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Abstract Investigating emotions relies on pre-validated stimuli to evaluate induced responses through subjective self-ratings and physiological changes. The creation of precise affect models necessitates extensive datasets. While datasets related to pictures, words, and sounds are abundant, those associated with videos are comparatively scarce. To overcome this challenge, we present the first virtual reality (VR) database with continuous self-ratings and physiological measures, including facial EMG. Videos were rated online using a head-mounted VR device (HMD) with attached emteqPRO mask and a cinema VR environment in remote home and laboratory settings with minimal setup requirements. This led to an affective video database with continuous valence and arousal self-rating measures and physiological responses (PPG, facial-EMG (7x), IMU). The AVDOS-VR database includes data from 37 participants who watched 30 randomly ordered videos (10 positive, neutral, and negative). Each 30-second video was assessed with two-minute relaxation between categories. Validation results suggest that remote data collection is ecologically valid, providing an effective strategy for future affective study designs. All data can be accessed via: www.gnacek.com/affective-video-database-online-study .

Virtual Reality (VR) enables the simulation of ecologically validated scenarios, which are ideal for studying behaviour in controllable conditions. Physiological measures captured in these studies provide a deeper insight into how an individual responds to a given scenario. However, the combination of the various biosensing devices presents several challenges, such as efficient time synchronisation between multiple devices, replication between participants and settings, as well as managing cumbersome setups. Additionally, important salient facial information is typically covered by the VR headset, requiring a different approach to facial muscle measurement. These challenges can restrict the use of these devices in laboratory settings. This paper describes a solution to this problem. More specifically, we introduce the emteqPRO system which provides an all-in-one solution for the collection of physiological data through a multi-sensor array built into the VR headset. EmteqPRO is a ready to use, flexible sensor platform enabling convenient, heterogenous, and multimodal emotional research in VR. It enables the capture of facial muscle activations, heart rate features, skin impedance, and movement data—important factors for the study of emotion and behaviour. The platform provides researchers with the ability to monitor data from users in real-time, in co-located and remote set-ups, and to detect activations in physiology that are linked to arousal and valence changes. The SDK (Software Development Kit), developed specifically for the Unity game engine enables easy integration of the emteqPRO features into VR environments.Code available at: (https://github.com/emteqlabs/emteqvr-unity/releases)