Xidong Yang's research while affiliated with University of Electronic Science and Technology of China and other places
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Publications (2)
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 (o...
Sign language recognition (SLR) can provide a helpful tool for the communication between the deaf and the external world. This paper proposed a component-based vocabulary extensible SLR framework using data from surface electromyographic (sEMG) sensors, accelerometers (ACC), and gyroscopes (GYRO). In this framework, a sign word was considered to be...
Citations
... Based on the structural characteristics of CSL, many scholars decompose it into pure structural elements for analysis and research, such as hand shape, orientation, posture, and position. Yang et al. [8] used the hand shape, orientation, position and other elements of gesture action to classify the vocabulary step by step. Although this method has high recognition rate and accuracy, it has the disadvantages of a small number of recognized words and lack of systematization. ...
... In early research, traditional machine learning algorithms based on manual feature extraction such as support vector machine (SVM) (Cortes and Vapnik, 1995), k-nearest neighbor (KNN) (Cover and Hart, 1967), and linear discriminant analysis (LDA) (Fisher, 1936) have been successfully applied in myoelectric pattern recognition (Du et al., 2010;Phinyomark et al., 2013;Wei et al., 2016). These algorithms were often conducted on LD-sEMG signals in a user-specific mode. ...
