Study on online gesture sEMG recognition

被引：0
|
作者：
Zhao, Zhangyan [1 ]
Chen, Xiang [1 ]
Zhang, Xu [1 ]
Yang, Jihai [1 ]
Tu, Youqiang [1 ]
Lantz, Vuokko [2 ]
Wang, Kongqiao [3 ]
机构：
[1] Univ Sci & Technol, Dept Elect Sci & Technol, Hefei 230027, Peoples R China
[2] Nokia Res Ctr, Interact CTC, Interacting Smart Environm, FI-00045 Helsinki, Finland
[3] NOKIA Investment CO LTD, Nokia Res Ctr, Beijing 100013, Peoples R China
来源：
ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF THEORETICAL AND METHODOLOGICAL ISSUES | 2007年 / 4681卷
关键词：
surface EMG; online gesture recognition;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We have realized an online gesture recognition platform for hand gestures using 2-channel surface EMG signals acquired from the forearm. Several features, such as AMV, AMV ratio and fourth-order AR model coefficients are extracted from the sEMG signal and the gesture segments are recognized with a Weighted Euclidean Distance Classifier. An above 90% recognition rate has been achieved with only a 400 mu s recognition time. The methods developed in this study are aimed to be applied in a fast-response sEMG control system and be transplanted into an embedded microprocessor system.
引用
收藏
页码：1257 / +
页数：2
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