Treatment of phantom limb pain (PLP) based on augmented reality and gaming controlled by myoelectric pattern recognition: A case study of a chronic PLP patient

Frontiers in Neuroscience

Volumn , Issue 8 FEB, 2014, Pages

  Ortiz Catalan, Max ^a,b   Sander, Nichlas ^a   Kristoffersen, Morten B ^a,b   Håkansson, Bo ^a   Brånemark, Rickard ^b  

^a CHALMERS UNIVERSITY OF TECHNOLOGY   (Sweden)

^b SAHLGRENSKA UNIVERSITY HOSPITAL   (Sweden)

Author keywords

Augmented reality; Electromyography; Myoelectric control; Neurorehabilitation; Pattern recognition; Phantom limb pain; Virtual reality

Indexed keywords

AGED; AMPLIFIER; AMPUTATION STUMP; ANALGESIA; ARTICLE; AUGMENTED REALITY; BEHAVIOR THERAPY; BRAIN DEPTH RECORDING; CASE REPORT; GAME; HUMAN; LIMB AMPUTATION; LIMB MOVEMENT; MALE; MCGILL PAIN QUESTIONNAIRE; MYOELECTRICITY; NOCICEPTION; PAIN ASSESSMENT; PATTERN RECOGNITION; PHANTOM PAIN; PREDICTION; RANGE OF MOTION; VIRTUAL REALITY EXPOSURE THERAPY; VISUAL FEEDBACK;

EID: 84898040970     PISSN: 16624548     EISSN: 1662453X     Source Type: Journal    
DOI: 10.3389/fnins.2014.00024     Document Type: Article

References (33)

