Does EMG control lead to distinct motor adaptation?

Frontiers in Neuroscience

Volumn 8, Issue SEP, 2014, Pages

  Johnson, Reva E ^a,b   Kording, Konrad P ^a,b,c   Hargrove, Levi J ^a   Sensinger, Jonathon W ^a,d,e  

^a REHABILITATION INSTITUTE OF CHICAGO   (United States)

^b Northwestern University   (United States)

^c NORTHWESTERN UNIVERSITY   (United States)

^d UNIVERSITY OF NEW BRUNSWICK   (Canada)

^e UNIVERSITY OF NEW BRUNSWICK   (Canada)

Author keywords

EMG; Motor adaptation; Prosthesis control; Sensory feedback; Uncertainty

Indexed keywords

ADAPTATION; ARTICLE; BAYESIAN LEARNING; ELBOW BRACE; ELECTROMYOGRAM; FEMALE; HUMAN; HUMAN EXPERIMENT; JOINT; MALE; MOTOR ACTIVITY; MOVEMENT (PHYSIOLOGY); MUSCLE ISOTONIC CONTRACTION; NORMAL HUMAN; SENSORY FEEDBACK; TORQUE; VISUAL FEEDBACK;

EID: 84907197262     PISSN: 16624548     EISSN: 1662453X     Source Type: Journal    
DOI: 10.3389/fnins.2014.00302     Document Type: Article

References (31)

