Interpreting Sign Components from Accelerometer and sEMG Data for Automatic Sign Language Recognition

被引：0

作者：

Li, Yun ^{[1
]}

Chen, Xiang ^{[1
]}

Zhang, Xu ^{[2
]}

Wang, Kongqiao ^{[3
]}

Yang, Jihai ^{[1
]}

机构：

[1] USTC, Dept Elect Sci & Technol, Hefei 230027, Peoples R China

[2] Rehabil Inst Chicago, SMPP, Chicago, IL 60611 USA

[3] Nokia China Investment Co Ltd, Nokia Res Ctr, Beijing, Peoples R China

来源：

2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2011年

关键词：

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

The identification of constituent components of each sign gesture is a practical way of establishing large-vocabulary sign language recognition (SLR) system. Aiming at developing such a system using portable accelerometer (ACC) and surface electromyographic (sEMG) sensors, this work proposes a method for automatic SLR at the component level. The preliminary experimental results demonstrate the effectiveness of the proposed method and the feasibility of interpreting sign components from ACC and sEMG data. Our study improves the performance of SLR based on ACC and sEMG sensors and will promote the realization of a large-vocabulary portable SLR system.

引用

页码：3358 / 3361

页数：4

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