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.
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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
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
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
Childress DS (1980) Closed-loop control in prosthetic systems: historical perspective. Ann Biomed Eng 8(4–6):293–303
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
Cipriani C, Controzzi M, Carrozza MC (2011) The SmartHand transradial prosthesis. J Neuroeng Rehabil 8(29):1–13
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
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
Flanagan JR, Bowman MC, Johansson RS (2006) Control strategies in object manipulation tasks. Curr Opin Neurobiol 16:650–659
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
Hogan N, Bizzi E, Mussa-Ivaldi FA, Flash T (1987) Controlling multijoint motor behavior. Exerc Sport Sci Rev 15:153–190
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
Johansson RS, Edin BB (1993) Predictive feed-forward sensory control during grasping and manipulation in man. Biomed Res 14(4):95–106
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
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
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
Mann RW, Reimers SD (1970) Kinesthetic sensing for the EMG controlled Boston Arm. IEEE Trans Man–Mach Syst 11(1):110–115
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
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
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
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
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
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
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
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
Szeto AY, Saunders FA (1982) Electrocutaneous stimulation for sensory communication in rehabilitation engineering. IEEE Trans Biomed Eng 4:300–308
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
Westling G, Johansson RS (1987) Responses in glabrous skin mechanoreceptors during precision grip in humans. Exp Brain Res 66:128–140
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.
Jacob L. Segil and Francesco Clemente have contributed equally to this work.
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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
- Sensorimotor control
- Tactile afferents
- Sensory substitution
- Sensory feedback