A soft robotic hand: design, analysis, sEMG control, and experiment

  • Naishi Feng
  • Qiurong Shi
  • Hong WangEmail author
  • Jiale Gong
  • Chong Liu
  • Zhiguo Lu


Soft robot is a new type of flexible robot which can imitate human hand activity. Electromyographic (EMG) signal is an important bioelectrical signal associated with muscle activity. The innovative combination of soft robot and EMG shows great potential. Based on this inspiration, a humanoid soft robotic hand controlled by EMG was proposed. We designed a single finger 3D model for the soft robotic hand and put forward the three-stage cavity structure. The finite element analysis has been performed to obtain the influence of the geometrical parameters including the number of cavities, the shape of the cavity side section, and the pressure in the cavity on the single finger bending performance. The optimal geometrical parameters were obtained. We analyzed the geometrical deformation of the finger simulation model and figured out the relationship between the input pressure of the soft hand and the angle of bending deformation. In addition, we designed and manufactured the soft robotic hand model and its pneumatic system. Twenty-four effective eigenvalues were extracted from the surface EMG signal (sEMG) of the forearm muscle group and ten-kinds-gestures recognizing system was established. Finally, we realized the online sEMG control of the soft robotic hand, so that the soft robotic hand can reproduce the gestures behavior of human. The correct rate of recognition is 96%. Conclusions obtained in this paper provide theoretical support for the development of humanoid soft robotic hand.


Soft robot sEMG Three-segment cavity structure Finite element analysis Human-robot interaction 


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Funding information

This study was supported by the National Natural Science Foundation of China (51505069, 51405073), National Key R & D Program of China (2017YFB1300300), the University Innovation Team of Liaoning Province (LT2014006), and the Fundamental Research Funds for the Central Universities (N150308001).


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Naishi Feng
    • 1
  • Qiurong Shi
    • 1
  • Hong Wang
    • 1
    Email author
  • Jiale Gong
    • 1
  • Chong Liu
    • 1
  • Zhiguo Lu
    • 1
  1. 1.Department of mechanical engineering and automationNortheastern UniversityShenyang CityPeople’s Republic of China

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