Chen Xiaogang, Wang Yijun, Nakanishi Masaki, Gao Xiaorong, Jung Tzyy-Ping, Gao Shangkai
Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China;
Swartz Center for Computational Neuroscience, University of California, San Diego, CA 92093; State Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
Proc Natl Acad Sci U S A. 2015 Nov 3;112(44):E6058-67. doi: 10.1073/pnas.1508080112. Epub 2015 Oct 19.
The past 20 years have witnessed unprecedented progress in brain-computer interfaces (BCIs). However, low communication rates remain key obstacles to BCI-based communication in humans. This study presents an electroencephalogram-based BCI speller that can achieve information transfer rates (ITRs) up to 5.32 bits per second, the highest ITRs reported in BCI spellers using either noninvasive or invasive methods. Based on extremely high consistency of frequency and phase observed between visual flickering signals and the elicited single-trial steady-state visual evoked potentials, this study developed a synchronous modulation and demodulation paradigm to implement the speller. Specifically, this study proposed a new joint frequency-phase modulation method to tag 40 characters with 0.5-s-long flickering signals and developed a user-specific target identification algorithm using individual calibration data. The speller achieved high ITRs in online spelling tasks. This study demonstrates that BCIs can provide a truly naturalistic high-speed communication channel using noninvasively recorded brain activities.
在过去20年里,脑机接口(BCI)取得了前所未有的进展。然而,低通信速率仍然是基于BCI的人类通信的关键障碍。本研究提出了一种基于脑电图的BCI拼写器,其信息传输速率(ITR)可达每秒5.32比特,这是使用非侵入性或侵入性方法的BCI拼写器中报告的最高ITR。基于视觉闪烁信号与诱发的单次试验稳态视觉诱发电位之间观察到的极高频率和相位一致性,本研究开发了一种同步调制和解调范式来实现该拼写器。具体而言,本研究提出了一种新的联合频率-相位调制方法,用0.5秒长的闪烁信号标记40个字符,并使用个体校准数据开发了一种用户特定的目标识别算法。该拼写器在在线拼写任务中实现了高ITR。本研究表明,BCI可以使用非侵入性记录的大脑活动提供一个真正自然主义的高速通信通道。