The brain-computer interface (BCI) plays an important role in assisting patients with amyotrophic lateral sclerosis (ALS) to enable them to participate in communication and entertainment. In this study, a novel channel projection-based canonical correlation analysis (CP-CCA) target identification method for steady-state visual evoked potential- (SSVEP-) based BCI system was proposed. The single-channel electroencephalography (EEG) signals of multiple trials were recorded when the subject is under the same stimulus frequency. The CCAs between single-channel EEG signals of multiple trials and sine-cosine reference signals were obtained. Then, the optimal reference signal of each channel was utilized to estimate the test EEG signal. To validate the proposed method, we acquired the training dataset with two testing conditions including the optimal time window length and the number of the trial of training data. The offline experiments conducted a comparison of the proposed method with the traditional canonical correlation analysis (CCA) and power spectrum density analysis (PSDA) method using a 5-class SSVEP dataset that was recorded from 10 subjects. Based on the training dataset, the online 3D-helicopter control experiment was carried out. The offline experimental results showed that the proposed method outperformed the CCA and the PSDA methods in terms of classification accuracy and information transfer rate (ITR). Furthermore, the online experiments of 3-DOF helicopter control achieved an average accuracy of 87.94 ± 5.93% with an ITR of 21.07 ± 4.42 bit/min.

中文翻译：

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基于SSVEP的四旋翼直升机控制BCI系统基于通道投影的CCA目标识别方法。

脑机接口（BCI）在协助患有肌萎缩性侧索硬化症（ALS）的患者中发挥重要作用，使他们能够参与交流和娱乐活动。在这项研究中，提出了一种新的基于通道投影的典型相关分析（CP-CCA）目标识别方法，用于基于稳态视觉诱发电位（B2S）的BCI系统。当受试者处于相同的刺激频率下时，记录了多个试验的单通道脑电图（EEG）信号。获得了多次试验的单通道EEG信号与正弦余弦参考信号之间的CCA。然后，利用每个通道的最佳参考信号来估计测试脑电信号。为了验证提出的方法，我们获得了具有两个测试条件的训练数据集，其中包括最佳时间窗口长度和训练数据的试验次数。离线实验使用从10名受试者中记录的5类SSVEP数据集，将建议的方法与传统的规范相关分析（CCA）和功率谱密度分析（PSDA）方法进行了比较。基于训练数据集，进行了在线3D直升机控制实验。离线实验结果表明，该方法在分类准确度和信息传递率（ITR）方面均优于CCA和PSDA方法。此外，在线进行3自由度直升机控制实验的平均准确度为87.94±5.93％，ITR为21.07±4.42 bit / min。