Hybrid-BCI: Classification of auditory and visual related potentials
Hybrid-BCI: Classification of auditory and visual related potentials
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DOI：
10.1109/scis-isis.2014.7044768
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发表时间：
2014-12
期刊：
影响因子：
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通讯作者：
Gaochao Cui;Qibin Zhao;Jianting Cao;A. Cichocki
中科院分区：
文献类型：
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作者：
Gaochao Cui;Qibin Zhao;Jianting Cao;A. Cichocki
脑机接口(BCI)是一种利用大脑记录的神经生理信号来控制外部机器或计算机的技术，由于技术和机械的发展，在过去的十年里得到了广泛的应用。基于P300的脑机接口，通常被称为P300拼写器，是最成功的范例之一，它在准确率高和训练时间短方面显示出优势。然而，现有的基于P300的脑机接口采用单一类型的外部刺激，如视觉刺激，这限制了它们的应用领域。本文提出了一种基于听觉和视觉同时诱发的多通道P300的混合脑机接口系统。实验结果表明，视觉刺激与多种类型刺激的事件相关电位有显著差异。分类结果证明了我们新的脑-机接口范式的有效性，它在更高的准确率方面优于视觉P300。
The brain computer interface (BCI) is a technology that utilizes neurophysiological signals recorded from brain to control external machines or computers, and has become widespread in the last decade due to technical and mechanical developments. A P300-based BCI, often called P300 speller, is one of the most successful paradigm, which has shown advantages in terms of high accuracy and short training time. However, the existing P300-based BCI employs single type of external stimuli, such as visual stimuli, which limits their application domains. In this paper, we propose a hybrid-BCI system based on multiple modality of P300 evoked by simultaneous auditory and visual stimuli. The experimental results show the significant difference in ERPs between visual stimuli and multiple types of stimuli. The classification results demonstrate the effectiveness of our new BCI paradigm, which outperforms the visual P300 in terms of higher accuracy.