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A soft neuroprosthetic hand providing simultaneous myoelectric control and tactile feedback


Neuroprosthetic hands are typically heavy (over 400 g) and expensive (more than US$10,000), and lack the compliance and tactile feedback of human hands. Here, we report the design, fabrication and performance of a soft, low-cost and lightweight (292 g) neuroprosthetic hand that provides simultaneous myoelectric control and tactile feedback. The neuroprosthesis has six active degrees of freedom under pneumatic actuation, can be controlled through the input from four electromyography sensors that measure surface signals from residual forearm muscles, and integrates five elastomeric capacitive sensors on the fingertips to measure touch pressure so as to enable tactile feedback by eliciting electrical stimulation on the skin of the residual limb. In a set of standardized tests performed by two individuals with transradial amputations, we show that the soft neuroprosthetic hand outperforms a conventional rigid neuroprosthetic hand in speed and dexterity. We also show that one individual with a transradial amputation wearing the soft neuroprosthetic hand can regain primitive touch sensation and real-time closed-loop control.

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Fig. 1: Design and operation of the soft neuroprosthetic hand.
Fig. 2: Performance characterization of the soft neuroprosthetic hand.
Fig. 3: An individual with a transradial amputation wearing the soft neuroprosthetic hand, restoring the versatile hand functions in daily activities.
Fig. 4: An individual with a transradial amputation wearing the soft neuroprosthetic hand, restoring the primitive touch sensation and the closed-loop control in blindfolded and acoustically shielded interaction experiments.

Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. Source data for Fig. 3a and Supplementary Figs. 23 and 26 are available as Supplementary Information. All data needed to evaluate the conclusions are presented in the paper and the Supplementary Information.


  1. Cordella, F. et al. Literature review on needs of upper limb prosthesis users. Front. Neurosci. 10, 209 (2016).

    PubMed  PubMed Central  Article  Google Scholar 

  2. Belter, J. T., Segil, J. L., Dollar, A. M. & Weir, R. F. Mechanical design and performance specifications of anthropomorphic prosthetic hands: a review. J. Rehabil. Res. Dev. 50, 599–618 (2013).

    PubMed  Article  Google Scholar 

  3. Lewis, S., Russold, M. F., Diet, H. & Kaniusas, E. Satisfaction of prosthesis users with electrical hand prostheses and their sugggested improvements. Biomed. Tech. (2013).

  4. Biddiss, W. A. & Chau, T. T. Upper limb prosthesis use and abandonment: a survey of the last 25 years. Prosthet. Orthot. Int. 31, 236–257 (2007).

    PubMed  Article  Google Scholar 

  5. Farina, D. & Aszmann, O. Bionic limbs: clinical reality and academic promises. Sci. Transl. Med. 6, 257ps12 (2014).

    PubMed  Article  Google Scholar 

  6. Carey, S. L., Lura, D. J. & Highsmith, M. J. Differences in myoelectric and body-powered upper-limb prostheses: systematic literature review. J. Rehabil. Res. Dev. 52, 247–262 (2015).

    PubMed  Article  Google Scholar 

  7. Xu, K., Guo, W., Hua, L., Sheng, X. & Zhu, X. A prosthetic arm based on EMG pattern recognition. In Proc. IEEE International Conference on Robotics and Biomimetics (ROBIO) 1179–1184 (IEEE, 2016).

  8. Catalano, M. G. et al. Adaptive synergies for the design and control of the Pisa/IIT SoftHand. Int. J. Robot. Res. 33, 768–782 (2014).

    Article  Google Scholar 

  9. Godfrey, S. B. et al. The SoftHand Pro: functional evaluation of a novel, flexible, and robust myoelectric prosthesis. PLoS ONE 13, e0205653 (2018).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  10. Kanzler, C. M. et al. An objective functional evaluation of myoelectrically-controlled hand prostheses: a pilot study using the virtual peg insertion test. In Proc. 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR) 392–397 (2019).

  11. Tan, D. W. et al. A neural interface provides long-term stable natural touch perception. Sci. Transl. Med. 6, 257ra138 (2014).

