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首页> 美国卫生研究院文献>Computational and Mathematical Methods in Medicine >Sequential Probability Ratio Testing with Power Projective Base Method Improves Decision-Making for BCI
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Sequential Probability Ratio Testing with Power Projective Base Method Improves Decision-Making for BCI

机译：幂投影基数法的顺序概率比率测试改善了BCI的决策能力

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摘要

Obtaining a fast and reliable decision is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this study, the EEG signals were firstly analyzed with a power projective base method. Then we were applied a decision-making model, the sequential probability ratio testing (SPRT), for single-trial classification of motor imagery movement events. The unique strength of this proposed classification method lies in its accumulative process, which increases the discriminative power as more and more evidence is observed over time. The properties of the method were illustrated on thirteen subjects' recordings from three datasets. Results showed that our proposed power projective method outperformed two benchmark methods for every subject. Moreover, with sequential classifier, the accuracies across subjects were significantly higher than that with nonsequential ones. The average maximum accuracy of the SPRT method was 84.1%, as compared with 82.3% accuracy for the sequential Bayesian (SB) method. The proposed SPRT method provides an explicit relationship between stopping time, thresholds, and error, which is important for balancing the time-accuracy trade-off. These results suggest SPRT would be useful in speeding up decision-making while trading off errors in BCI.
机译：获得快速可靠的决策是脑机接口（BCI）的重要问题，尤其是在实际的实时应用（例如轮椅或神经假体控制）中。在这项研究中，脑电信号首先用功率投影基础法进行分析。然后，我们将决策模型（顺序概率比检验（SPRT））应用于运动图像运动事件的单次试验分类。提出的分类方法的独特优势在于其累积过程，随着时间的推移越来越多的证据被发现，这增加了判别力。在来自三个数据集的十三名受试者的记录中说明了该方法的性质。结果表明，对于每个主题，我们提出的幂投影方法均优于两种基准方法。此外，使用顺序分类器，跨主题的准确性显着高于非顺序分类器。 SPRT方法的平均最大准确性为84.1％，而顺序贝叶斯（SB）方法的平均最大准确性为82.3％。提出的SPRT方法在停止时间，阈值和误差之间提供了明确的关系，这对于平衡时间精度的权衡非常重要。这些结果表明，SPRT将有助于加速决策制定，同时权衡BCI中的错误。

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