An EEG Method to Identify Image Preference With an Explicit/Implicit Task Brain-Computer Interface

Abstract

Accurately determining an individual's preference for images remains a major challenge in the field of emotional research. This study proposes a novel paradigm for identifying individual image preferences using electroencephalography (EEG) signals and brain-computer interface (BCI). The paradigm involves both explicit and implicit tasks, where participants perform a typical event-related potential-based brain-computer interface(ERP-BCI) operation and their subjective image preferences are identified, respectively. Two experiments with a total of 27 participants demonstrate that event-related potential (ERP) signals during explicit BCI tasks are significantly influenced by target image preferences, enabling high-accuracy image preference recognition. Online experiments selecting positive and negative preference images from a candidate pool show top-1 accuracy approaching 100% and top-3 accuracy exceeding 90%. These results indicate the effectiveness of the proposed EEG-based image preference recognition paradigm, laying the groundwork for preference analysis applications.