The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia
Open accessAbstract
Computer-mediated connections between human motor cortical neurons and assistive devices promise to improve or restore lost function in people with paralysis. Recently, a pilot clinical study of an intracortical neural interface system demonstrated that a tetraplegic human was able to obtain continuous two-dimensional control of a computer cursor using neural activity recorded from his motor cortex. This control, however, was not sufficiently accurate for reliable use in many common computer control tasks. Here, we studied several central design choices for such a system including the kinematic representation for cursor movement, the decoding method that translates neuronal ensemble spiking activity into a control signal and the cursor control task used during training for optimizing the parameters of the decoding method. In two tetraplegic participants, we found that controlling a cursor's velocity resulted in more accurate closed-loop control than controlling its position directly and that cursor velocity control was achieved more rapidly than position control. Control quality was further improved over conventional linear filters by using a probabilistic method, the Kalman filter, to decode human motor cortical activity. Performance assessment based on standard metrics used for the evaluation of a wide range of pointing devices demonstrated significantly improved cursor control with velocity rather than position decoding.
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Cites
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Cited by
Reach and grasp by people with tetraplegia using a neurally controlled robotic arm
Hochberg, L. R., Bacher, D., Jarosiewicz, B., Masse, N. Y., Simeral, J. D., Vogel, J., Haddadin, S., Liu, J., Cash, S. S., van der Smagt, P., et al. (2012) · Nature · doi:10.1038/nature11076 · Cited by 2,719
Self-citationDecoding motor imagery from the posterior parietal cortex of a tetraplegic human
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Failure mode analysis of silicon-based intracortical microelectrode arrays in non-human primates
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Self-citationA high-performance neural prosthesis enabled by control algorithm design
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Simeral, J. D., Kim, S.-P., Black, M. J., Donoghue, J. P., & Hochberg, L. R. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/2/025027 · Cited by 496
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Metadata
- Authors
- Kim, S.-P., Simeral, J. D., Hochberg, L. R., Donoghue, J. P., & Black, M. J.
- Venue
- Journal of Neural Engineering
- Publisher
- IOP Publishing
- Published
- 2008-11-18
- Volume
- 5
- Issue
- 4
- Pages
- 455-476
- ISSN
- 1741-2552 (ISSN-L)
- 1741-2560
- OpenAlex
- W2009664245
- Cited by
- 397
- References
- 47
- FWCI
- 11.20
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Kim, S.-P., Simeral, J. D., Hochberg, L. R., Donoghue, J. P., & Black, M. J. (2008). Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia. Journal of Neural Engineering. https://doi.org/10.1088/1741-2560/5/4/010
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