Evaluating true BCI communication rate through mutual information and language models.
Evaluating true BCI communication rate through mutual information and language models.
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DOI：
10.1371/journal.pone.0078432
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Pouratian N
中科院分区：
文献类型：
--
作者：
Speier W;Arnold C;Pouratian N
脑机接口（BCI）系统是一种很有前途的手段，恢复通信的患者患有“闭锁”综合征。提高系统性能的研究主要集中在克服脑电图（EEG）记录的低信噪比的方法上。然而，由于评估指标和假设的阵列，文献和方法很难比较，包括：1）所有字符的概率相等，2）字符选择是无记忆的，3）错误完全随机发生。更准确地反映BCI语言输出中包含的信息量的评估指标的标准化对于取得进展至关重要。我们提出了一个基于互信息的度量，结合先验信息和系统误差模型。在一项研究中使用的系统的参数进行了重新优化，表明在优化中使用的度量显着影响所选择的参数值和所得到的系统性能。然后，使用不同的指标，包括以前使用的BCI文献和新倡导的指标，11 BCI通信研究的结果进行了评估。六项研究的结果因评估所用的指标而异，拟议的指标产生的结果与其中两项研究最初发表的结果不同。标准化指标以准确反映信息传输速率对于正确评估和比较BCI通信系统并以公正的方式推进该领域至关重要。
Brain-computer interface (BCI) systems are a promising means for restoring communication to patients suffering from “locked-in” syndrome. Research to improve system performance primarily focuses on means to overcome the low signal to noise ratio of electroencephalogric (EEG) recordings. However, the literature and methods are difficult to compare due to the array of evaluation metrics and assumptions underlying them, including that: 1) all characters are equally probable, 2) character selection is memoryless, and 3) errors occur completely at random. The standardization of evaluation metrics that more accurately reflect the amount of information contained in BCI language output is critical to make progress. We present a mutual information-based metric that incorporates prior information and a model of systematic errors. The parameters of a system used in one study were re-optimized, showing that the metric used in optimization significantly affects the parameter values chosen and the resulting system performance. The results of 11 BCI communication studies were then evaluated using different metrics, including those previously used in BCI literature and the newly advocated metric. Six studies' results varied based on the metric used for evaluation and the proposed metric produced results that differed from those originally published in two of the studies. Standardizing metrics to accurately reflect the rate of information transmission is critical to properly evaluate and compare BCI communication systems and advance the field in an unbiased manner.
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影响因子：
4
作者：
Speier W;Arnold C;Lu J;Taira RK;Pouratian N
通讯作者：
Pouratian N
DOI：
10.1016/j.clinph.2010.01.030
发表时间：
2010-07
期刊：
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
影响因子：
--
作者：
Townsend G;LaPallo BK;Boulay CB;Krusienski DJ;Frye GE;Hauser CK;Schwartz NE;Vaughan TM;Wolpaw JR;Sellers EW
通讯作者：
Sellers EW
DOI：
10.1016/j.clinph.2012.08.002
发表时间：
2013-02
期刊：
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
影响因子：
--
作者：
Lu J;Speier W;Hu X;Pouratian N
通讯作者：
Pouratian N
DOI：
10.1109/tnsre.2004.841878
发表时间：
2005-03-01
影响因子：
4.9
作者：
Serby, H;Yom-Tov, E;Inbar, GF
通讯作者：
Inbar, GF
影响因子：
3.7
作者：
Furdea, A.;Halder, S.;Kuebler, A.
通讯作者：
Kuebler, A.