基于肌电信号容错分类的手部动作识别 | |
丁其川; 赵新刚; 韩建达 | |
刊名 | 机器人 |
2015 | |
卷号 | 37期号:1页码:9-16 |
关键词 | 肌电信号 数据丢失 动作分类 人机交互 |
ISSN号 | 1002-0446 |
其他题名 | Recognizing hand motions based on fault-tolerant classification with EMG signals |
产权排序 | 1 |
中文摘要 | 针对肌电交互系统中因电极断开、损坏及数据传输中断等故障造成的数据错误/丢失问题,提出一种基于高斯混合模型的肌电信号容错分类方法,通过对肌电信号特征样本中错误/丢失数据边缘化或条件均值归错实现非完整数据样本分类。应用所提出的方法识别5种手部动作,实验结果表明,该方法的动作识别精度要高于传统的零归错与均值归错方法。最后,融合容错分类机制开发了肌电假手平台,在线实验验证了提出的方法可以有效提高肌电交互系统的鲁棒性。 |
英文摘要 | In view of the fault/missing data problem caused by disconnected/damaged electrodes and data-transmission interrupting in myoelectric-interface systems, an EMG (electromyography) fault-tolerant classification method based on Gaussian mixture model is proposed, with which an incomplete-data sample can be classified via marginalizing or conditionalmean imputation of the fault/missing data in the EMG feature sample. The proposed method is applied to recognizing five kinds of hand motion. Experimental results show that the proposed method can provide higher motion-recognition accuracy than that by the traditional zero and mean imputation methods. Finally, a myoelectric-hand platform is developed by involving the fault-tolerant classification mechanism, and the online experiments show that the proposed method can effectively improve the robustness of myoelectric-interface systems. |
收录类别 | EI ; CSCD |
语种 | 中文 |
CSCD记录号 | CSCD:5364506 |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.ac.cn/handle/173321/16212] |
专题 | 沈阳自动化研究所_机器人学研究室 |
推荐引用方式 GB/T 7714 | 丁其川,赵新刚,韩建达. 基于肌电信号容错分类的手部动作识别[J]. 机器人,2015,37(1):9-16. |
APA | 丁其川,赵新刚,&韩建达.(2015).基于肌电信号容错分类的手部动作识别.机器人,37(1),9-16. |
MLA | 丁其川,et al."基于肌电信号容错分类的手部动作识别".机器人 37.1(2015):9-16. |
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