Isaksen Jonas, Mohebbi Ali, Puthusserypady Sadasivan
Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:1512-1515. doi: 10.1109/EMBC.2016.7590997.
In this study, a c-VEP based BCI system was developed to run on three distinctive pseudorandom sequences, namely the m-code, the Gold-code, and the Barker-code. The Visual Evoked Potentials (VEPs) were provoked using these codes. In the online session, subjects controlled a LEGO Mindstorms robot around a fixed track. Choosing the optimal code proved a significant increase in accuracy (p<;0.00001) over the average performance. No single code proved significantly more accurate than the others (p=0.81), suggesting that the term "optimal code" is subject-dependent. However, the Gold-code was significantly faster than both alternatives (p=0.006, p=0.016). When choosing the optimal code for accuracy, no significant decrease in Time Per Identification (TPI) was found (p=0.67). Thus, when creating an online c-VEP based BCI system, it is recommended to use multiple random sequences for increased performance.
在本研究中，开发了一种基于c-VEP的脑机接口系统，使其能在三种不同的伪随机序列上运行，即m码、Gold码和巴克码。使用这些编码诱发视觉诱发电位（VEP）。在在线实验环节，受试者控制一个乐高Mindstorms机器人在固定轨道上运行。结果表明，选择最优编码相比于平均表现，准确率有显著提高（p<0.00001）。没有一种编码被证明比其他编码显著更准确（p = 0.81），这表明“最优编码”是依赖于受试者的。然而，Gold码比其他两种编码明显更快（p = 0.006，p = 0.016）。在选择用于提高准确率的最优编码时，未发现每次识别时间（TPI）有显著下降（p = 0.67）。因此，在创建基于在线c-VEP的脑机接口系统时，建议使用多个随机序列以提高性能。
