five

Dataset of binocularly coded steady-state visual evoked potentials recorded with an augmented reality headset

收藏
DataCite Commons2025-07-04 更新2024-08-26 收录
下载链接:
https://figshare.com/articles/dataset/Multi-frequency_steady-state_visual_evoked_potential_dataset_in_the_augmented_reality_environment_using_a_portable_stimulation_device_epoch_data_/26764735
下载链接
链接失效反馈
官方服务:
资源简介:
Steady-state visually evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have shown significant promise for practical applications. The integration of SSVEP-BCIs with head-mounted augmented-reality (AR) displays is expected to foster wearable, portable systems; nevertheless, empirical resources for such configurations are scarce, especially for paradigms employing innovative stimulation paradigms. Here we present a curated SSVEP dataset recorded with a binocular AR headset that independently modulates the visual input to each eye and a lightweight electroencephalography recorder. Beyond the conventional binocular-congruent single-frequency stimulation adopted in AR-SSVEP studies, the dataset systematically explores binocular-incongruent dual-frequency encoding whereby the two lenses render flickers with distinct frequencies and/or phases. We report comparative analyses of SSVEP characteristics and BCI performance under congruent versus incongruent protocols, and delineate the influence of inter-ocular frequency and phase disparities. The results substantiate the feasibility of wearable AR-SSVEP-BCIs and highlight binocular-incongruent dual-frequency stimulation as a compelling strategy for improving target separability. The dataset should accelerate research on portable SSVEP-BCIs, novel encoding schemes, and the neural mechanisms of binocular vision.If you use this dataset for a publication, please cite our corresponding research paper: "Dataset of binocularly coded steady-state visual evoked potentials recorded with an augmented reality headset".

基于稳态视觉诱发电位(Steady-state Visually Evoked Potential,SSVEP)的脑机接口(Brain-Computer Interface,BCI)在实际应用中展现出了可观的应用前景。将SSVEP-BCI与头戴式增强现实(Augmented Reality,AR)显示器相结合,有望构建可穿戴、便携式系统;然而,此类配置的实证研究资源仍较为匮乏,尤其是针对采用创新刺激范式的相关研究。本研究公开了一套经过精心筛选的SSVEP数据集,该数据集由可独立调节双眼视觉输入的双目AR头显与轻量化脑电图(Electroencephalography,EEG)记录仪共同采集得到。相较于AR-SSVEP研究中常用的双眼一致单频刺激范式,本数据集系统探究了双眼不一致双频编码方案:即两个显示透镜分别呈现具有不同频率和/或相位的闪烁刺激。本研究针对一致与不一致刺激范式下的SSVEP特征与BCI性能开展了对比分析,并阐明了双眼间频率与相位差异所带来的影响。研究结果证实了可穿戴AR-SSVEP-BCI的可行性,并凸显出双眼不一致双频刺激作为提升目标可区分性的有效策略的应用价值。本数据集将有助于推动便携式SSVEP-BCI、新型编码方案以及双眼视觉神经机制相关领域的研究进展。若您在学术出版物中使用本数据集,请引用相关研究论文:"Dataset of binocularly coded steady-state visual evoked potentials recorded with an augmented reality headset"。
提供机构:
figshare
创建时间:
2024-08-17
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作