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Optimal Channel Selection for Robust EEG Single-trial Analysis

机译:适用于强大的EEG单试性分析的最佳通道选择

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EEG is an extensively used powerful tool for brain computer interface due to its good temporal resolution and ease of use. The signals captured by multichannel EEG recordings contribute to huge data and often lead to the high computational burden on the computer. An optimal number of electrodes that capture brain signals relevant to the purpose can be used, excluding the redundant and non-contributing electrodes. In this study, we propose an optimization technique on common spatial pattern for channel selection. The implementation of optimization is done as a sequential quadratic programming problem of fast convergence. Extensive experimentation is done to show that the proposed method induces large variance between two tasks of brain action related to sub vocalized speech.
机译:由于其良好的时间分辨率和易用性,EEG是一个广泛使用的强大的脑电电脑界面工具。 MultiShannel EEG录音拍摄的信号有助于大量数据,并且通常会导致计算机上的高计算负担。可以使用捕获与该目的相关的脑信号的最佳电极数,除以冗余和非贡献电极。在这项研究中,我们提出了一种关于通道选择的共同空间模式的优化技术。优化的实现是作为快速收敛的顺序二次编程问题。完成了广泛的实验表明该方法在与子发声语音相关的脑动作的两个任务之间引起了大的差异。

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