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Experimental Brain Research

, Volume 232, Issue 12, pp 3785–3795 | Cite as

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

  • Peter S. LumEmail author
  • Iian Black
  • Rahsaan J. Holley
  • Jessica Barth
  • Alexander W. Dromerick
Research Article

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.

Keywords

Amputation Internal model Grasp Prosthesis Motor control 

Notes

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.

References

  1. Adee S (2009) The revolution will be prosthetized. Spectr IEEE 46:44–48CrossRefGoogle Scholar
  2. Biddiss EA, Chau TT (2007a) Upper limb prosthesis use and abandonment: a survey of the last 25 years. Prosthet Orthot Int 31:236–257PubMedCrossRefGoogle Scholar
  3. Biddiss E, Chau T (2007b) Upper-limb prosthetics: critical factors in device abandonment. Am J Phys Med Rehabil 86:977–987PubMedCrossRefGoogle Scholar
  4. Biddiss EA, Chau TT (2008) Multivariate prediction of upper limb prosthesis acceptance or rejection. Disabil Rehabil Assist Technol 3(4):181–192PubMedCrossRefGoogle Scholar
  5. Bleecker M, Bolla-Wilson K, Kawas C, Agnew J (1988) Age-specific norms for the Mini-Mental State Exam. Neurology 38:1565–1568PubMedCrossRefGoogle Scholar
  6. 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):1759–1764PubMedCrossRefGoogle Scholar
  7. Bouwsema H, van der Sluis CK, Bongers RM (2010) Learning to control opening and closing a myoelectric hand. Arch Phys Med Rehabil 91(9):1442–1446PubMedCrossRefGoogle Scholar
  8. 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):1331–1348PubMedCrossRefGoogle Scholar
  9. 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):16PubMedCentralPubMedCrossRefGoogle Scholar
  10. Brashers-Krug T, Shadmehr R, Bizzi E (1996) Consolidation in human motor memory. Nature 382:252–255PubMedCrossRefGoogle Scholar
  11. 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 24:8662–8671CrossRefGoogle Scholar
  12. 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):615–627PubMedCrossRefGoogle Scholar
  13. 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):1199–1204PubMedCrossRefGoogle Scholar
  14. Dudkiewicz I, Gabrielov R, Seiv-Ner I, Zelig G, Heim M (2004) Evaluation of prosthetic usage in upper limb amputees. Disabil Rehabil 26:60–63PubMedCrossRefGoogle Scholar
  15. 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):785–795PubMedCrossRefGoogle Scholar
  16. Engeberg ED, Meek SG (2009) Backstepping and sliding mode control hybridized for a prosthetic hand. IEEE Trans Neural Syst Rehabil Eng 17(1):70–79PubMedCrossRefGoogle Scholar
  17. Engeberg ED, Meek S (2012) Enhanced visual feedback for slip prevention with a prosthetic hand. Prosthet Orthot Int 36:423–429PubMedCrossRefGoogle Scholar
  18. 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 18:376–385CrossRefGoogle Scholar
  19. Engeberg ED, Meek SG, Minor MA (2008) Hybrid force–velocity sliding mode control of a prosthetic hand. IEEE Trans Biomed Eng 55(5):1572–1581PubMedCrossRefGoogle Scholar
  20. 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 32:509–519PubMedCrossRefGoogle Scholar
  21. Gordon AM, Westling G, Cole KJ, Johansson RS (1993) Memory representations underlying motor commands used during manipulation of common and novel objects. J Neurophysiol 69:1789–1796PubMedGoogle Scholar
  22. 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 22:374–384PubMedCrossRefGoogle Scholar
  23. 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):483–489PubMedCrossRefGoogle Scholar
  24. 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 321:129–132CrossRefGoogle Scholar
  25. 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):2594–2608PubMedCrossRefGoogle Scholar
  26. 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 56:550–564PubMedCrossRefGoogle Scholar
  27. Kadiallah A, Franklin DW, Burdet E (2012) Generalization in adaptation to stable and unstable dynamics. PLoS ONE 7(10):e45075PubMedCentralPubMedCrossRefGoogle Scholar
