Skip to main content
Log in

Humans can integrate feedback of discrete events in their sensorimotor control of a robotic hand

  • Research Article
  • Published:
Experimental Brain Research Aims and scope Submit manuscript

Abstract

Providing functionally effective sensory feedback to users of prosthetics is a largely unsolved challenge. Traditional solutions require high band-widths for providing feedback for the control of manipulation and yet have been largely unsuccessful. In this study, we have explored a strategy that relies on temporally discrete sensory feedback that is technically simple to provide. According to the Discrete Event-driven Sensory feedback Control (DESC) policy, motor tasks in humans are organized in phases delimited by means of sensory encoded discrete mechanical events. To explore the applicability of DESC for control, we designed a paradigm in which healthy humans operated an artificial robot hand to lift and replace an instrumented object, a task that can readily be learned and mastered under visual control. Assuming that the central nervous system of humans naturally organizes motor tasks based on a strategy akin to DESC, we delivered short-lasting vibrotactile feedback related to events that are known to forcefully affect progression of the grasp-lift-and-hold task. After training, we determined whether the artificial feedback had been integrated with the sensorimotor control by introducing short delays and we indeed observed that the participants significantly delayed subsequent phases of the task. This study thus gives support to the DESC policy hypothesis. Moreover, it demonstrates that humans can integrate temporally discrete sensory feedback while controlling an artificial hand and invites further studies in which inexpensive, noninvasive technology could be used in clever ways to provide physiologically appropriate sensory feedback in upper limb prosthetics with much lower band-width requirements than with traditional solutions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Antfolk C, Bjorkman A, Frank SO, Sebelius F, Lundborg G, Rosen B (2012) Sensory feedback from a prosthetic hand based on air-mediated pressure from the hand to the forearm skin. J Rehabil Med 44(8):702–707

    Article  PubMed  Google Scholar 

  • Antfolk C, D’Alonzo M, Rosén B, Lundborg G, Sebelius F, Cipriani C (2013) Sensory feedback in upper limb prosthetics. Expert Rev Med Devices 10(1):45–54

    Article  PubMed  CAS  Google Scholar 

  • Chatterjee A, Chaubey P, Martin J, Thakor N (2008) Testing a prosthetic haptic feedback simulator with an interactive force matching task. J Prosthet Orthot 20(2):27–34

    Article  Google Scholar 

  • Childress DS (1980) Closed-loop control in prosthetic systems: historical perspective. Ann Biomed Eng 8(4–6):293–303

    Article  PubMed  CAS  Google Scholar 

  • Cipriani C, Zaccone F, Micera S, Carrozza MC (2008) On the shared control of an EMG-controlled prosthetic hand: analysis of user–prosthesis interaction. IEEE Trans Robot 24(1):170–184

    Article  Google Scholar 

  • Cipriani C, Controzzi M, Carrozza MC (2011) The SmartHand transradial prosthesis. J Neuroeng Rehabil 8(29):1–13

    Google Scholar 

  • Cipriani C, D’Alonzo M, Carrozza MC (2012) A miniature vibrotactile sensory substitution device for multifingered hand prosthetics. IEEE Trans Biomed Eng 59(2):400–408

    Article  PubMed  Google Scholar 

  • Dhillon GS, Horch KW (2005) Direct neural sensory feedback and control of a prosthetic arm. IEEE Trans Neural Syst Rehabil Eng 13(4):468–472

    Article  PubMed  Google Scholar 

  • Flanagan JR, Bowman MC, Johansson RS (2006) Control strategies in object manipulation tasks. Curr Opin Neurobiol 16:650–659

    Article  PubMed  CAS  Google Scholar 

  • Gordon AM, Westling G, Cole KJ, Johansson RS (1993) Memory representations underlying motor commands used during manipulation of common and novel objects. J Neurophysiol 69:1789–1796

    PubMed  CAS  Google Scholar 

  • Hogan N, Bizzi E, Mussa-Ivaldi FA, Flash T (1987) Controlling multijoint motor behavior. Exerc Sport Sci Rev 15:153–190

    PubMed  CAS  Google Scholar 

  • Horch K, Meek S, Taylor TG, Hutchinson DT (2011) Object discrimination with an artificial hand using electrical stimulation of peripheral tactile and proprioceptive pathways with intrafascicular electrodes. IEEE Trans Neural Syst Rehabil Eng 19(5):483–489

    Article  PubMed  Google Scholar 

  • Johansson RS, Edin BB (1993) Predictive feed-forward sensory control during grasping and manipulation in man. Biomed Res 14(4):95–106

