Sensors | |
A Novel Phonology- and Radical-Coded Chinese Sign Language Recognition Framework Using Accelerometer and Surface Electromyography Sensors | |
Juan Cheng2  Xun Chen2  Aiping Liu1  Hu Peng2  | |
[1] Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T-1Z4, Canada; E-Mail:;Department of Biomedical Engineering, Hefei University of Technology, 193 Tunxi Road, Hefei 230009, China; E-Mails: | |
关键词: sign language recognition; component level classification; accelerometer; electromyography; hidden markov model (HMM); dynamic time warping; | |
DOI : 10.3390/s150923303 | |
来源: mdpi | |
【 摘 要 】
Sign language recognition (SLR) is an important communication tool between the deaf and the external world. It is highly necessary to develop a worldwide continuous and large-vocabulary-scale SLR system for practical usage. In this paper, we propose a novel phonology- and radical-coded Chinese SLR framework to demonstrate the feasibility of continuous SLR using accelerometer (ACC) and surface electromyography (sEMG) sensors. The continuous Chinese characters, consisting of coded sign gestures, are first segmented into active segments using EMG signals by means of moving average algorithm. Then, features of each component are extracted from both ACC and sEMG signals of active segments (
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
RO202003190006297ZK.pdf | 5474KB | download |