Introduction
Virtual Reality (VR) is defined as “an advanced form of human–computer interface that allows the user to interact with and become immersed in a computer-generated environment in a naturalistic fashion” (Schultheis and Rizzo, 2001). Unlike lab scenarios, video stimuli, or even augmented reality, VR is unique in that it is at the furthest end of the reality continuum (Milgram and Kishino, 1994) replacing real-world environments with virtual contexts. This allows for levels of stimulus control that surpass lab testing, absolute control of colors, textures, and luminance (Riva et al., 2016). The addition of integrated eye tracking, which is currently available to control interfaces and guide avatars in games (e.g., FOVE Eye Tracking VR Headset), opens up for measuring psychophysiological responses remotely on a large scale. In their extensive review of the VR literature, Lindner et al. (2017) concluded that eye tracking is becoming an important new technology in commercially available VR. The widespread use of VR by the public, in research, and in therapy is creating a need for more high-quality empirical studies examining VR and its capability for naturalistic “Big Data.”
In this paper, we propose and provide a proof-of-concept assessment of a robust system for large-scale in-home testing using consumer products that combine psychophysiological measures and VR, here referred to as a Virtual Lab. Specifically, our first aim is to simultaneously test and correlate two autonomic measures: skin conductance response (SCR), a well-established autonomic measure that has been reliably used in previous VR studies, and pupil dilation, a measure which has been demonstrated as a reliable autonomic measure but has yet to be tested and validated in VR. Our second aim is to demonstrate that these measures can be reliably recorded independent of physical location, demonstrating possibilities for remote testing. For a Virtual Lab to be a feasible reality in scientific research, it is important to establish that: (a) there is a demand for remote data collection on a large scale, (b) there is a wide availability of VR equipment in homes, and (c) there is a way to measure autonomic responses in a reliable and robust manner through the VR device. Each of which will be discussed briefly in the following sections.[…}


