brain-computer interfaces; calibration; electroencephalography; feature extraction; medical signal processing; signal classification; visual evoked potentials; PLS-based stimulus frequency recognition model; SSVEP detection; SSVEP feature extraction; SSVEP-based BCI systems; calibration times; classification accuracy; information transfer rates; partial least squares-based stimulus frequency recognition model; steady-state visual evoked potential based brain-computer interfaces; steady-state visual evoked potential detection; Accuracy; Brain modeling; Correlation; Electroencephalography; Feature extraction; Vectors; Visualization; Brain-computer interface (BCI); canonical correlation analysis (CCA); least absolute shrinkage and selection operator (LASSO); partial least squares (PLS); steady-state visual evoked potential (SSVEP);
机译:刺激图案,色彩组合和闪烁频率对稳态视觉诱发电位形貌的影响
机译:使用刺激表示的时间插值以任意频率驱动稳态视觉诱发电位
机译:结合规范相关分析和无限参考进行稳态视觉诱发电位记录的频率识别:与周期图方法的比较
机译:基于稳态视觉诱发电位检测的基于局部最小二乘刺激频率识别模型
机译:稳态视觉诱发电位:改进实验设计并确定变化的来源。
机译:使用刺激表示的时间插值以任意频率驱动稳态视觉诱发电位
机译:使用刺激表示的时间插值以任意频率驱动稳态视觉诱发电位
机译:在调节视觉刺激期间听觉和视觉诱发电位到不相关的刺激