计划课题（2020YFC1523100）、国家自然科学基金面上项目（61877016）资助

作者	单位
沈子祺	1. 合肥工业大学计算机与信息学院
谢文军	2. 合肥工业大学软件学院
刘晓平	1. 合肥工业大学计算机与信息学院

Author	Institution
Shen Ziqi	1. School of Computer Science and Information Technology, Hefei University of Technology
Xie Wenjun	2. School of Software, Hefei University of Technology
Liu Xiaoping	1. School of Computer Science and Information Technology, Hefei University of Technology

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中文摘要:

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。

英文摘要:

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.

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