Gnacek, M., Broulidakis, J., Mavridou, I., Fatoorechi, M., Seiss, E., Kostoulas, T., Balaguer-Ballester, E., Kiprijanovska, I., Rosten, C. and Nduka, C., 2022. emteqPRO—Fully Integrated Biometric Sensing Array for Non-Invasive Biomedical Research in Virtual Reality. Frontiers in virtual reality, 3, 781218.
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Official URL: https://www.frontiersin.org/articles/10.3389/frvir...
DOI: 10.3389/frvir.2022.781218
Abstract
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)
Item Type: | Article |
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ISSN: | 2673-4192 |
Uncontrolled Keywords: | virtual reality; biosensors; affect; electromyography; photoplethysmography; biomedical measurement; valence; arousal |
Group: | Faculty of Media & Communication |
ID Code: | 38103 |
Deposited By: | Symplectic RT2 |
Deposited On: | 06 Feb 2023 16:48 |
Last Modified: | 06 Feb 2023 16:48 |
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