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Study of A Brain-Controlled Switch during Motor Imagery

机译:运动成像中脑控开关的研究

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Most brain-computer interface (BCI) systems use the synchronization paradigm to detect specific brain activities to control external devices. However, for further asynchronous control application it is necessary to provide users with a switch for the system on and off based on spontaneous brain activities. EEG data during motor imagery of right hand movement were collected by 64 electrodes from 4 healthy subjects. After pre-processing the feature related with motion were extracted by common spacial pattern and then by a linear discriminant classifier, the recognition rate of system on/off was about 90% for the offline analysis. Additionally by the maximum redundancy minimum correlation analysis, the most relevant channel was obtained. In the future, the brain-controlled switch may play an important role in brain-computer interface capacities in practical applications.
机译:大多数脑机接口(BCI)系统使用同步范例来检测特定的大脑活动以控制外部设备。但是,对于进一步的异步控制应用程序,有必要根据自然的大脑活动为用户提供打开和关闭系统的开关。右手运动图像中的EEG数据由来自4名健康受试者的64个电极收集。预处理后,通过普通的空间模式提取出与运动相关的特征,然后通过线性判别器进行分类,离线分析系统的开/关识别率约为90%。另外,通过最大冗余最小相关分析,获得了最相关的信道。将来,在实际应用中,脑控开关可能会在脑机接口功能中发挥重要作用。

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