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Vigilance state fluctuations and performance using brain-computer interface for communication

机译:使用人机界面进行通信的警惕状态波动和性能

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The effect of fatigue and drowsiness on brain-computer interface (BCI) performance was evaluated. Twenty healthy participants performed a standardized 11-min calibration of a Rapid Serial Visual Presentation BCI system 5 times over 2 h. For each calibration, BCI performance was evaluated using area under the receiver operating characteristic curve (AUC). Self-rated measures were obtained following each calibration including the Karolinska Sleepiness Scale and a standardized boredom scale. Physiological measures were obtained during each calibration including P300 amplitude, theta power, alpha power, median power frequency, and eye-blink rate. There was a significant decrease in AUC over the five sessions. This was paralleled by increases in self-rated sleepiness and boredom and decreases in P300 amplitude. Alpha power, median power frequency, and eye-blink rate also increased but more modestly. AUC changes were only partly explained by changes in P300 amplitude. There was a decrease in BCI performance over time that related to increases in sleepiness and boredom. This worsened performance was only partly explained by decreases in P300 amplitude. Thus, drowsiness and boredom have a negative impact on BCI performance. Increased BCI performance may be possible by developing physiological measures to provide feedback to the user or to adapt the classifier to state.
机译:评估了疲劳和嗜睡对脑机接口(BCI)性能的影响。二十名健康参与者在2小时内对快速连续视觉演示BCI系统进行了11分钟的标准化校准5次。对于每次校准,使用接收器工作特性曲线(AUC)下的面积评估BCI性能。每次校准后均获得了自评量度,包括卡罗林斯卡困倦量表和标准化无聊量表。在每次校准过程中获得了生理指标,包括P300幅度,θ功率,α功率,中值功率频率和眨眼率。在五个会议中,AUC显着减少。与此相对应的是,自我评估的嗜睡和乏味的增加以及P300幅度的降低。 Alpha功率,中值功率频率和眨眼率也有所增加,但幅度较小。 P300振幅的变化仅部分解释了AUC的变化。随着时间的流逝,BCI表现下降,这与嗜睡和无聊感增加有关。这种恶化的性能只能部分地由P300幅度的减小来解释。因此,嗜睡和无聊对BCI表现有负面影响。通过开发生理措施为用户提供反馈或使分类器适应状态,可能会提高BCI性能。

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