Human-Machine Interfaces Laboratory (HMIL), Sharif University of Technology, Tehran, Iran.
Human-Machine Interfaces Laboratory (HMIL), Sharif University of Technology, Tehran, Iran.
Comput Methods Programs Biomed. 2020 Apr;187:105326. doi: 10.1016/j.cmpb.2020.105326. Epub 2020 Jan 22.
Steady-state visual evoked potential (SSVEP) and rapid serial visual presentation (RSVP) are useful methods in the brain-computer interface (BCI) systems. Hybrid BCI systems that combine these two approaches can enhance the proficiency of the P300 spellers.
In this study, a new hybrid RSVP/SSVEP BCI is proposed to increase the classification accuracy and information transfer rate (ITR) as compared with the other RSVP speller paradigms. In this paradigm, RSVP (eliciting a P300 response) and SSVEP stimulations are presented in such a way that the target group of characters is identified by RSVP stimuli, and the target character is recognized by SSVEP stimuli.
The proposed paradigm achieved accuracy of 93.06%, and ITR of 23.41 bit/min averaged across six subjects.
The new hybrid system demonstrates that by using SSVEP stimulation in Triple RSVP speller paradigm, we could enhance the performance of the system as compared with the traditional Triple RSVP paradigm. Our work is the first hybrid paradigm in RSVP spellers that could obtain the higher classification accuracy and information transfer rate in comparison with the previous RSVP spellers.
稳态视觉诱发电位（SSVEP）和快速序列视觉呈现（RSVP）是脑机接口（BCI）系统中有用的方法。结合这两种方法的混合 BCI 系统可以提高 P300 拼写器的熟练程度。
在这项研究中，提出了一种新的混合 RSVP/SSVEP BCI，与其他 RSVP 拼写器范式相比，可提高分类准确性和信息传输率（ITR）。在该范式中，以 RSVP（诱发出 P300 反应）和 SSVEP 刺激的方式呈现，RSVP 刺激可识别目标字符组，而 SSVEP 刺激可识别目标字符。
所提出的范式在 6 名受试者的平均准确率达到 93.06%，信息传输率为 23.41 位/分钟。
新的混合系统表明，通过在三 RSVP 拼写器范式中使用 SSVEP 刺激，与传统的三 RSVP 范式相比，我们可以提高系统的性能。与之前的 RSVP 拼写器相比，我们的工作是第一个能够获得更高分类准确性和信息传输率的 RSVP 混合范式。
