基于脑电图（EEG）的通信：人类中的EEG控制与系统性能
Electroencephalographic(EEG)-based communication: EEG control versus system performance in humans.
作者信息
Sheikh Hesham, McFarland Dennis J, Sarnacki William A, Wolpaw Jonathan R
机构信息
Laboratory of Nervous System Disorders, Wadsworth Center, New York State Department of Health and State University of New York, Empire State Plaza, Albany, NY 12201, USA.
出版信息
Neurosci Lett. 2003 Jul 17;345(2):89-92. doi: 10.1016/s0304-3940(03)00470-1.
People can learn to control electroencephalographic (EEG) sensorimotor rhythm amplitude so as to move a cursor to select among choices on a computer screen. We explored the dependence of system performance on EEG control. Users moved the cursor to reach a target at one of four possible locations. EEG control was measured as the correlation (r(2)) between rhythm amplitude and target location. Performance was measured as accuracy (% of targets hit) and as information transfer rate (bits/trial). The relationship between EEG control and accuracy can be approximated by a linear function that is constant for all users. The results facilitate offline predictions of the effects on performance of using different EEG features or combinations of features to control cursor movement.
人们可以学会控制脑电图（EEG）的感觉运动节律幅度，以便移动光标在电脑屏幕上的选项中进行选择。我们探究了系统性能对脑电图控制的依赖性。用户移动光标以到达四个可能位置之一的目标。脑电图控制通过节律幅度与目标位置之间的相关性（r(2)）来衡量。性能通过准确率（命中目标的百分比）和信息传输率（比特/试验）来衡量。脑电图控制与准确率之间的关系可以用一个对所有用户都恒定的线性函数来近似。这些结果有助于离线预测使用不同脑电图特征或特征组合来控制光标移动对性能的影响。
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