IEEE Trans Neural Syst Rehabil Eng. 2020 Jan;28(1):113-122. doi: 10.1109/TNSRE.2019.2953975. Epub 2019 Nov 18.
Rapid serial visual presentation (RSVP) based brain-computer interfaces (BCIs) can detect target images among a continuous stream of rapidly presented images, by classifying a viewer's event related potentials (ERPs) associated with the target and non-targets images. Whilst the majority of RSVP-BCI studies to date have concentrated on the identification of a single type of image, namely pictures, here we study the capability of RSVP-BCI to detect three different target image types: pictures, numbers and words. The impact of presentation duration (speed) i.e., 100-200ms (5-10Hz), 200-300ms (3.3-5Hz) or 300-400ms (2.5-3.3Hz), is also investigated. 2-way repeated measure ANOVA on accuracies of detecting targets from non-target stimuli (ratio 1:9) measured via area under the receiver operator characteristics curve (AUC) for N=15 subjects revealed a significant effect of factor Stimulus-Type (pictures, numbers, words) (F (2,28) = 7.243, p = 0.003 ) and for Stimulus-Duration (F (2,28) = 5.591, p = 0.011). Furthermore, there is an interaction between stimulus type and duration: F (4,56) = 4.419, p = 0.004 ). The results indicate that when designing RSVP-BCI paradigms, the content of the images and the rate at which images are presented impact on the accuracy of detection and hence these parameters are key experimental variables in protocol design and applications, which apply RSVP for multimodal image datasets.
快速序列视觉呈现 (RSVP) 脑机接口 (BCI) 可以通过对与目标和非目标图像相关的观察者事件相关电位 (ERP) 进行分类,从连续快速呈现的图像流中检测目标图像。虽然迄今为止,大多数 RSVP-BCI 研究都集中在识别单一类型的图像,即图片,但在这里,我们研究 RSVP-BCI 检测三种不同目标图像类型的能力:图片、数字和文字。还研究了呈现持续时间(速度)的影响,即 100-200ms(5-10Hz)、200-300ms(3.3-5Hz)或 300-400ms(2.5-3.3Hz)。通过接收者操作特征曲线下面积 (AUC) 测量的来自非目标刺激的目标检测准确性的 2 向重复测量方差分析,对于 N=15 个受试者,发现刺激类型(图片、数字、文字)的因素(F (2,28) = 7.243,p = 0.003)和刺激持续时间(F (2,28) = 5.591,p = 0.011)有显著影响。此外,刺激类型和持续时间之间存在交互作用:F (4,56) = 4.419,p = 0.004)。结果表明,在设计 RSVP-BCI 范式时,图像的内容和呈现图像的速度会影响检测的准确性,因此这些参数是协议设计和应用中的关键实验变量,适用于 RSVP 多模态图像数据集。