1. Bach, F., Schmitz, B., Maaß, H., Cakmak, H., Diers, M., Bodmann, R., et al. (2010). "Using interactive immersive VR/AR for the therapy of phantom limb pain," in Proceedings of the 13th International Conference on Humans Computer (Aizu-Wakamatsu), 183-187. Available online at: http://dl.acm.org/citation.cfm?id=1994529 [Accessed September 16, 2013].
2. Brodie, E. E., Whyte, A., and Niven, C. A. (2007). Analgesia through the looking-glass? A randomized controlled trial investigating the effect of viewing a "virtual" limb upon phantom limb pain, sensation and movement. Eur. J. Pain 11, 428-436. doi: 10.1016/j.ejpain.2006.06.002
3. Brodie, E. E., Whyte, A., and Waller, B. (2003). Increased motor control of a phantom leg in humans results from the visual feedback of a virtual leg. Neurosci. Lett. 341, 167-169. doi: 10.1016/S0304-3940(03)00160-5
4. Burckhardt, C. S., and Bjelle, A. (1994). A Swedish version of the short-form Mcgill Pain Questionnaire. Scand. J. Rheumatol. 23, 77-81. doi: 10.3109/03009749409103032
5. Clark, R. L., Bowling, F. L., Jepson, F., and Rajbhandari, S. (2013). Phantom limb pain after amputation in diabetic patients does not differ from that after amputation in nondiabetic patients. Pain 154, 729-732. doi: 10.1016/j.pain.2013.01.009
6. Cole, J., Crowle, S., Austwick, G., and Slater, D. H. (2009). Exploratory findings with virtual reality for phantom limb pain; from stump motion to agency and analgesia. Disabil. Rehabil. 31, 846-854. doi: 10.1080/09638280802355197
7. Desmond, D., O'Neill, K., De Paor, A., McDarby, G., and MacLachlan, M. (2006). Augmenting the reality of phantom limbs: three case studies using an augmented mirror box procedure. J. Prosthet Orthot. 18, 74. doi: 10.1097/00008526-200607000-00005
8. Dijkstra, P. U., Geertzen, J. H. B., Stewart, R., and van der Schans, C. P. (2002). Phantom pain and risk factors: a multivariate analysis. J. Pain Symptom Manag. 24, 578-585. doi: 10.1016/S0885-3924(02)00538-9
9. Di Pino, G., Porcaro, C., Tombini, M., Assenza, G., Pellegrino, G., Tecchio, F., et al. (2012). A neurally-interfaced hand prosthesis tuned inter-hemispheric communication. Restor. Neurol. Neurosci. 30, 407-418. doi: 10.3233/RNN-2012-120224
10. Flor, H., Elbert, T., Knecht, S., Wienbruch, C., Pantev, C., Birbaumer, N., et al. (1995). Phantom-limb pain as a perceptual correlate of cortical reorganization following arm amputation. Nature 375, 482-484. doi: 10.1038/375482a0
11. Flor, H., Nikolajsen, L., and Staehelin Jensen, T. (2006). Phantom limb pain: a case of maladaptive CNS plasticity? Nat. Rev. Neurosci. 7, 873-881. doi: 10.1038/nrn1991
12. Holden, M. K. (2005). Virtual environments for motor rehabilitation: review. Cyberpsychol. Behav. 8, 187-211. doi: 10.1089/cpb.2005.8.187
13. Kuiken, T., Dumanian, G., Lipschutz, R., Miller, L. A., and Stubblefield, K. (2004). The use of targeted muscle reinnervation for improved myoelectric prosthesis control in a bilateral shoulder disarticulation amputee. Prosthet. Orthot. Int. 28, 245-253. doi: 10.3109/03093640409167756
14. Kuiken, T., Li, G., Lock, B. A., Lipschutz, R. D., Miller, L. A., Stubblefield, K. A., et al. (2009). Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. J. Am. Med. Assoc. 301, 619-628. doi: 10.1001/jama.2009.116
15. Lee, S. W., Wilson, K. M., Lock, B. A., and Kamper, D. G. (2011). Subject-specific myoelectric pattern classification of functional hand movements for stroke survivors. IEEE Trans. Neural Syst. Rehabil. Eng. 19, 558-566. doi: 10.1109/TNSRE.2010.2079334
16. Liu, J., and Zhou, P. (2013). A novel myoelectric pattern recognition strategy for hand function restoration after incomplete cervical spinal cord injury. IEEE Trans. Neural Syst. Rehabil. Eng. 21, 96-103. doi: 10.1109/TNSRE.2012.2218832
17. Lotze, M., Grodd, W., Birbaumer, N., Erb, M., Huse, E., and Flor, H. (1999). Does use of a myoelectric prosthesis prevent cortical reorganization and phantom limb pain? Nat. Neurosci. 2, 501-502. doi: 10.1038/9145
18. Melzack, R. (1987). The short-form McGill pain questionnaire. Pain 30, 191-197. doi: 10.1016/0304-3959(87)91074-8
19. Mercier, C., and Sirigu, A. (2009). Training with virtual visual feedback to alleviate phantom limb pain. Neurorehabil. Neural Repair 23, 587-594. doi: 10.1177/1545968308328717
20. Murray, C. D., Patchick, E., Pettifer, S., Caillette, F., and Howard, T. (2006a). Immersive virtual reality as a rehabilitative technology for phantom limb experience: a protocol. Cyberpsychol. Behav. 9, 167-170. doi: 10.1089/cpb.2006.9.167
21. Murray, C. D., Patchick, E., Pettifer, S., Howard, T., Caillette, F., Kulkarni, J., et al. (2006b). Investigating the efficacy of a virtual mirror box in treating phantom limb pain in a sample of chronic sufferers. Int. J. Disabil. Hum. Dev. 5, 227-234. doi: 10.1515/IJDHD.2006.5.3.227
22. Nikolajsen, L., and Jensen, T. S. (2001). Phantom limb pain. Br. J. Anaesth. 87, 107-116. doi: 10.1093/bja/87.1.107
23. Ortiz-Catalan, M., Brånemark, R., and Håkansson, B. (2013). BioPatRec: a modular research platform for the control of artificial limbs based on pattern recognition algorithms. Source Code Biol. Med. 8:11. doi: 10.1186/1751-0473-8-11
24. Ortiz-Catalan, M., Håkansson, B., and Brånemark, R. (in press). Real-time and simultaneous control of artificial limbs based on pattern recognition algorithms. IEEE Trans. Neural Syst. Rehabil. Eng. (accepted).
25. Raffin, E., Giraux, P., and Reilly, K. T. (2012a). The moving phantom: motor execution or motor imagery? Cortex 48, 746-757. doi: 10.1016/j.cortex.2011.02.003
26. Raffin, E., Mattout, J., Reilly, K. T., and Giraux, P. (2012b). Disentangling motor execution from motor imagery with the phantom limb. Brain 135, 582-595. doi: 10.1093/brain/awr337
27. Ramachandra, V., and Rogers-Ramachandra, D. (1996). Synaesthesia in phantom limbs induced with mirrors. Proc. Biol. Sci. 263, 377-386. doi: 10.1098/rspb.1996.0058
28. Saridis, G. N., and Gootee, T. P. (1982). EMG pattern analysis and classification for a prosthetic arm. IEEE Trans. Biomed. Eng. 29, 403-412. doi: 10.1109/TBME.1982.324954
29. Sherman, R. A. (1980). Published treatments of phantom limb pain. J. Phys. Med. 59, 232-244.
30. Simon, A. M., Hargrove, L. J., Lock, B. A., and Kuiken, T. (2011a). A decision-based velocity ramp for minimizing the effect of misclassifications during real-time pattern recognition control. IEEE Trans. Biomed. Eng. 58, 2360-2368. doi: 10.1109/TBME.2011.2155063
31. Simon, A. M., Hargrove, L. J., Lock, B. A., and Kuiken, T. (2011b). Target achievement control test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses. J. Rehabil. Res. Dev. 48, 619-628. doi: 10.1682/JRRD.2010.08.0149
32. Sveistrup, H. (2004). Motor rehabilitation using virtual reality. J. Neuroeng. Rehabil. 1:10. doi: 10.1186/1743-0003-1-10
33. Wirta, R. W., Taylor, D. R., and Finley, F. R. (1978). Pattern-recognition arm prosthesis: a historical perspective-a final report. Bull. Prosthet. Res. Fall, 8-35.