A State Equation Model for Joint Moment Estimation Based on SEMG

被引：0
|
作者：
Qin, Hao [1 ]
Wang, Fei [1 ]
Fan, Zhibo [1 ]
Wei, Xiaotong [1 ]
Guo, Jiyuan [1 ]
Zheng, Yongbo [1 ]
机构：
[1] Northeastern Univ, Fac Robot Sci & Engn, Shenyang, Peoples R China
来源：
2019 9TH IEEE ANNUAL INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (IEEE-CYBER 2019) | 2019年
关键词：
human-machine interaction; sEMG; moment estimation model; CGA gait database; TORQUE;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
in recent years, with the vigorous development of exoskeleton robots, the research in the field of human machine interaction has gradually deepened. As an important reference information in this field, human physiological signals have attracted more and more attention of researchers. Among them, surface electromyography (sEMG) signals have become one of the hot research subjects because of its generation ahead of limb movements. In this study, a joint moment estimation model based on electromyography (EMG) was established, and then an experiment was designed to estimate the knee joint moment information during lower limb movement. The accuracy of the estimation model was verified by comparing with the results of CGA gait database.
引用
收藏
页码：226 / 230
页数：5
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