1. Antfolk, C., D'Alonzo, M., Rose´n, B., Lundborg, G., Sebelius, F., and Cipriani, C. (2013). Sensory feedback in upper limb prosthetics. Expert Rev. Med. Devices 10, 45-54. doi:10.1586/erd.12.68.
2. Baddeley, R. J., Ingram, H. A, and Miall, R. C. (2003). System identification applied to a visuomotor task: near-optimal human performance in a noisy changing task. J. Neurosci. 23, 3066-75.
3. Biddiss, E. A., Beaton, D., and Chau, T. (2007). Consumer design priorities for upper limb prosthetics. Disabil. Rehabil. Assist. Technol. 2, 346-357. doi:10.1080/17483100701714733.
4. Biddiss, E. A., and Chau, T. (2007). Upper limb prosthesis use and abandonment: a survey of the last 25 years. Prosthet. Orthot. Int. 31, 236-257. doi:10.1080/03093640600994581.
5. Burge, J., Ernst, M. O., and Banks, M. S. (2008). The statistical determinants of adaptation rate in human reaching. J. Vis. 8, 1-19. doi:10.1167/8.4.20.Introduction.
6. Chhabra, M., and Jacobs, R. A (2006). Near-optimal human adaptive control across different noise environments. J. Neurosci. 26, 10883-7. doi:10.1523/JNEUROSCI.2238-06.2006.
7. Clancy, E. A., Morin, E., and Merletti, R. (2002). Sampling, noise-reduction and amplitude estimation issues in surface electromyography. J. Electromyogr. Kinesiol. 12, 1-16.
8. Ernst, M. O., and Banks, M. S. (2002). Humans integrate visual and haptic information in a statistically optimal fashion. Nature 415, 429-33. doi:10.1038/415429a.
9. Heckathorne, C. (2004). Components for electric-powered systems. Atlas Amputations Limb Defic.
10. Hentschke, H., and Stu¨ttgen, M. C. (2011). Computation of measures of effect size for neuroscience data sets. Eur. J. Neurosci. 34, 1887-94. doi:10.1111/j.1460-9568.2011.07902.x.
11. Kawato, M. (1999). Internal models for motor control and trajectory planning. Curr. Opin. Neurobiol. 9, 718-727.
12. Kording, K., and Wolpert, D. M. (2004). Bayesian integration in sensorimotor learning. Nature 427, 244-7. doi:10.1038/nature02169.
13. Kuiken, T., Li, G., Lock, B., Lipschutz, R. D., Miller, L. A., Stubblefield, K., and Englehart, K. (2009). Targeted muscle reinnervation for real-time myoelectric control of multifunction artificial arms. J. Am. Med. Assoc. 301, 619-628.
14. Lotze, M., Flor, H., Grodd, W., Larbig, W., and Birbaumer, N. (2001). Phantom movements and pain. An fMRI study in upper limb amputees. Brain 124, 2268-77.
15. 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, 501-2. doi:10.1038/9145.
16. Orba´n, G., and Wolpert, D. M. (2011). Representations of uncertainty in sensorimotor control. Curr. Opin. Neurobiol. 21, 629-35. doi:10.1016/j.conb.2011.05.026.
17. Parker, P. A., Englehart, K., and Hudgins, B. S. (2006). Myoelectric signal processing for control of powered limb prostheses. J. Electromyogr. Kinesiol. 16, 541-8. doi:10.1016/j.jelekin.2006.08.006.
18. Poulet, J. F. A, and Hedwig, B. (2007). New insights into corollary discharges mediated by identified neural pathways. Trends Neurosci. 30, 14-21. doi:10.1016/j.tins.2006.11.005.
19. Radhakrishnan, S. M., Baker, S. N., and Jackson, A. (2008). Learning a novel myoelectric-controlled interface task. J. Neurophysiol. 100, 2397-408. doi:10.1152/jn.90614.2008.
20. Richardson, J. T. E. (2011). Eta squared and partial eta squared as measures of effect size in educational research. Educ. Res. Rev. 6, 135-147. doi:10.1016/j.edurev.2010.12.001.
21. Saunders, I., and Vijayakumar, S. (2011). The role of feed-forward and feedback processes for closed-loop prosthesis control. J. Neuroeng. Rehabil. 8, 60. doi:10.1186/1743-0003-8-60.
22. Sensinger, J. W., and Weir, R. F.(2008). User-modulated impedance control of a prosthetic elbow in unconstrained, perturbed motion. IEEE Trans. Biomed. Eng. 55, 1043-55. doi:10.1109/TBME.2007.905385.
23. Tassinari, H., Hudson, T. E., and Landy, M. S. (2006). Combining priors and noisy visual cues in a rapid pointing task. J. Neurosci. 26, 10154-63. doi:10.1523/JNEUROSCI.2779-06.2006.
24. Torres-Oviedo, G., and Bastian, A. J. (2012). Natural error patterns enable transfer of motor learning to novel contexts. J. Neurophysiol. 107, 346-56. doi:10.1152/jn.00570.2011.
25. Vodovnik, L., and Rebersek, S. (1974). Information content of myo-control signals for orthotic and prosthetic systems. Arch. Phys. Med. Rehabil. 55, 52-56.
26. Wei, K., and Kording, K. (2009). Relevance of error: what drives motor adaptation? J. Neurophysiol. 101, 655-64. doi:10.1152/jn.90545.2008.
27. Wei, K., and Kording, K. (2010). Uncertainty of feedback and state estimation determines the speed of motor adaptation. Front. Comput. Neurosci. 4, 11. doi:10.3389/fncom.2010.00011.
28. Weir, R. F., and Sensinger, J. W. (2009). "The design of artificial arms and hands for prosthetic applications," in Biomedical Engineering and Design Handbook, Volume 2, ed. M. Kutz (McGraw-Hill).
29. Wheeler, J. W., Bark, K., Savall, J., and Cutkosky, M. (2010). Investigation of rotational skin stretch for proprioceptive feedback with application to myoelectric systems. IEEE Trans. Neural Syst. Rehabil. Eng. 18, 58-66. doi:10.1109/TNSRE.2009.2039602.
30. Wolpert, D. M., Ghahramani, Z., and Jordan, M. I. (1995). An internal model for sensorimotor integration. Science 269, 1880-1882.
31. Zecca, M., Micera, S., Carrozza, M. C., and Dario, P. (2002). Control of multifunctional prosthetic hands by processing the electromyographic signal. Crit. Rev. Biomed. Eng. 30, 459-85.