论文标题
使用3D虚拟BCI平台进行视觉运动图像分类的新型框架
A Novel Framework for Visual Motion Imagery Classification Using 3D Virtual BCI Platform
论文作者
论文摘要
在这项研究中，使用3D大脑计算机界面（BCI）训练平台来刺激受试者的视觉运动图像和视觉感知。当受试者感知并想象刺激时，我们测量了激活脑区域和α波段功率活性。基于此，分别在视觉刺激会话和视觉运动图像会话中分类4级。结果表明，枕骨区域参与视觉感知和视觉运动图像，并且在视觉运动图像中增加了α波段的功率，并且在视觉运动刺激中减少了。与视觉运动图像和运动图像的性能相比，视觉运动图像的性能高于运动图像。使用一种与REST方法对二进制类别进行分类，并分析大脑激活，以证明与视觉相关的脑波信号有意义，结果很重要。
In this study, 3D brain-computer interface (BCI) training platforms were used to stimulate the subjects for visual motion imagery and visual perception. We measured the activation brain region and alpha-band power activity when the subjects perceived and imagined the stimuli. Based on this, 4-class were classified in visual stimuli session and visual motion imagery session respectively. The results showed that the occipital region is involved in visual perception and visual motion imagery, and alpha-band power is increased in visual motion imagery session and decreased in visual motion stimuli session. Compared with the performance of visual motion imagery and motor imagery, visual motion imagery has higher performance than motor imagery. The binary class was classified using one versus rest approach as well as analysis of brain activation to prove that visual-related brain wave signals are meaningful, and the results were significant.
