AVDOS-VR: Affective Video Database with Physiological Signals and Continuous Ratings Collected Remotely in VR
Authors: Gnacek, M., Quintero, L., Mavridou, I., Balaguer-Ballester, E., Kostoulas, T., Nduka, C., Seiss, E.
Journal: Scientific Data
Publication Date: 01/12/2024
Volume: 11
Issue: 1
eISSN: 2052-4463
DOI: 10.1038/s41597-024-02953-6
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 .
https://eprints.bournemouth.ac.uk/39384/
Source: Scopus
AVDOS-VR: Affective Video Database with Physiological Signals and Continuous Ratings Collected Remotely in VR.
Authors: Gnacek, M., Quintero, L., Mavridou, I., Balaguer-Ballester, E., Kostoulas, T., Nduka, C., Seiss, E.
Journal: Sci Data
Publication Date: 25/01/2024
Volume: 11
Issue: 1
Pages: 132
eISSN: 2052-4463
DOI: 10.1038/s41597-024-02953-6
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 .
https://eprints.bournemouth.ac.uk/39384/
Source: PubMed
AVDOS-VR: Affective Video Database with Physiological Signals and Continuous Ratings Collected Remotely in VR
Authors: Gnacek, M., Quintero, L., Mavridou, I., Balaguer-Ballester, E., Kostoulas, T., Nduka, C., Seiss, E.
Journal: SCIENTIFIC DATA
Publication Date: 25/01/2024
Volume: 11
Issue: 1
eISSN: 2052-4463
DOI: 10.1038/s41597-024-02953-6
https://eprints.bournemouth.ac.uk/39384/
Source: Web of Science
AVDOS-VR: Affective Video Database with Physiological Signals and Continuous Ratings Collected Remotely in VR
Authors: Gnacek, M., Quintero, L., Balaguer-Ballester, E., Kostoulas, T., Nduka, C., Seiss, E.
Journal: Nature Scientific Data
Publication Date: 29/02/2024
Publisher: Springer Nature
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
https://eprints.bournemouth.ac.uk/39384/
Source: Manual
AVDOS-VR: Affective Video Database with Physiological Signals and Continuous Ratings Collected Remotely in VR.
Authors: Gnacek, M., Quintero, L., Mavridou, I., Balaguer-Ballester, E., Kostoulas, T., Nduka, C., Seiss, E.
Journal: Scientific data
Publication Date: 01/2024
Volume: 11
Issue: 1
Pages: 132
eISSN: 2052-4463
ISSN: 2052-4463
DOI: 10.1038/s41597-024-02953-6
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 .
https://eprints.bournemouth.ac.uk/39384/
Source: Europe PubMed Central