Asynchronous decoding of grasp aperture from human ECoG during a reach-to-grasp task.

Matthew S. Fifer, Mohsen Mollazadeh, Soumyadipta Acharya, Nitish V Thakor, Nathan E Crone

Research output: Contribution to journalArticle

Abstract

Recent studies in primate neurophysiology have focused on decoding multi-joint kinematics from single unit and local field potential recordings. However, the extent to which these results can be generalized to human subjects is not known. We have recorded simultaneous electrocorticographic (ECoG) and hand kinematics in a human subject performing reach-grasp-hold of objects varying in shape and size. All Spectral features in various gamma bands (30-50 Hz, 70-100 Hz and 100-150 Hz frequency bands) were able to predict the time course of grasp aperture with high correlation (max r = 0.80) using as few as one ECoG feature from a single electrode (max r for single feature = 0.75) in single trials without prior knowledge of task timing. These results suggest that the population activity captured with ECoG contains information about coordinated finger movements that potentially can be exploited to control advanced upper limb neuroprosthetics.

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Hand Strength
Biomechanical Phenomena
Decoding
Kinematics
Neurophysiology
Upper Extremity
Primates
Frequency bands
Fingers
Electrodes
Hand
Joints
Population

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

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title = "Asynchronous decoding of grasp aperture from human ECoG during a reach-to-grasp task.",
abstract = "Recent studies in primate neurophysiology have focused on decoding multi-joint kinematics from single unit and local field potential recordings. However, the extent to which these results can be generalized to human subjects is not known. We have recorded simultaneous electrocorticographic (ECoG) and hand kinematics in a human subject performing reach-grasp-hold of objects varying in shape and size. All Spectral features in various gamma bands (30-50 Hz, 70-100 Hz and 100-150 Hz frequency bands) were able to predict the time course of grasp aperture with high correlation (max r = 0.80) using as few as one ECoG feature from a single electrode (max r for single feature = 0.75) in single trials without prior knowledge of task timing. These results suggest that the population activity captured with ECoG contains information about coordinated finger movements that potentially can be exploited to control advanced upper limb neuroprosthetics.",
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AU - Fifer, Matthew S.

AU - Mollazadeh, Mohsen

AU - Acharya, Soumyadipta

AU - Thakor, Nitish V

AU - Crone, Nathan E

PY - 2011

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