Skip to main content
Log in

Internal models of upper limb prosthesis users when grasping and lifting a fragile object with their prosthetic limb

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

Abstract

Internal models allow unimpaired individuals to appropriately scale grip force when grasping and lifting familiar objects. In prosthesis users, the internal model must adapt to the characteristics of the prosthetic devices and reduced sensory feedback. We studied the internal models of 11 amputees and eight unimpaired controls when grasping and lifting a fragile object. When the object was modified from a rigid to fragile state, both subject groups adapted appropriately by significantly reducing grasp force on the first trial with the fragile object compared to the rigid object (p < 0.020). There was a wide range of performance skill illustrated by amputee subjects when lifting the fragile object in 10 repeated trials. One subject, using a voluntary close device, never broke the object, four subjects broke the fragile device on every attempt and seven others failed on their initial attempts, but improved over the repeated trials. Amputees decreased their grip forces 51 ± 7 % from the first to the last trial (p < 0.001), indicating a practice effect. However, amputees used much higher levels of force than controls throughout the testing (p < 0.015). Amputees with better performance on the Box and Blocks test used lower grip force levels (p = 0.006) and had more successful lifts of the fragile object (p = 0.002). In summary, amputees do employ internal models when picking up objects; however, the accuracy of these models is poor and grip force modulation is significantly impaired. Further studies could examine the alternative sensory modalities and training parameters that best promote internal model formation.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Adee S (2009) The revolution will be prosthetized. Spectr IEEE 46:44–48

    Article  Google Scholar 

  • Biddiss EA, Chau TT (2007a) Upper limb prosthesis use and abandonment: a survey of the last 25 years. Prosthet Orthot Int 31:236–257

    Article  PubMed  Google Scholar 

  • Biddiss E, Chau T (2007b) Upper-limb prosthetics: critical factors in device abandonment. Am J Phys Med Rehabil 86:977–987

    Article  PubMed  Google Scholar 

  • Biddiss EA, Chau TT (2008) Multivariate prediction of upper limb prosthesis acceptance or rejection. Disabil Rehabil Assist Technol 3(4):181–192

    Article  PubMed  Google Scholar 

  • Bleecker M, Bolla-Wilson K, Kawas C, Agnew J (1988) Age-specific norms for the Mini-Mental State Exam. Neurology 38:1565–1568

    Article  CAS  PubMed  Google Scholar 

  • Bouwsema H, van der Sluis CK, Bongers RM (2008) The role of order of practice in learning to handle an upper-limb prosthesis. Arch Phys Med Rehabil 89(9):1759–1764

    Article  PubMed  Google Scholar 

  • Bouwsema H, van der Sluis CK, Bongers RM (2010) Learning to control opening and closing a myoelectric hand. Arch Phys Med Rehabil 91(9):1442–1446

    Article  PubMed  Google Scholar 

  • Bouwsema H, Kyberd PJ, Hill W, van der Sluis CK, Bongers RM (2012) Determining skill level in myoelectric prosthesis use with multiple outcome measures. J Rehabil Res Dev 49(9):1331–1348

    Article  PubMed  Google Scholar 

  • Bouwsema H, van der Sluis CK, Bongers RM (2014) Changes in performance over time while learning to use a myoelectric prosthesis. J Neuroeng Rehabil 11(1):16

    Article  PubMed Central  PubMed  Google Scholar 

  • Brashers-Krug T, Shadmehr R, Bizzi E (1996) Consolidation in human motor memory. Nature 382:252–255

    Article  CAS  PubMed  Google Scholar 

  • Caithness G, Osu R, Bays P et al (2004) Failure to consolidate the consolidation theory of learning for sensorimotor adaptation tasks. J Neurosci: Off J Soc Neurosci 24:8662–8671

    Article  CAS  Google Scholar 

  • Cohen LG, Bandinelli S, Findley TW, Hallett M (1991) Motor reorganization after upper limb amputation in man. A study with focal magnetic stimulation. Brain 114(1B):615–627

    Article  PubMed  Google Scholar 

  • Dromerick AW, Schabowsky CN, Holley RJ, Monroe B, Markotic A, Lum PS (2008) Effect of training on upper-extremity prosthetic performance and motor learning: a single-case study. Arch Phys Med Rehabil 89(6):1199–1204

    Article  PubMed  Google Scholar 

  • Dudkiewicz I, Gabrielov R, Seiv-Ner I, Zelig G, Heim M (2004) Evaluation of prosthetic usage in upper limb amputees. Disabil Rehabil 26:60–63

