论文标题

触觉感知和对自然纹理的注意力的分类

Classification of Tactile Perception and Attention on Natural Textures from EEG Signals

论文作者

Kim, Myoung-Ki, Cho, Jeong-Hyun, Jeong, Ji-Hoon

论文摘要

大脑计算机界面允许失去运动技能的人基于脑电图控制机器人四肢。大多数BCI仅由视觉反馈来指导,并且没有体感反馈,这是正常运动行为的重要组成部分。接触感是一种非常关键的感官方式,尤其是在对象识别和操纵中。操纵对象时,大脑会使用有关对象的触觉特性的经验信息。此外,主要的体感皮层不仅参与处理我们体内的触摸感,而且还响应与其他人或无生命物体的可见接触。根据这些发现,我们进行了初步实验,以确认一种称为触摸图像的新型范式的可能性。对四个对象进行了触觉图像实验,通过神经生理学分析,与实际触觉意义的脑波进行了比较分析。此外,通过基本的机器学习算法证实了高分类性能。

Brain-computer interface allows people who have lost their motor skills to control robot limbs based on electroencephalography. Most BCIs are guided only by visual feedback and do not have somatosensory feedback, which is an important component of normal motor behavior. The sense of touch is a very crucial sensory modality, especially in object recognition and manipulation. When manipulating an object, the brain uses empirical information about the tactile properties of the object. In addition, the primary somatosensory cortex is not only involved in processing the sense of touch in our body but also responds to visible contact with other people or inanimate objects. Based on these findings, we conducted a preliminary experiment to confirm the possibility of a novel paradigm called touch imagery. A haptic imagery experiment was conducted on four objects, and through neurophysiological analysis, a comparison analysis was performed with the brain waves of the actual tactile sense. Also, high classification performance was confirmed through the basic machine learning algorithm.

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