Kim Aram, Zhou Zixuan, Kretch Kari S, Finley James M
Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:4491-4494. doi: 10.1109/EMBC.2017.8037854.
The ability to successfully navigate obstacles in our environment requires integration of visual information about the environment with estimates of our body's state. Previous studies have used partial occlusion of the visual field to explore how information about the body and impending obstacles are integrated to mediate a successful clearance strategy. However, because these manipulations often remove information about both the body and obstacle, it remains to be seen how information about the lower extremities alone is utilized during obstacle crossing. Here, we used an immersive virtual reality (VR) interface to explore how visual feedback of the lower extremities influences obstacle crossing performance. Participants wore a head-mounted display while walking on treadmill and were instructed to step over obstacles in a virtual corridor in four different feedback trials. The trials involved: (1) No visual feedback of the lower extremities, (2) an endpoint-only model, (3) a link-segment model, and (4) a volumetric multi-segment model. We found that the volumetric model improved success rate, placed their trailing foot before crossing and leading foot after crossing more consistently, and placed their leading foot closer to the obstacle after crossing compared to no model. This knowledge is critical for the design of obstacle negotiation tasks in immersive virtual environments as it may provide information about the fidelity necessary to reproduce ecologically valid practice environments.
在我们的环境中成功避开障碍物的能力需要将有关环境的视觉信息与对我们身体状态的估计相结合。先前的研究使用部分视野遮挡来探究关于身体和即将出现的障碍物的信息是如何整合的,以介导成功的通过策略。然而,由于这些操作通常会去除关于身体和障碍物的信息,在穿越障碍物时仅关于下肢的信息是如何被利用的仍有待观察。在这里,我们使用沉浸式虚拟现实(VR)界面来探究下肢的视觉反馈如何影响障碍物穿越性能。参与者在跑步机上行走时佩戴头戴式显示器,并被指示在四种不同的反馈试验中跨过虚拟走廊中的障碍物。试验包括:(1)无下肢视觉反馈,(2)仅端点模型,(3)链接段模型,以及(4)体积多段模型。我们发现,与无模型相比,体积模型提高了成功率,在穿越前更一致地放置后脚,穿越后更一致地放置前脚,并且穿越后将前脚放置得更靠近障碍物。这些知识对于沉浸式虚拟环境中障碍物协商任务的设计至关重要,因为它可能提供有关再现生态有效练习环境所需逼真度的信息。