  28. Kawato M (1999) Internal models for motor control and trajectory planning. Curr Opin Neurobiol 9:718–727PubMedCrossRefGoogle Scholar
  29. 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):798–805PubMedCrossRefGoogle Scholar
  30. 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 369:371–380PubMedCrossRefGoogle Scholar
  31. Kuiken TA, Li G et al (2009) Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. JAMA 301:619–628PubMedCentralPubMedCrossRefGoogle Scholar
  32. 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 87:1605–1610PubMedCrossRefGoogle Scholar
  33. 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):776–783PubMedCrossRefGoogle Scholar
  34. 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 47:299–316PubMedCrossRefGoogle Scholar
  35. 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):53–62PubMedGoogle Scholar
  36. Mercier C, Reilly KT, Vargas CD, Aballea A, Sirigu A (2006) Mapping phantom movement representations in the motor cortex of amputees. Brain 129(8):2202–2210PubMedCrossRefGoogle Scholar
  37. 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):201–211PubMedCrossRefGoogle Scholar
  38. 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 14:756–762PubMedCrossRefGoogle Scholar
  39. Ohnishi K, Weir RF, Kuiken TA (2007) Neural machine interfaces for controlling multifunctional powered upper-limb prostheses. Expert Rev Med Devices 4:43–53PubMedCrossRefGoogle Scholar
  40. Park E, Meek SG (1995) Adaptive filtering of the electromyographic signal for prosthetic control and force estimation. IEEE Trans Bio-med Eng 42:1048–1052CrossRefGoogle Scholar
  41. Pasluosta CF, Chiu AW (2012) Evaluation of a neural network-based control strategy for a cost-effective externally-powered prosthesis. Assist Technol 24(3):196–208PubMedCrossRefGoogle Scholar
  42. Philip BA, Frey SH (2011) Preserved grip selection planning in chronic unilateral upper extremity amputees. Exp Brain Res 214:437–452PubMedCrossRefGoogle Scholar
  43. Philip BA, Frey SH (2014) Compensatory changes accompanying chronic forced use of the nondominant hand by unilateral amputees. J Neurosci 34(10):3622–3631PubMedCentralPubMedCrossRefGoogle Scholar
  44. 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):404–411PubMedCrossRefGoogle Scholar
  45. 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):8043–8048PubMedGoogle Scholar
  46. 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):2226–2232PubMedCrossRefGoogle Scholar
  47. 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 188:589–601PubMedCrossRefGoogle Scholar
  48. Shadmehr R, Mussa-Ivaldi FA (1994) Adaptive representation of dynamics during learning of a motor task. J Neurosci 14:3208–3224PubMedGoogle Scholar
  49. 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):2209–2213PubMedCentralPubMedCrossRefGoogle Scholar
  50. Weeks DL, Wallace SA, Noteboom JT (2000) Precision-grip force changes in the anatomical and prosthetic limb during predictable load increases. Exp Brain Res 132:404–410PubMedCrossRefGoogle Scholar
  51. 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):437–443PubMedCrossRefGoogle Scholar
  52. Wettels N, Parnandi A, Moon J, Loeb G, Sukhatme G (2009) Grip control using biomimetic tactile sensing systems. IEEE/ASME Trans Mechantron 14:718–723CrossRefGoogle Scholar
  53. 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 89:422–429PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Peter S. Lum
    • 1
    • 2
    • 3
    Email author
  • Iian Black
    • 3
  • Rahsaan J. Holley
    • 3
  • Jessica Barth
    • 3
  • Alexander W. Dromerick
    • 2
    • 3
    • 4
  1. 1.Biomedical EngineeringThe Catholic University of AmericaWashingtonUSA
  2. 2.Washington DC Veterans Affairs Medical CenterWashingtonUSA
  3. 3.MedStar National Rehabilitation HospitalWashingtonUSA
  4. 4.Georgetown University Medical CenterWashingtonUSA

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