Brunnstrom Stage Automatic Evaluation for Stroke Patients by Using Multi-Channel sEMG

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	Brunnstrom Stage Automatic Evaluation for Stroke Patients by Using Multi-Channel sEMG
	Wang FY(王丰焱)1,2,3; Zhang DH(张道辉)1,2; Hu SK(胡少康)1,2,3; Zhu B(朱波)1,2,3; Han F(韩非)1,2,3; Zhao XG(赵新刚)1,2
	2020
会议日期	July 20-24, 2020
会议地点	Montreal, QC, Canada
页码	3763-3766
英文摘要	Rehabilitation level evaluation is an important part of the automatic rehabilitation training system. As a general rule, this process is manually performed by rehabilitation doctors using chart-based ordinal scales which can be both subjective and inefficient. In this paper, a novel approach based on ensemble learning is proposed which automatically evaluates stroke patients' rehabilitation level using multi-channel sEMG signals to this problem. The correlation between rehabilitation levels and rehabilitation training actions is investigated and actions suitable for rehabilitation assessment are selected. Then, features are extracted from the selected actions. Finally, the features are used to train the stacking classification model. Experiments using sEMG data collected from 24 stroke patients have been carried out to examine the validity and feasibility of the proposed method. The experiment results show that the algorithm proposed in this paper can improve the classification accuracy of 6 Brunnstrom stages to 94.36%, which can promote the application of home-based rehabilitation training in practice.
产权排序	1
会议录	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-7281-1990-8
WOS记录号	WOS:000621592204029
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/27673]
专题	沈阳自动化研究所_机器人学研究室
通讯作者	Zhao XG(赵新刚)
作者单位	1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 3.University of the Chinese Academy of Sciences, Beijing 100049, China
推荐引用方式 GB/T 7714	Wang FY,Zhang DH,Hu SK,et al. Brunnstrom Stage Automatic Evaluation for Stroke Patients by Using Multi-Channel sEMG[C]. 见:. Montreal, QC, Canada. July 20-24, 2020.