TY - GEN
T1 - Recognition of motion of human upper limb using sEMG in real time
T2 - 2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012
AU - Song, Zhibin
AU - Guo, Shuxiang
AU - Pang, Muye
AU - Zhang, Songyuan
PY - 2012
Y1 - 2012
N2 - The surface electromyographic (sEMG) signal has been researched in many fields, such as medical diagnoses and prostheses control. In this paper, recognition of motion of human upper limb by processing sEMG signal in real time was proposed for application in bilateral rehabilitation, in which hemiplegia patients trained their impaired limbs by rehabilitation device based on motion of the intact limbs. In the processing of feature exaction of sEMG, Wavelet packet transform (WPT) and autoregressive (AR) model were used. The effect of feature exaction with both methods was discussed through the processing of classification where Back-propagation Neural Networks were trained. The experimental results show both methods can obtain reliable accuracy of motion pattern recognition. Moreover, on the experimental condition, the recognized accuracy of WPT is higher than that of AR model.
AB - The surface electromyographic (sEMG) signal has been researched in many fields, such as medical diagnoses and prostheses control. In this paper, recognition of motion of human upper limb by processing sEMG signal in real time was proposed for application in bilateral rehabilitation, in which hemiplegia patients trained their impaired limbs by rehabilitation device based on motion of the intact limbs. In the processing of feature exaction of sEMG, Wavelet packet transform (WPT) and autoregressive (AR) model were used. The effect of feature exaction with both methods was discussed through the processing of classification where Back-propagation Neural Networks were trained. The experimental results show both methods can obtain reliable accuracy of motion pattern recognition. Moreover, on the experimental condition, the recognized accuracy of WPT is higher than that of AR model.
UR - https://www.scopus.com/pages/publications/84876493645
U2 - 10.1109/ROBIO.2012.6491165
DO - 10.1109/ROBIO.2012.6491165
M3 - 会议稿件
AN - SCOPUS:84876493645
SN - 9781467321273
T3 - 2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest
SP - 1403
EP - 1408
BT - 2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest
PB - IEEE Computer Society
Y2 - 11 December 2012 through 14 December 2012
ER -