    PubMed  PubMed Central  Article  Google Scholar 

  12. Raspopovic, S. et al. Restoring natural sensory feedback in real-time bidirectional hand prostheses. Sci. Transl. Med. 6, 222ra19 (2014).

    PubMed  Article  Google Scholar 

  13. Clemente, F. et al. Non-Invasive, temporally discrete feedback of object contact and release improves grasp control of closed-loop myoelectric transradial prostheses. IEEE Trans. Neural Syst. Rehabil. Eng. 24, 1314–1322 (2016).

    PubMed  Article  Google Scholar 

  14. D’Anna, E. et al. A somatotopic bidirectional hand prosthesis with transcutaneous electrical nerve stimulation based sensory feedback. Sci. Rep. 7, 10930 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  15. Valle, G. et al. Biomimetic intraneural sensory feedback enhances sensation naturalness, tactile sensitivity, and manual dexterity in a bidirectional prosthesis. Neuron 100, 37–45 (2018).

    CAS  PubMed  Article  Google Scholar 

  16. Osborn, L. E. et al. Prosthesis with neuromorphic multilayered e-dermis perceives touch and pain. Sci. Robot. 3, eaat3818 (2018).

    Article  Google Scholar 

  17. Zollo, L. et al. Restoring tactile sensations via neural interfaces for real-time force-and-slippage closed-loop control of bionic hands. Sci. Robot. 4, eaau9924 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  18. D’Anna, E. et al. A closed-loop hand prosthesis with simultaneous intraneural tactile and position feedback. Sci. Robot. 4, eaau8892 (2019).

    PubMed  Article  Google Scholar 

  19. Rus, D. & Tolley, M. T. Design, fabrication and control of soft robots. Nature 521, 467–475 (2015).

    CAS  PubMed  Article  Google Scholar 

  20. Rich, S. I., Wood, R. J. & Majidi, C. Untethered soft robotics. Nat. Electron. 1, 102–112 (2018).

    Article  Google Scholar 

  21. Polygerinos, P. et al. Soft Robotics: review of fluid-driven intrinsically soft devices; manufacturing, sensing, control, and applications in human-robot interaction. Adv. Eng. Mater. 19, 1700016 (2017).

    Article  CAS  Google Scholar 

  22. Hu, W., Lum, G. Z., Mastrangeli, M. & Sitti, M. Small-scale soft-bodied robot with multimodal locomotion. Nature 554, 81–85 (2018).

    CAS  PubMed  Article  Google Scholar 

  23. Acome, E. et al. Hydraulically amplified self-healing electrostatic actuators with muscle-like performance. Science 359, 61–65 (2018).

    CAS  PubMed  Article  Google Scholar 

  24. Connolly, F., Walsh, C. J. & Bertoldi, K. Automatic design of fiber-reinforced soft actuators for trajectory matching. Proc. Natl Acad. Sci. USA 114, 51–56 (2017).

    CAS  PubMed  Article  Google Scholar 

  25. Cacucciolo, V. et al. Stretchable pumps for soft machines. Nature 572, 516–519 (2019).

    CAS  PubMed  Article  Google Scholar 

  26. Farrow, N. & Correll, N. A soft pneumatic actuator that can sense grasp and touch. In Proc. IEEE International Conference on Intelligent Robots and Systems (IROS) 2317–2323 (IEEE, 2015).

  27. Ferris, D. P. & Lewis, C. L. Robotic lower limb exoskeletons using proportional myoelectric control. In Proc. IEEE Engineering in Medicine and Biology Society Annual Conference 2119–2124 (2009).

  28. Polygerinos, P. et al. EMG controlled soft robotic glove for assistance during activities of daily living. In Proc. IEEE International Conference on Rehabilitation Robotics (ICORR) 55–60 (IEEE, 2015).

  29. Ge, L. et al. Design, modeling, and evaluation of fabric-based pneumatic actuators for soft wearable assistive gloves. Soft Robot. 7, 583–596 (2020).

    PubMed  Article  Google Scholar 

  30. Deimel, R. & Brock, O. A novel type of compliant and underactuated robotic hand for dexterous grasping. Int. J. Robot. Res. 35, 161–185 (2016).

