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虚拟现实中恐惧、挫折和顿悟的生理反应特征。

Characterizing Physiological Responses to Fear, Frustration, and Insight in Virtual Reality.

出版信息

IEEE Trans Vis Comput Graph. 2022 Nov;28(11):3917-3927. doi: 10.1109/TVCG.2022.3203113. Epub 2022 Oct 21.

Abstract

Physiological sensing often complements studies of human behavior in virtual reality (VR) to detect users' affective and cognitive states. Some psychological states, such as fear and frustration, can be particularly hard to differentiate from a physiological perspective as they are close in the arousal and valence emotional space. Moreover, it is largely unclear how users' physiological reactions are expressed in response to transient psychological states such as fear, frustration, and insight-especially since these are rich indicators for characterizing users' responses to dynamic systems but are hard to capture in highly interactive settings. We conducted a study ($N=24$) to analyze participants' pulmonary, electrodermal, cardiac, and pupillary responses to moments of fear, frustration, and insight in immersive settings. Participants interacted in five VR environments, throughout which we measured their physiological reactions and analyzed the patterns we observed. We also measured subjective fear and frustration using questionnaires. We found differences between fear and frustration pupillary, respiratory, and electrodermal responses, as well as between the pupillary changes that followed fear in a horror game and those that followed fear in a vertigo experiment. We present the relationships between fear levels, frustration levels, and their physiological responses. To detect these affective events and states, we introduce user-independent binary classification models that achieved an average micro $F_{1}$ score of 71% for detecting fear in a horror game, 75% for fear of vertigo, 76% for frustration, and 75% for insight, showing the promise for detecting these states from passive and objective signals.

摘要

生理感应通常与虚拟现实 (VR) 中的人类行为研究相辅相成,以检测用户的情感和认知状态。一些心理状态,如恐惧和挫折感,从生理角度来看很难区分,因为它们在唤醒和效价情感空间上非常接近。此外,人们还不清楚用户的生理反应如何在面对恐惧、挫折和顿悟等短暂的心理状态时表现出来,尤其是因为这些是对动态系统进行特征描述的重要指标,但很难在高度互动的环境中捕捉到这些状态。我们进行了一项研究(N=24),以分析参与者在沉浸式环境中对恐惧、挫折和顿悟时刻的肺、皮肤电、心脏和瞳孔反应。参与者在五个 VR 环境中进行交互,在此期间我们测量了他们的生理反应,并分析了我们观察到的模式。我们还使用问卷调查来测量主观恐惧和挫折感。我们发现恐惧和挫折感在瞳孔、呼吸和皮肤电反应方面存在差异,以及恐怖游戏中恐惧后和眩晕实验中恐惧后瞳孔变化之间的差异。我们展示了恐惧水平、挫折水平及其生理反应之间的关系。为了检测这些情感事件和状态,我们引入了用户独立的二进制分类模型,该模型在恐怖游戏中检测恐惧的平均微 F1 得分为 71%,在眩晕恐惧中为 75%,在挫折中为 76%,在顿悟中为 75%,这表明从被动和客观的信号中检测这些状态具有很大的潜力。

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