What is the clinical evidence from this study?

Study design: Observational. Population: Healthy participants (n=37). Intervention: Virtual reality affective video viewing (AVDOS-VR). Primary outcome: Validation of continuous self-ratings and physiological measures in VR.

What does this research mean for the field?

Remote data collection of physiological signals and continuous affective self-ratings using virtual reality headsets is ecologically valid and provides an effective strategy for emotion research. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

January 25, 2024Open Access

AVDOS-VR: Affective Video Database with Physiological Signals and Continuous Ratings Collected Remotely in VR

Key Result

The AVDOS-VR database successfully captured continuous valence and arousal self-ratings alongside physiological responses (PPG, facial-EMG, IMU) from 37 participants in remote and laboratory VR settings.

Study Design

Type

Observational (n=37)

Multicenter

Structured PICO

Population

37 participants (16 males, 21 females), mean age 23.4 years (range 18-40). Exclusion criteria: age below 18 or over 45, inability to wear contact lenses, psychological conditions, cardiovascular, respiratory, or neurological conditions, and possible alexithymia.

Intervention

Watching 30 randomly ordered 30-second affective videos (10 positive, neutral, negative) in a VR headset (Pico G2 4k with emteqPRO mask) with continuous self-ratings and physiological measures (PPG, facial-EMG, IMU) collected remotely or in a simulated remote lab setting.

Outcome

Creation of the AVDOS-VR database with continuous valence and arousal self-rating measures and physiological responses.

The AVDOS-VR database provides a novel, ecologically valid dataset of continuous self-ratings and physiological measures collected remotely in virtual reality to advance affective computing research.

Limitations

Unsupervised remote data collection carries the potential for participants moving or removing the device, necessitating rigorous validation procedures.
Device fit quality might degrade over time or immediately after calibration ends.

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 .

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