DocumentCode :
2484120
Title :
Interpreting sign components from accelerometer and sEMG data for automatic sign language recognition
Author :
Li, Yun ; Chen, Xiang ; Zhang, Xu ; Wang, Kongqiao ; Yang, Jihai
Author_Institution :
Dept. of Electron. Sci. & Technol., Univ. of Sci. & Technol. of China (USTC), Hefei, China
fYear :
2011
fDate :
Aug. 30 2011-Sept. 3 2011
Firstpage :
3358
Lastpage :
3361
Abstract :
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.
Keywords :
accelerometers; biocommunications; electromyography; gesture recognition; accelerometer data; automatic sign language recognition; constituent component identification; portable accelerometer; sEMG data; sign components; sign gesture; sign language recognition system; surface electromyographic sensors; Accelerometers; Electromyography; Handicapped aids; Sensors; Shape; Support vector machine classification; Training; Electromyography; Humans; Markov Chains; Sign Language;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2011.6090910
Filename :
6090910
Link To Document :
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