AffectTracker: Real-time continuous rating of affective experience in immersive Virtual Reality.

Subjective experience is key to understanding affective states, characterized by valence and arousal. Traditional experiments using post-stimulus summary ratings do not resemble natural behavior. Fluctuations of affective states can be explored with dynamic stimuli, such as videos. Continuous ratings can capture moment-to-moment affective experience, however the rating or the feedback can be interfering. We designed, empirically evaluated, and openly share AffectTracker, a tool to collect continuous ratings of two-dimensional affective experience (valence and arousal) during dynamic stimulation, such as 360-degree videos in immersive virtual reality. AffectTracker comprises three customizable feedback options: a simplified affect grid (Grid), an abstract pulsating variant (Flubber), and no visual feedback. Two studies with healthy adults were conducted, each at two sites (Berlin, Germany, and Torino, Italy). In Study 1 (Selection: n=51), both Grid and Flubber demonstrated high user experience and low interference in repeated 1-min 360-degree videos. Study 2 (Evaluation: n=83) confirmed these findings for Flubber with a longer (23-min), more varied immersive experience, maintaining high user experience and low interference. Continuous ratings collected with AffectTracker effectively captured valence and arousal variability. For shorter, less eventful stimuli, their correlation with post-stimulus summary ratings demonstrated the tool’s validity; for longer, more eventful stimuli, it showed the tool’s benefits of capturing additional variance. Our findings suggest that AffectTracker provides a reliable, minimally interfering method to gather moment-to-moment affective experience also in immersive environments, offering new research opportunities to link affective states and physiological dynamics.

主观体验对于理解情感状态至关重要，情感状态以效价和唤醒度为其特征。传统的使用刺激后总结性评分的实验无法模拟自然行为。情感状态的波动可以通过动态刺激，如视频，进行探究。连续评分能够捕捉到瞬间的情感体验，然而评分或反馈可能会产生干扰。我们设计、实证评估并公开分享了AffectTracker这一工具，用于在动态刺激过程中，如沉浸式虚拟现实中的360度视频中，收集二维情感体验（效价和唤醒度）的连续评分。AffectTracker包含三种可定制的反馈选项：简化的情感网格（Grid）、抽象的脉冲变体（Flubber）以及无视觉反馈。在两个地点（德国柏林和意大利都灵）对健康成年人进行了两项研究。在第一项研究（选择：n=51）中，Grid和Flubber在重复的1分钟360度视频中均表现出高用户体验和低干扰。第二项研究（评估：n=83）通过更长时间（23分钟）和更多样化的沉浸式体验确认了Flubber的这些发现，同时保持了高用户体验和低干扰。使用AffectTracker收集的连续评分有效地捕捉了效价和唤醒度的变化性。对于较短且事件较少的刺激，其与刺激后总结性评分的相关性证明了该工具的有效性；对于较长且事件较多的刺激，它展示了该工具捕捉额外变化性的优势。我们的研究结果表明，AffectTracker提供了一种可靠且干扰最小的收集瞬间情感体验的方法，即使在沉浸式环境中也是如此，为将情感状态与生理动力学联系起来提供了新的研究机会。