    Google Scholar 

  • Johansson RS, Westling G (1984) Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objects. Exp Brain Res 56:550–564

    Article  PubMed  CAS  Google Scholar 

  • Johansson RS, Westling G (1991) Afferent signals during manipulative tasks in man. In: Franzen O, Westman J (eds) Somatosensory mechanisms. Macmillan Press, London, pp 25–48

    Google Scholar 

  • Lundborg G (2003) Richard P. Bunge memorial lecture. Nerve injury and repair—a challenge to the plastic brain. J Peripher Nerv Syst 8:209–226

    Article  PubMed  Google Scholar 

  • Mann RW, Reimers SD (1970) Kinesthetic sensing for the EMG controlled Boston Arm. IEEE Trans Man–Mach Syst 11(1):110–115

    Article  Google Scholar 

  • Meek SG, Jacobsen SC, Goulding PP (1989) Extended physiologic taction: design and evaluation of a proportional force feedback system. J Rehabil Res Dev 26(3):53–62

    PubMed  CAS  Google Scholar 

  • Panarese A, Edin B, Vecchi F, Carrozza MC, Johansson RS (2009) Humans can integrate force feedback to toes in their sensorimotor control of a robotic hand. IEEE Trans Neural Syst Rehabil Eng 17(6):560–567

    Article  PubMed  Google Scholar 

  • Rosén B, Lundborg G, Dahlin LB, Holmberg J, Karlson B (1994) Nerve repair: correlation of restitution of functional sensibility with specific cognitive capacities. J Hand Surg 19:452–458

    Article  Google Scholar 

  • Rossini PM, Micera S, Benvenuto A et al (2010) Double nerve intraneural interface implant on a human amputee for robotic hand control. Clin Neurophysiol 121(5):777–783

    Article  PubMed  Google Scholar 

  • Sasaki Y, Nakayama Y, Yoshida M (2002) Sensory feedback system using interferential current for EMG prosthetic hand. Eng Med Biol 24th Annu Conf Annu Fall Meet Biomed Eng Soc Proc Second Joint IEEE 3:2402–2403

    Article  Google Scholar 

  • Saunders I, Vijayakumar S (2011) The role of feed-forward and feedback processes for closed-loop prosthesis control. J Neuroeng Rehabil 8(60):1–12

    Google Scholar 

  • Sensinger JW, Schultz AE, Kuiken TA (2009) Examination of force discrimination in human upper limb amputees with reinnervated limb sensation following peripheral nerve transfer. IEEE Trans Neural Syst Rehabil Eng 17(5):438–444

    Article  PubMed  PubMed Central  Google Scholar 

  • Stepp CE, An Q, Matsuoka Y (2012) Repeated training with augmentative vibrotactile feedback increases object manipulation performance. PLoS One 7(2):e32743. doi:10.1371/journal.pone.0032743

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  • Szeto AY, Saunders FA (1982) Electrocutaneous stimulation for sensory communication in rehabilitation engineering. IEEE Trans Biomed Eng 4:300–308

    Article  Google Scholar 

  • Tan D, Schiefer M, Keith MW, Anderson R, Tyler DJ (2013) Stability and selectivity of a chronic, multi-contact cuff electrode for sensory stimulation in a human amputee. In: International IEEE/EMBS Conference on Neural Engineering (NER), pp 859–862

  • Tsakiris M, Haggard P (2005) The rubber hand illusion revisited: visuotactile integration and self-attribution. J Exp Psychol Hum Percept Perform 3:80–91

    Article  Google Scholar 

  • Westling G, Johansson RS (1987) Responses in glabrous skin mechanoreceptors during precision grip in humans. Exp Brain Res 66:128–140

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

This work was supported by the European Commission under the WAY Project (FP7-ICT-288551), the Swedish Research Council (VR 2011-3128), the Italian Ministry of Education University and Research under the FIRB-2010 MY-HAND Project [RBFR10VCLD], by the Fulbright Program and by the Department of Veterans Affairs, Rehabilitation Research and Development Service administered through VA Eastern Colorado Healthcare System—Denver VAMC.

Conflict of interest

CC hold shares in Prensilia S.R.L., the company that manufactures robotic hands as the one used in this work, under the license to Scuola Superiore Sant’Anna.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Christian Cipriani.

Additional information

Jacob L. Segil and Francesco Clemente have contributed equally to this work.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cipriani, C., Segil, J.L., Clemente, F. et al. Humans can integrate feedback of discrete events in their sensorimotor control of a robotic hand. Exp Brain Res 232, 3421–3429 (2014). https://doi.org/10.1007/s00221-014-4024-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00221-014-4024-8

Keywords

Navigation