Brain-computer interface with rapid serial multimodal presentation using artificial facial images and voice
Brain-computer interface with rapid serial multimodal presentation using artificial facial images and voice
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DOI：
10.1016/j.compbiomed.2021.104685
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发表时间：
2021-02
影响因子：
7.7
通讯作者：
Akinari Onishi
中科院分区：
文献类型：
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作者：
Akinari Onishi
多模态刺激引起的脑电图（EEG）信号可以驱动脑机接口（BCI），研究表明，视觉和听觉刺激可以同时用于提高BCI性能。然而，没有研究调查的影响，多模态刺激在快速串行视觉呈现（RSVP）脑机接口。本研究提出了一种快速串行多模态呈现（RSMP）脑机接口，结合人工面部图像和人工语音刺激。为了阐明视听刺激对RSMP BCI的影响，分别应用加扰图像和掩蔽声音代替视觉和听觉刺激。研究结果表明，视听刺激提高了RSMP BCI的性能，Pz的P300有助于分类准确性。脑机接口的在线准确率达到85.7 ± 11.5%。总之，这些发现可能有助于开发更好的凝视独立BCI系统。
Electroencephalography (EEG) signals elicited by multimodal stimuli can drive brain-computer interfaces (BCIs), and research has demonstrated that visual and auditory stimuli can be employed simultaneously to improve BCI performance. However, no studies have investigated the effect of multimodal stimuli in rapid serial visual presentation (RSVP) BCIs. The present study proposed a rapid serial multimodal presentation (RSMP) BCI that incorporates artificial facial images and artificial voice stimuli. To clarify the effect of audiovisual stimuli on the RSMP BCI, scrambled images and masked sounds were applied instead of visual and auditory stimuli, respectively. The findings indicated that the audiovisual stimuli improved performance of the RSMP BCI, and that P300 at Pz contributed to classification accuracy. Online accuracy of the BCI reached 85.7 ± 11.5 %. Taken together, these findings may aid in the development of better gaze-independent BCI systems.