    Article  CAS  PubMed  Google Scholar 

  • Edin BB, Ascari L, Beccai L, Roccella S, Cabibihan JJ, Carrozza MC (2008) Bio-inspired sensorization of a biomechatronic robot hand for the grasp-and-lift task. Brain Res Bull 75(6):785–795

    Article  CAS  PubMed  Google Scholar 

  • Engeberg ED, Meek SG (2009) Backstepping and sliding mode control hybridized for a prosthetic hand. IEEE Trans Neural Syst Rehabil Eng 17(1):70–79

    Article  PubMed  Google Scholar 

  • Engeberg ED, Meek S (2012) Enhanced visual feedback for slip prevention with a prosthetic hand. Prosthet Orthot Int 36:423–429

    Article  PubMed  Google Scholar 

  • Engeberg ED, Meek S (2013) Adaptive sliding mode control for prosthetic hands to simultaneously prevent slip and minimize deformation of grasped objects. IEEE Trans Mechatron 18:376–385

    Article  Google Scholar 

  • Engeberg ED, Meek SG, Minor MA (2008) Hybrid force–velocity sliding mode control of a prosthetic hand. IEEE Trans Biomed Eng 55(5):1572–1581

    Article  PubMed  Google Scholar 

  • Gagne M, Hetu S, Reilly KT, Mercier C (2011) The map is not the territory: motor system reorganization in upper limb amputees. Hum Brain Mapp 32:509–519

    Article  PubMed  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

    CAS  PubMed  Google Scholar 

  • Hermsdorfer J, Elias Z, Cole JD, Quaney BM, Nowak DA (2008) Preserved and impaired aspects of feed-forward grip force control after chronic somatosensory deafferentation. Neurorehabil Neural Repair 22:374–384

    Article  CAS  PubMed  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 

  • Irlbacher K, Meyer B-U, Voss M, Brandt SA, Roricht S (2001) Spatial reorganization of cortical motor output maps of stump muscles in human upper-limb amputees. Neurosci Lett 321:129–132

    Article  Google Scholar 

  • Jacobs S, Danielmeier C, Frey SH (2010) Human anterior intraparietal and ventral premotor cortices support representations of grasping with the hand or a novel tool. J Cogn Neurosci 22(11):2594–2608

    Article  PubMed  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  CAS  PubMed  Google Scholar 

  • Kadiallah A, Franklin DW, Burdet E (2012) Generalization in adaptation to stable and unstable dynamics. PLoS ONE 7(10):e45075

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Kawato M (1999) Internal models for motor control and trajectory planning. Curr Opin Neurobiol 9:718–727

    Article  CAS  PubMed  Google Scholar 

  • Kim K, Colgate JE (2012) Haptic feedback enhances grip force control of sEMG-controlled prosthetic hands in targeted reinnervation amputees. IEEE Trans Neural Syst Rehabil Eng 20(6):798–805

    Article  PubMed  Google Scholar 

  • Kuiken TA, Miller LA, Lipschutz RD et al (2007) Targeted reinnervation for enhanced prosthetic arm function in a woman with a proximal amputation: a case study. Lancet 369:371–380

    Article  PubMed  Google Scholar 

  • Kuiken TA, Li G et al (2009) Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. JAMA 301:619–628

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Lang CE, Wagner JM, Dromerick AW, Edwards DF (2006) Measurement of upper-extremity function early after stroke: properties of the action research arm test. Arch Phys Med Rehabil 87:1605–1610

    Article  PubMed  Google Scholar 

  • Light CM, Chappell PH, Kyberd PJ (2002) Establishing a stan-dardized clinical assessment tool of pathologic and pros-thetic hand function: normative data, reliability, and validity. Arch Phys Med Rehabil 83(6):776–783

    Article  PubMed  Google Scholar 

  • McFarland LV, Hubbard Winkler SL, Heinemann AW, Jones M, Esquenazi A (2010) Unilateral upper-limb loss: satisfaction and prosthetic-device use in veterans and service members from Vietnam and OIF/OEF conflicts. J Rehabil Res Dev 47:299–316

    Article  PubMed  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

    CAS  PubMed  Google Scholar 

  • Mercier C, Reilly KT, Vargas CD, Aballea A, Sirigu A (2006) Mapping phantom movement representations in the motor cortex of amputees. Brain 129(8):2202–2210

    Article  PubMed  Google Scholar 

  • Metzger AJ, Dromerick AW, Schabowsky CN, Holley RJ, Monroe B, Lum PS (2010) Feedforward control strategies of subjects with transradial amputation in planar reaching. J Rehabil Res Dev 47(3):201–211

