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System for optimal rapid serial visual presentation (RSVP) from user-specific neural brain signals

机译:用于根据用户特定的神经脑信号进行最佳快速串行视觉呈现(RSVP)的系统

摘要

Described is a system for optimizing rapid serial visual presentation (RSVP). A similarity metric is computed for RSVP images, and the images are sequenced according to the similarity metrics. The sequenced images are presented to a user, and neural signals are received to detect a P300 signal. A neural score for each image is computed, and the system is optimized to model the neural scores. The images are resequenced according a predictive model to output a sequence prediction which does not cause a false P300 signal. Additionally, the present invention describes computing a set of motion surprise maps from image chips. The image chips are labeled as static or moving and prepared into RSVP datasets. Neural signals are recorded in response to the RSVP datasets, and an EEG score is computed from the neural signals. Each image chip is then classified as containing or not containing an item of interest.
机译:描述了一种用于优化快速串行视觉呈现(RSVP)的系统。计算RSVP图像的相似性度量,并根据相似性度量对图像进行排序。序列化的图像呈现给用户,并接收神经信号以检测P300信号。计算每个图像的神经分数,并对系统进行优化以对神经分数建模。根据预测模型对图像重新排序,以输出不会引起错误P300信号的序列预测。另外,本发明描述了从图像芯片计算一组运动惊喜图。图像芯片被标记为静态或移动,并准备成RSVP数据集。响应RSVP数据集记录神经信号,并根据神经信号计算EEG分数。然后,将每个图像芯片分类为包含或不包含感兴趣的项目。

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