Simultaneous neural control of simple reaching and grasping with the modular prosthetic limb using intracranial EEG

Matthew S. Fifer, Guy Hotson, Brock A. Wester, David P. McMullen, Yujing Wang, Matthew S. Johannes, Kapil D. Katyal, John B. Helder, Matthew P. Para, R. Jacob Vogelstein, William S Anderson, Nitish V Thakor, Nathan E Crone

Research output: Contribution to journalArticle

Abstract

Intracranial electroencephalographic (iEEG) signals from two human subjects were used to achieve simultaneous neural control of reaching and grasping movements with the Johns Hopkins University Applied Physics Lab (JHU/APL) Modular Prosthetic Limb (MPL), a dexterous robotic prosthetic arm. We performed functional mapping of high gamma activity while the subject made reaching and grasping movements to identify task-selective electrodes. Independent, online control of reaching and grasping was then achieved using high gamma activity from a small subset of electrodes with a model trained on short blocks of reaching and grasping with no further adaptation. Classification accuracy did not decline (p <0.05, one-way ANOVA) over three blocks of testing in either subject. Mean classification accuracy during independently executed overt reach and grasp movements for (Subject 1, Subject 2) were (0.85, 0.81) and (0.80, 0.96), respectively, and during simultaneous execution they were (0.83, 0.88) and (0.58, 0.88), respectively. Our models leveraged knowledge of the subject's individual functional neuroanatomy for reaching and grasping movements, allowing rapid acquisition of control in a time-sensitive clinical setting. We demonstrate the potential feasibility of verifying functionally meaningful iEEG-based control of the MPL prior to chronic implantation, during which additional capabilities of the MPL might be exploited with further training.

Original languageEnglish (US)
Article number6807532
Pages (from-to)695-705
Number of pages11
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume22
Issue number3
DOIs
StatePublished - 2014

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Electroencephalography
Prosthetics
Extremities
Electrodes
Neuroanatomy
Physics
Robotics
Analysis of Variance
Arm
Analysis of variance (ANOVA)
Electrocorticography
Testing

Keywords

  • Brain-machine interface (BMI)
  • electrocorticography
  • functional mapping
  • high gamma
  • upper limb prosthesis

ASJC Scopus subject areas

  • Neuroscience(all)
  • Computer Science Applications
  • Biomedical Engineering
  • Medicine(all)

Cite this

Simultaneous neural control of simple reaching and grasping with the modular prosthetic limb using intracranial EEG. / Fifer, Matthew S.; Hotson, Guy; Wester, Brock A.; McMullen, David P.; Wang, Yujing; Johannes, Matthew S.; Katyal, Kapil D.; Helder, John B.; Para, Matthew P.; Vogelstein, R. Jacob; Anderson, William S; Thakor, Nitish V; Crone, Nathan E.

In: IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 22, No. 3, 6807532, 2014, p. 695-705.

Research output: Contribution to journalArticle

Fifer, Matthew S. ; Hotson, Guy ; Wester, Brock A. ; McMullen, David P. ; Wang, Yujing ; Johannes, Matthew S. ; Katyal, Kapil D. ; Helder, John B. ; Para, Matthew P. ; Vogelstein, R. Jacob ; Anderson, William S ; Thakor, Nitish V ; Crone, Nathan E. / Simultaneous neural control of simple reaching and grasping with the modular prosthetic limb using intracranial EEG. In: IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2014 ; Vol. 22, No. 3. pp. 695-705.
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