    Article  PubMed  Google Scholar 

  • Nowak DA, Hermsdorfer J, Glasauer S, Philipp J, Meyer L, Mai N (2001) The effects of digital anaesthesia on predictive grip force adjustments during vertical movements of a grasped object. Eur J Neurosci 14:756–762

    Article  CAS  PubMed  Google Scholar 

  • Ohnishi K, Weir RF, Kuiken TA (2007) Neural machine interfaces for controlling multifunctional powered upper-limb prostheses. Expert Rev Med Devices 4:43–53

    Article  PubMed  Google Scholar 

  • Park E, Meek SG (1995) Adaptive filtering of the electromyographic signal for prosthetic control and force estimation. IEEE Trans Bio-med Eng 42:1048–1052

    Article  CAS  Google Scholar 

  • Pasluosta CF, Chiu AW (2012) Evaluation of a neural network-based control strategy for a cost-effective externally-powered prosthesis. Assist Technol 24(3):196–208

    Article  PubMed  Google Scholar 

  • Philip BA, Frey SH (2011) Preserved grip selection planning in chronic unilateral upper extremity amputees. Exp Brain Res 214:437–452

    Article  PubMed  Google Scholar 

  • Philip BA, Frey SH (2014) Compensatory changes accompanying chronic forced use of the nondominant hand by unilateral amputees. J Neurosci 34(10):3622–3631

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Platz T, Pinkowski C, van Wijck F, Kim IH, di Bella P, Johnson G (2005) Reliability and validity of arm function assessment with standardized guidelines for the Fugl-Meyer Test, action research arm test and box and block test: a multicentre study. Clin Rehabil 19(4):404–411

    Article  PubMed  Google Scholar 

  • Rijntjes M, Dettmers C, Büchel C, Kiebel S, Frackowiak RS, Weiller C (1999) A blueprint for movement: functional and anatomical representations in the human motor system. J Neurosci 19(18):8043–8048

    CAS  PubMed  Google Scholar 

  • Rombokas E, Stepp CE, Chang C, Malhotra M, Matsuoka Y (2013) Vibrotactile sensory substitution for electromyographic control of object manipulation. IEEE Trans Biomed Eng 60(8):2226–2232

    Article  PubMed  Google Scholar 

  • Schabowsky CN, Dromerick AW, Holley RJ, Monroe B, Lum PS (2008) Trans-radial upper extremity amputees are capable of adapting to a novel dynamic environment. Exp Brain Res 188:589–601

    Article  PubMed  Google Scholar 

  • Shadmehr R, Mussa-Ivaldi FA (1994) Adaptive representation of dynamics during learning of a motor task. J Neurosci 14:3208–3224

    CAS  PubMed  Google Scholar 

  • Umiltà MA, Escola L, Intskirveli I, Grammont F, Rochat M, Caruana F, Jezzini A, Gallese V, Rizzolatti G (2008) When pliers become fingers in the monkey motor system. Proc Natl Acad Sci USA 105(6):2209–2213

    Article  PubMed Central  PubMed  Google Scholar 

  • Weeks DL, Wallace SA, Noteboom JT (2000) Precision-grip force changes in the anatomical and prosthetic limb during predictable load increases. Exp Brain Res 132:404–410

    Article  CAS  PubMed  Google Scholar 

  • Weeks DL, Wallace SA, Anderson DI (2003) Training with an upper-limb prosthetic simulator to enhance transfer of skill across limbs. Arch Phys Med Rehabil 84(3):437–443

    Article  PubMed  Google Scholar 

  • Wettels N, Parnandi A, Moon J, Loeb G, Sukhatme G (2009) Grip control using biomimetic tactile sensing systems. IEEE/ASME Trans Mechantron 14:718–723

    Article  Google Scholar 

  • Ziegler-Graham K, MacKenzie EJ, Ephraim PL, Travison TG, Brookmeyer R (2008) Estimating the prevalence of limb loss in the united states: 2005 to 2050. Arch Phys Med Rehabil 89:422–429

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The Funding for this work provided by the US Army Medical Research and Materiel Command (W81XWH-11-1-0632) and the Department of Veterans Affairs (A7104P).

Conflict of interest

The authors have no conflict of interests to report.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Peter S. Lum.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lum, P.S., Black, I., Holley, R.J. et al. Internal models of upper limb prosthesis users when grasping and lifting a fragile object with their prosthetic limb. Exp Brain Res 232, 3785–3795 (2014). https://doi.org/10.1007/s00221-014-4071-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00221-014-4071-1

Keywords

Navigation