PMID- 27164613
OWN - NLM
STAT- MEDLINE
DCOM- 20180108
LR  - 20180222
IS  - 2168-2208 (Electronic)
IS  - 2168-2194 (Linking)
VI  - 21
IP  - 4
DP  - 2017 Jul
TI  - Chinese Sign Language Recognition Based on an Optimized Tree-Structure Framework.
PG  - 994-1004
LID - 10.1109/JBHI.2016.2560907 [doi]
AB  - Chinese Sign Language (CSL) subword recognition based on surface electromyography 
      (sEMG), accelerometer (ACC), and gyroscope (GYRO) sensors was explored in this 
      paper. In order to fuse effectively the information of these three kinds of 
      sensors, the classification abilities of sEMG, ACC, GYRO, and their combinations 
      in three common sign components (one or two handed, hand orientation, and hand 
      amplitude) were evaluated first and then an optimized tree-structure 
      classification framework was proposed for CSL subword recognition. Eight subjects 
      participated in this study and recognition experiments under different testing 
      conditions were implemented on a target set consisting of 150 CSL subwords. The 
      proposed optimized tree-structure classification framework based on sEMG, ACC, 
      and GYRO obtained the best performance among seven different testing conditions 
      with single sensor, paired-sensor fusion, and three-sensor fusion, and the 
      overall recognition accuracies of 94.31% and 87.02% were obtained for 150 CSL 
      subwords in a user-specific test and user-independent test, respectively. Our 
      study could lay a basis for the implementation of large-vocabulary sign language 
      recognition system based on sEMG, ACC, and GYRO sensors.
FAU - Yang, Xidong
AU  - Yang X
FAU - Chen, Xiang
AU  - Chen X
FAU - Cao, Xiang
AU  - Cao X
FAU - Wei, Shengjing
AU  - Wei S
FAU - Zhang, Xu
AU  - Zhang X
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20160503
PL  - United States
TA  - IEEE J Biomed Health Inform
JT  - IEEE journal of biomedical and health informatics
JID - 101604520
SB  - IM
MH  - Accelerometry/methods
MH  - Adult
MH  - Algorithms
MH  - China
MH  - Electromyography/*methods
MH  - Equipment Design
MH  - Gestures
MH  - Humans
MH  - Male
MH  - Movement/physiology
MH  - Pattern Recognition, Automated/*methods
MH  - *Sign Language
MH  - *Signal Processing, Computer-Assisted
MH  - Young Adult
EDAT- 2016/05/11 06:00
MHDA- 2018/01/09 06:00
CRDT- 2016/05/11 06:00
PHST- 2016/05/11 06:00 [pubmed]
PHST- 2018/01/09 06:00 [medline]
PHST- 2016/05/11 06:00 [entrez]
AID - 10.1109/JBHI.2016.2560907 [doi]
PST - ppublish
SO  - IEEE J Biomed Health Inform. 2017 Jul;21(4):994-1004. doi: 
      10.1109/JBHI.2016.2560907. Epub 2016 May 3.