Brunnstrom Stage Automatic Evaluation for Stroke Patients by Using Multi-Channel sEMG
文献类型：会议论文
| 作者 | Wang FY(王丰焱)1,2,3 ; Zhang DH(张道辉)2,3; 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)2,3
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| 出版日期 | 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
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| 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 |
| 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.University of the Chinese Academy of Sciences, Beijing 100049, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, 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. |
入库方式： OAI收割
来源：沈阳自动化研究所
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