论文标题
迈向神经素：用于解码直观触觉的脑部计算机界面
Towards Neurohaptics: Brain-Computer Interfaces for Decoding Intuitive Sense of Touch
论文作者
论文摘要
非侵入性脑部计算机界面（BCI）广泛用于识别用户的意图。特别是，与触觉和感觉解码有关的BCI可能会对许多工业领域（例如制造高级触摸显示器，控制机器人设备以及更身临其境的虚拟现实或增强现实）提供各种影响。在本文中，我们介绍了称为NeuroHaptics的基于触觉和感官感知的BCI系统。这是一项初步研究，用于使用实际的触摸和触摸图像范式的各种场景。我们设计了一个新型的实验环境和一种可以在接触指定材料下获取大脑信号的设备，以产生自然的感觉和纹理感觉。通过实验，我们相对于四个不同的纹理对象收集了脑电图（EEG）信号。招募了七个主题进行实验，并使用机器学习和深度学习方法评估了分类表现。因此，我们可以确认对EEG信号进行实际触摸和触摸图像以开发实用的神经运动剂的可行性。
Noninvasive brain-computer interface (BCI) is widely used to recognize users' intentions. Especially, BCI related to tactile and sensation decoding could provide various effects on many industrial fields such as manufacturing advanced touch displays, controlling robotic devices, and more immersive virtual reality or augmented reality. In this paper, we introduce haptic and sensory perception-based BCI systems called neurohaptics. It is a preliminary study for a variety of scenarios using actual touch and touch imagery paradigms. We designed a novel experimental environment and a device that could acquire brain signals under touching designated materials to generate natural touch and texture sensations. Through the experiment, we collected the electroencephalogram (EEG) signals with respect to four different texture objects. Seven subjects were recruited for the experiment and evaluated classification performances using machine learning and deep learning approaches. Hence, we could confirm the feasibility of decoding actual touch and touch imagery on EEG signals to develop practical neurohaptics.
