Channel selection for brain signal classification by penalized automatic relevance determination
Channel selection for brain signal classification by penalized automatic relevance determination
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DOI：
10.1109/apsipa.2015.7415427
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发表时间：
2015-12
期刊：
影响因子：
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通讯作者：
Reo Togashi;Y. Washizawa
中科院分区：
文献类型：
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作者：
Reo Togashi;Y. Washizawa
在脑机接口（BCI）中选择或减少信道对降低成本和提高广义精度具有重要意义。报道了一种基于P300的脑机接口信道选择方法。在本文中，我们应用了作为ARD扩展的惩罚ARD (PARD)，并与GARD在我们的听觉脑机接口中进行了比较。实验结果表明，与GARD相比，PARD提供了更多的稀疏解，而其分类精度与GARD几乎相同。
Channel selection or reduction in Brain computer interface (BCI) is important to reduce the cost and improve the generalized accuracy. A channel selection method using group automatic relevance determination (GARD) for P300 based BCI has been reported. In this paper, we apply the penalized ARD (PARD) which is an extension of ARD, and compare with GARD in our auditory BCI. Experimental results show that PARD provides more sparse solution than GARD while PARD shows almost the same classification accuracy as GARD.