Rubow Colin, Tsai Chia-Hsuan, Brewer Eric, Mattson Connor, Brown Daniel S, Zhang Haohan
Department of Mechanical Engineering, University of Utah, Salt Lake City, 84112, USA.
Robotics Center, University of Utah, Salt Lake City, 84112, USA.
Sci Data. 2024 Dec 5;11(1):1328. doi: 10.1038/s41597-024-04184-1.
We describe a multimodal dataset of paired head and eye movements acquired in controlled virtual reality environments. Our dataset includes head and eye movement for n = 25 participants who interacted with four different virtual reality environments that required coordinated head and eye behaviors. Our data collection involved two visual tracking tasks and two visual searching tasks. Each participant performed each task three times, resulting in approximately 1080 seconds of paired head and eye movement and 129,611 data samples of paired head and eye rotations per participant. This dataset enables research into predictive models of intended head movement conditioned on gaze for augmented and virtual reality experiences, as well as assistive devices like powered exoskeletons for individuals with head-neck mobility limitations. This dataset also allows biobehavioral and mechanism studies of the variability in head and eye movement across different participants and tasks. The virtual environment developed for this data collection is open sourced and thus available for others to perform their own data collection and modify the environment.
我们描述了一个在受控虚拟现实环境中获取的头部和眼睛运动配对的多模态数据集。我们的数据集包括n = 25名参与者的头部和眼睛运动，这些参与者与四个需要协调头部和眼睛行为的不同虚拟现实环境进行了交互。我们的数据收集涉及两项视觉跟踪任务和两项视觉搜索任务。每个参与者对每项任务执行三次，每位参与者产生了大约1080秒的头部和眼睛运动配对以及129611个头部和眼睛旋转配对的数据样本。该数据集有助于研究基于注视的预期头部运动预测模型，用于增强现实和虚拟现实体验，以及为头部颈部活动受限的个体提供诸如动力外骨骼等辅助设备。该数据集还允许对不同参与者和任务中头部和眼睛运动的变异性进行生物行为和机制研究。为此次数据收集开发的虚拟环境是开源的，因此可供其他人进行自己的数据收集并修改该环境。
