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基于前庭网络的多媒体生物传感网络晕动病检测。

Multimodal Biosensing for Vestibular Network-Based Cybersickness Detection.

出版信息

IEEE J Biomed Health Inform. 2022 Jun;26(6):2469-2480. doi: 10.1109/JBHI.2021.3134024. Epub 2022 Jun 3.

Abstract

Virtual reality (VR) has the potential to induce cybersickness (CS), which impedes CS-susceptible VR users from the benefit of emerging VR applications. To better detect CS, the current study investigated whether/how the newly proposed human vestibular network (HVN) is involved in flagship consumer VR-induced CS by simultaneously recording autonomic physiological signals as well as neural signals generated in sensorimotor and cognitive domains. The VR stimuli were made up of one or two moderate CS-inducing entertaining task(s) as well as a mild CS-inducing cognitive task implemented before and after the moderate CS task(s). Results not only showed that CS impaired cognitive control ability, represented by the degree of attentional engagement, but also revealed that combined indicators from all three HVN domains could together establish the best regression relationship with CS ratings. More importantly, we found that every HVN domain had its unique advantage with the dynamic changes in CS severity and time. These results provide evidence for involvement of the HVN in CS and indicate the necessity of HVN-based CS detection.

摘要

虚拟现实(VR)有可能引起网络晕动症(CS),这会使易患 CS 的 VR 用户无法从新兴的 VR 应用中受益。为了更好地检测 CS,本研究通过同时记录自主生理信号以及在感觉运动和认知领域产生的神经信号,调查了新提出的人类前庭网络(HVN)是否/如何参与主流消费 VR 引起的 CS。VR 刺激由一个或两个中等 CS 诱导的娱乐任务以及一个中等 CS 诱导的认知任务组成,该认知任务在中等 CS 任务之前和之后执行。结果不仅表明 CS 会损害认知控制能力,表现为注意力投入程度,还揭示了来自 HVN 三个领域的综合指标可以共同建立与 CS 评分的最佳回归关系。更重要的是,我们发现每个 HVN 领域都有其独特的优势,与 CS 严重程度和时间的动态变化有关。这些结果为 HVN 参与 CS 提供了证据,并表明基于 HVN 的 CS 检测的必要性。

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