Empirical Inference

Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery

2011

Article

ei


The combination of brain–computer interfaces (BCIs) with robot-assisted physical therapy constitutes a promising approach to neurorehabilitation of patients with severe hemiparetic syndromes caused by cerebrovascular brain damage (e.g. stroke) and other neurological conditions. In such a scenario, a key aspect is how to reestablish the disrupted sensorimotor feedback loop. However, to date it is an open question how artificially closing the sensorimotor feedback loop influences the decoding performance of a BCI. In this paper, we answer this issue by studying six healthy subjects and two stroke patients. We present empirical evidence that haptic feedback, provided by a seven degrees of freedom robotic arm, facilitates online decoding of arm movement intention. The results support the feasibility of future rehabilitative treatments based on the combination of robot-assisted physical therapy with BCIs.

Author(s): Gomez Rodriguez, M. and Peters, J. and Hill, J. and Schölkopf, B. and Gharabaghi, A. and Grosse-Wentrup, M.
Journal: Journal of Neural Engineering
Volume: 8
Number (issue): 3
Pages: 1-12
Year: 2011
Month: June
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Digital: 0
DOI: 10.1088/1741-2560/8/3/036005
EPUB: 036005

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BibTex

@article{GomezRodriguezPHSGG2011_2,
  title = {Closing the sensorimotor loop: haptic feedback facilitates decoding of motor imagery },
  author = {Gomez Rodriguez, M. and Peters, J. and Hill, J. and Sch{\"o}lkopf, B. and Gharabaghi, A. and Grosse-Wentrup, M.},
  journal = {Journal of Neural Engineering},
  volume = {8},
  number = {3},
  pages = {1-12},
  month = jun,
  year = {2011},
  doi = {10.1088/1741-2560/8/3/036005},
  month_numeric = {6}
}