The Study of Hand Gesture Recognition Based on the Fusion of Surface Electromyography and Tissue Impedance
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    Abstract:

    Using surface electromyography (sEMG) signals to gesture recognition is a common method. In order to improve the stability and accuracy of gesture recognition, it usually requires to collect more channels of myoelectric signals. However, this would need a high number of electrodes, resulting the increasing of the complexity of myoelectric recognition system. Therefore, using a small number of sEMG electrodes to ensure the performance of gesture recognition has always been an promising direction in the sEMG-based applications. In this study, we designed a portable four-channel sEMG and impedance signal acquisition device that can simultaneously collect sEMG and tissue impedance signal between differential electrode pairs without adding additional sensors and channels. The self-made device was used to collect the hybrid signals of sEMG and tissue impedance for seven classes of hand gesture recognition. The experimental results show that the four-channel fusion information collected by the system could improve the accuracy and stability of gesture recognition. Compared with using EMG only, the fusion method could improve gesture recognition performance by more than 3% and achieve a recognition rate of 96.2%.

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WANG Yuan, YUAN Simin, HUANG Pingao, et al. The Study of Hand Gesture Recognition Based on the Fusion of Surface Electromyography and Tissue Impedance[J]. Journal of Integration Technology,2020,9(3):26-35

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History
  • Received:February 24,2020
  • Revised:March 24,2020
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  • Online: May 18,2020
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