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Multi-modal physiological markers of arousal induced by CO2 inhalation in Virtual Reality

Multi-modal physiological markers of arousal induced by CO2 inhalation in Virtual Reality
Multi-modal physiological markers of arousal induced by CO2 inhalation in Virtual Reality
High arousal states, like fear and anxiety, play a crucial role in organisms’ adaptive responses to threats. Yet, inducing and reliably measuring such states within controlled settings presents challenges. This study uses a novel approach of CO2 enriched air vs normal air in a Virtual Reality (VR) con- text to induce high arousal whilst measuring physiological signals such as galvanic skin response (GSR), facial skin impedance, facial electromyography (fEMG), photoplethysmography (PPG), breathing, and pupillometry. In a single-blind study, 63 participants underwent a regimen involving 20 minutes of breathing regular air followed by 20 minutes of 7.5% CO2, separated by a brief interval. Findings demonstrate the efficacy of CO2 inhalation in elicit- ing high arousal, as substantiated by statistically significant changes for all signals, further validated through high (94%) accuracy arousal classification. This study establishes a method for inducing high arousal states within a laboratory context validated through comprehensive multi-sensor data and machine learning analyses. The study underscores the value of employing a suite of physiological measures to comprehensively describe the intricate dynamics of arousal. The generated database is a promising resource for re- searching physiological markers of arousal, panic, fear, and anxiety, offering insights that can potentially resonate within clinical and therapeutic realms.
Affective computing, Arousal, Methods of data collection, Physiological signals, Virtual reality
Gnacek, Michal
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Özhan, Neslihan
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Broulidakis, John
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Mavridou, Ifigeneia
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Kostoulas, Theodoros
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Balaguer-Ballester, Emili
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Gjoreski, Martin
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Gjoreski, Hristijan
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Nduka, Charles
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Garner, Matthew
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Graf, Erich
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Seiss, Ellen
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Gnacek, Michal
81dbfd9a-0adc-4a3a-8dca-3b7eb5cfcc7b
Özhan, Neslihan
1384b181-e822-4d99-9ecb-a43ec46716c8
Broulidakis, John
abdcd53b-3a88-4528-aad9-650afeb1632d
Mavridou, Ifigeneia
b0f29c8a-227c-4bf0-a985-34476da8c719
Kostoulas, Theodoros
c6b34760-5a7e-48ca-aea0-0ac8c6e98807
Balaguer-Ballester, Emili
324d2f45-af35-4704-b76f-83c4b3fb5a6e
Gjoreski, Martin
27abbcbb-15c5-4249-af15-77cf184c7749
Gjoreski, Hristijan
a76c310d-6151-4fc6-93c8-db1ff71921c3
Nduka, Charles
8e237c28-8bd3-4e12-89a6-854a819a2a43
Garner, Matthew
3221c5b3-b951-4fec-b456-ec449e4ce072
Graf, Erich
1a5123e2-8f05-4084-a6e6-837dcfc66209
Seiss, Ellen
807715b9-11fd-4316-931c-4c4a521d1db1

Gnacek, Michal, Özhan, Neslihan, Broulidakis, John, Mavridou, Ifigeneia, Kostoulas, Theodoros, Balaguer-Ballester, Emili, Gjoreski, Martin, Gjoreski, Hristijan, Nduka, Charles, Garner, Matthew, Graf, Erich and Seiss, Ellen (2025) Multi-modal physiological markers of arousal induced by CO2 inhalation in Virtual Reality. Information Fusion, 126 (Part B), [103643]. (doi:10.1016/j.inffus.2025.103643).

Record type: Article

Abstract

High arousal states, like fear and anxiety, play a crucial role in organisms’ adaptive responses to threats. Yet, inducing and reliably measuring such states within controlled settings presents challenges. This study uses a novel approach of CO2 enriched air vs normal air in a Virtual Reality (VR) con- text to induce high arousal whilst measuring physiological signals such as galvanic skin response (GSR), facial skin impedance, facial electromyography (fEMG), photoplethysmography (PPG), breathing, and pupillometry. In a single-blind study, 63 participants underwent a regimen involving 20 minutes of breathing regular air followed by 20 minutes of 7.5% CO2, separated by a brief interval. Findings demonstrate the efficacy of CO2 inhalation in elicit- ing high arousal, as substantiated by statistically significant changes for all signals, further validated through high (94%) accuracy arousal classification. This study establishes a method for inducing high arousal states within a laboratory context validated through comprehensive multi-sensor data and machine learning analyses. The study underscores the value of employing a suite of physiological measures to comprehensively describe the intricate dynamics of arousal. The generated database is a promising resource for re- searching physiological markers of arousal, panic, fear, and anxiety, offering insights that can potentially resonate within clinical and therapeutic realms.

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Accepted/In Press date: 20 August 2025
e-pub ahead of print date: 2 September 2025
Published date: 8 September 2025
Keywords: Affective computing, Arousal, Methods of data collection, Physiological signals, Virtual reality

Identifiers

Local EPrints ID: 505579
URI: http://eprints.soton.ac.uk/id/eprint/505579
PURE UUID: 09332408-9f20-4753-ad89-38876db3281d
ORCID for Neslihan Özhan: ORCID iD orcid.org/0000-0001-8648-2458
ORCID for Matthew Garner: ORCID iD orcid.org/0000-0001-9481-2226
ORCID for Erich Graf: ORCID iD orcid.org/0000-0002-3162-4233

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Date deposited: 14 Oct 2025 16:42
Last modified: 15 Oct 2025 01:40

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Contributors

Author: Michal Gnacek
Author: Neslihan Özhan ORCID iD
Author: John Broulidakis
Author: Ifigeneia Mavridou
Author: Theodoros Kostoulas
Author: Emili Balaguer-Ballester
Author: Martin Gjoreski
Author: Hristijan Gjoreski
Author: Charles Nduka
Author: Matthew Garner ORCID iD
Author: Erich Graf ORCID iD
Author: Ellen Seiss

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