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

Michal Gnacek1,2, Luis Quintero3, Ifigeneia Mavridou4

  • 1Centre for Digital Entertainment, Faculty of Media and Communication, Bournemouth University, Poole, BH12 5BB, UK. mgnacek@bournemouth.ac.uk.

Scientific Data
|January 25, 2024
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Summary
This summary is machine-generated.

This study introduces the first virtual reality (VR) affective video database (AVDOS-VR) with continuous physiological and self-rating measures. Remote data collection proved ecologically valid for future emotion research.

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Area of Science:

  • Psychology
  • Computer Science
  • Neuroscience

Background:

  • Affective computing requires extensive datasets for precise emotion models.
  • Existing video-based emotion datasets are scarce compared to other modalities.
  • Virtual reality (VR) offers immersive potential for emotion research.

Purpose of the Study:

  • To introduce the first virtual reality (VR) affective video database (AVDOS-VR).
  • To collect continuous self-ratings and physiological responses during video viewing.
  • To validate remote data collection for affective studies.

Main Methods:

  • Utilized a head-mounted VR device (HMD) with emteqPRO mask for online data collection.
  • Recorded physiological data: photoplethysmography (PPG), facial electromyography (EMG), and inertial measurement units (IMU).
  • Collected continuous valence and arousal self-ratings from 37 participants viewing 30 videos.

Main Results:

  • Developed the AVDOS-VR database with multimodal affective data.
  • Demonstrated the ecological validity of remote data collection methods.
  • Showcased minimal setup requirements for VR-based affective studies.

Conclusions:

  • The AVDOS-VR database provides a valuable resource for emotion research.
  • Remote VR data collection is an effective strategy for large-scale affective studies.
  • This approach facilitates the creation of more robust affect models.