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DC Field | Value | Language |
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dc.citation.endPage | 203 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 193 | - |
dc.citation.title | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING | - |
dc.citation.volume | 19 | - |
dc.contributor.author | Kim, Sung-Phil | - |
dc.contributor.author | Simeral, John D. | - |
dc.contributor.author | Hochberg, Leigh R. | - |
dc.contributor.author | Donoghue, John P. | - |
dc.contributor.author | Friehs, Gerhard M. | - |
dc.contributor.author | Black, Michael J. | - |
dc.date.accessioned | 2023-12-22T06:12:41Z | - |
dc.date.available | 2023-12-22T06:12:41Z | - |
dc.date.created | 2014-12-19 | - |
dc.date.issued | 2011-04 | - |
dc.description.abstract | We present a point-and-click intracortical neural interface system (NIS) that enables humans with tetraplegia to volitionally move a 2-D computer cursor in any desired direction on a computer screen, hold it still, and click on the area of interest. This direct brain-computer interface extracts both discrete (click) and continuous (cursor velocity) signals from a single small population of neurons in human motor cortex. A key component of this system is a multi-state probabilistic decoding algorithm that simultaneously decodes neural spiking activity of a small population of neurons and outputs either a click signal or the velocity of the cursor. The algorithm combines a linear classifier, which determines whether the user is intending to click or move the cursor, with a Kalman filter that translates the neural population activity into cursor velocity. We present a paradigm for training the multi-state decoding algorithm using neural activity observed during imagined actions. Two human participants with tetraplegia (paralysis of the four limbs) performed a closed-loop radial target acquisition task using the point-and-click NIS over multiple sessions. We quantified point-and-click performance using various human-computer interaction measurements for pointing devices. We found that participants could control the cursor motion and click on specified targets with a small error rate (<3% in one participant). This study suggests that signals from a small ensemble of motor cortical neurons (similar to 40) can be used for natural point-and-click 2-D cursor control of a personal computer. | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, v.19, no.2, pp.193 - 203 | - |
dc.identifier.doi | 10.1109/TNSRE.2011.2107750 | - |
dc.identifier.issn | 1534-4320 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/9553 | - |
dc.identifier.wosid | 000289476700009 | - |
dc.language | 영어 | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Point-and-Click Cursor Control With an Intracortical Neural Interface System by Humans With Tetraplegia | - |
dc.type | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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