A high-performance brain-computer interface

被引:477
作者
Santhanam, Gopal
Ryu, Stephen I.
Yu, Byron M.
Afshar, Afsheen
Shenoy, Krishna V.
机构
[1] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
[2] Stanford Univ, Sch Med, Dept Neurosurg, Stanford, CA 94305 USA
[3] Stanford Univ, Sch Med, Med Scientist Training Program, Stanford, CA 94305 USA
[4] Stanford Univ, Sch Med, Neurosci Program, Stanford, CA 94305 USA
关键词
D O I
10.1038/nature04968
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Recent studies have demonstrated that monkeys(1-4) and humans(5-9) can use signals from the brain to guide computer cursors. Brain computer interfaces (BCIs) may one day assist patients suffering from neurological injury or disease, but relatively low system performance remains a major obstacle. In fact, the speed and accuracy with which keys can be selected using BCIs is still far lower than for systems relying on eye movements. This is true whether BCIs use recordings from populations of individual neurons using invasive electrode techniques(1-5,7,8) or electroencephalogram recordings using less-(6) or non-invasive(9) techniques. Here we present the design and demonstration, using electrode arrays implanted in monkey dorsal premotor cortex, of a manyfold higher performance BCI than previously reported(9,10). These results indicate that a fast and accurate key selection system, capable of operating with a range of keyboard sizes, is possible ( up to 6.5 bits per second, or similar to 15 words per minute, with 96 electrodes). The highest information throughput is achieved with unprecedentedly brief neural recordings, even as recording quality degrades over time. These performance results and their implications for system design should substantially increase the clinical viability of BCIs in humans.
引用
收藏
页码:195 / 198
页数:4
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