Visual object detection system based on augmented reality and steady-state visual evoked potential

本研究探讨了一种基于增强现实（AR）环境和稳态视觉诱发电位（SSVEP）的脑机接口（BCI）系统，用于在真实场景下通过视觉注视完成对现实物品的选取任务。该系统结合了目标检测技术和AR技术，在真实物体上附加视觉增强效果，从而给予用户视觉刺激诱发相关脑电信号，再利用SSVEP技术解析脑电信号，完成对用户关注物体的识别。此外，本文采用了基于自适应动态时间窗的滤波器组典型相关分析算法实现对受试者脑电信号的快速解析。实验结果表明，该系统可以有效地识别解析SSVEP信号，对用户视觉目标的识别平均准确率达到了90.6%。该系统拓展了SSVEP信号在现实生活场景中的应用，在帮助行动不便和肢体功能受损患者进行物品选取任务上具备可行性和有效性。.; This study investigates a brain-computer interface (BCI) system based on an augmented reality (AR) environment and steady-state visual evoked potentials (SSVEP). The system is designed to facilitate the selection of real-world objects through visual gaze in real-life scenarios. By integrating object detection technology and AR technology, the system augmented real objects with visual enhancements, providing users with visual stimuli that induced corresponding brain signals. SSVEP technology was then utilized to interpret these brain signals and identify the objects that users focused on. Additionally, an adaptive dynamic time-window-based filter bank canonical correlation analysis was employed to rapidly parse the subjects' brain signals. Experimental results indicated that the system could effectively recognize SSVEP signals, achieving an average accuracy rate of 90.6% in visual target identification. This system extends the application of SSVEP signals to real-life scenarios, demonstrating feasibility and efficacy in assisting individuals with mobility impairments and physical disabilities in object selection tasks.