    Article  Google Scholar 

  31. Scharff et al. In Soft Robotics: Rends, Applications and Challenges (eds Laschi, C. et al.) 23–29 (Springer, 2017).

  32. Zhao, H., O’Brien, K., Li, S. & Shepherd, R. F. Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides. Sci. Robot. 1, 7529 (2016).

    Article  Google Scholar 

  33. Zhou, J. et al. BCL-13: a 13-DOF soft robotic hand for dexterous grasping and in-hand manipulation. IEEE Robot. Autom. Lett. 3, 3379–3386 (2018).

    Article  Google Scholar 

  34. Zhou, J. et al. A Soft-robotic approach to anthropomorphic robotic hand dexterity. IEEE Access 7, 101483–101495 (2019).

    Article  Google Scholar 

  35. Emerson, E. T., Krizek, T. J. & Greenwald, D. P. Anatomy, physiology, and functional restoration of the thumb. Ann. Plast. Surg. 36, 180–191 (1996).

    CAS  PubMed  Article  Google Scholar 

  36. Gustus, A., Stillfried, G., Visser, J., Jörntell, H. & Smagt, P. Human hand modelling: kinematics, dynamics, applications. Biol. Cybern. 106, 741–755 (2012).

    PubMed  Article  Google Scholar 

  37. Keplinger, C. et al. Stretchable, transparent, ionic conductors. Science 341, 984–987 (2013).

    CAS  PubMed  Article  Google Scholar 

  38. Yang, C. & Suo, Z. Hydrogel ionotronics. Nat. Rev. Mater. 3, 125–142 (2018).

    CAS  Article  Google Scholar 

  39. Gu, G. et al. Integrated soft ionotronic skin with stretchable and transparent hydrogel-elastomer ionic sensors for hand-motion monitoring. Soft Robot. 6, 368–376 (2019).

    PubMed  Article  Google Scholar 

  40. Englehart, K. & Hudgins, B. A robust, real-time control scheme for multifunction myoelectric control. IEEE Trans. Biomed. Eng. 50, 848–854 (2003).

    PubMed  Article  Google Scholar 

  41. Feix, T., Romero, J., Schmiedmayer, H., Dollar, A. M. & Kragic, D. The GRASP taxonomy of human grasp types. IEEE Trans. Hum. Mach. Syst. 46, 66–77 (2016).

    Article  Google Scholar 

  42. Bullock, I. M. et al. Grasp frequency and usage in daily household and machine shop tasks. IEEE Trans. Haptics 6, 296–308 (2013).

    PubMed  Article  Google Scholar 

  43. Kyberd, P. J., Evans, M. & Winkel, S. An intelligent anthropomorphic hand, with automatic Grasp. Robotica 16, 531–536 (1998).

    Article  Google Scholar 

  44. Hammock, M. L., Chortos, A., Tee, B., Tok, J. & Bao, Z. 25th anniversary article: the evolution of electronic skin (e-skin): a brief history, design considerations, and recent progress. Adv. Mater. 25, 5997–6038 (2013).

    CAS  PubMed  Article  Google Scholar 

  45. Resnik, L. & Borgia, M. Reliability and validity of outcome measures for upper limb amputation. JPO J. Prosthet. Orthot. 24, 192–201 (2012).

    Article  Google Scholar 

  46. Phillips, S. L., Harris, M. S., Koss, L. & Latlief, G. Experiences and outcomes with powered partial hand prostheses: a case series of subjects with multiple limb amputations. JPO J. Prosthet. Orthot. 24, 93–97 (2012).

    Article  Google Scholar 

  47. Smit, G., Plettenburg, D. & Helm, F. The lightweight delft cylinder hand, the first multi-articulating hand that meets the basic user requirements. IEEE Trans. Neural Syst. Rehabil. Eng. 23, 431–440 (2015).

    PubMed  Article  Google Scholar 

  48. Fougner, A. et al. Control of upper limb prostheses: terminology and proportional myoelectric control—a review. IEEE Trans. Neural Syst. Rehabil. Eng. 20, 663–677 (2012).

    PubMed  Article  Google Scholar 

  49. Hahne, J. M. et al. Simultaneous control of multiple functions of bionic hand prostheses: performance and robustness in end users. Sci. Robot. 3, eaat3630 (2018).

    PubMed  Article  Google Scholar 

  50. Zhuang, K. Z. et al. Shared human-robot proportional control of a dexterous myoelectric prosthesis. Nat. Mach. Intell. 1, 400–411 (2019).

    Article  Google Scholar 

  51. Jones, D. R. H & Ashby, M. F. Engineering Materials 1: An Introduction to Properties, Applications and Design 4th edn (Butterworth-Heinemann, 2011).

  52. Farina, D. et al. The extraction of neural information from the surface EMG for the control of upper-limb prostheses: emerging avenues and challenges. IEEE Trans. Neural Syst. Rehabil. Eng. 22, 797–809 (2014).

    PubMed  Article  Google Scholar 

  53. Chai, G. et al. Characterization of evoked tactile sensation in forearm amputees with transcutaneous electrical nerve stimulation. J. Neural Eng. 12, 066002 (2015).

    PubMed  Article  Google Scholar 

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We thank the participants for agreeing to participate in this research; M. Feng, Z. Shen, X. Huang and N. Ding for their participation in building the experimental set-ups; and Q. He for the discussions of the model and simulation. This study was supported in part by the National Natural Science Foundation of China (grant nos 91948302, 52025057 and 51620105002), the Science and Technology Commission of Shanghai Municipality (grant no. 20550712100), Shanghai Jiao Tong University Scientific and Technological Innovation Funds, and Massachusetts Institute of Technology.

Author information

Authors and Affiliations



G.G., N.Z., X. Zhu and X. Zhao conceived the idea and designed the study. G.G., N.Z., H.X., H.Y., Q.S. and X. Zhu performed experiments and analysed the experimental data. Y.Y., G.C., X.S. and X. Zhu developed the EMG sensors and electrical stimulation platform. G.G., S.L., L.G. and X. Zhao developed the theoretical model and performed the FEM simulation for verification. G.G., X. Zhu and X. Zhao directed the project. G.G., N.Z., H.X., X. Zhu and X. Zhao prepared the manuscript and all of the authors provided feedback and agree with the final version of the manuscript.

Corresponding authors

Correspondence to Guoying Gu, Xiangyang Zhu or Xuanhe Zhao.

Ethics declarations

Competing interests

G.G., N.Z., H.X., S.L., X. Zhu and X. Zhao are listed as co-inventors on a patent application (US application no. 63/039,929) that covers the design and fabrication of the soft neuroprosthetic hand.

Additional information

Peer review information Nature Biomedical Engineering thanks the anonymous reviewers for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary methods, figures, tables and references, and captions for Supplementary Videos 1–14.

Reporting Summary

Supplementary Video 1

Simulation and experiments of the individual motion of five soft fingers.

Supplementary Video 2

Demonstration of independent control of 6 d.f. with one pump.

Supplementary Video 3

Demonstration of the durability of a soft finger.

Supplementary Video 4

Demonstration of fast wearing and training of a soft neuroprosthetic hand.

Supplementary Video 5

Evaluation of the soft neuroprosthetic hand with standardized tests.

Supplementary Video 6

Results of the standardized tests by the same participant wearing a rigid neuroprosthetic hand.

Supplementary Video 7

Demonstration of the compliant advantage of the soft neuroprosthetic hand.

Supplementary Video 8

Demonstration of the four electromyography-controlled grasp types.

Supplementary Video 9

Demonstration of versatile hand functions in daily activities of the individual.

Supplementary Video 10

Demonstration of handling objects with different shapes and sizes.

Supplementary Video 11

Demonstration of holding heavy payloads.

Supplementary Video 12

Demonstration of the touch sensation of an individual finger and multiple fingers.

Supplementary Video 13

Demonstration of closed-loop control.

Supplementary Video 14

Demonstration of graded tactile feedback.

Supplementary Dataset 1

Source data for Fig. 3a.

Supplementary Dataset 2

Source data for Supplementary Fig. 23.

Supplementary Dataset 3

Source data for Supplementary Fig. 26.

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Gu, G., Zhang, N., Xu, H. et al. A soft neuroprosthetic hand providing simultaneous myoelectric control and tactile feedback. Nat Biomed Eng (2021).

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