Faceteq prototype v.05 is a wearable technology for measuring facial expressions and biometric responses for experimental studies in Virtual Reality. Developed by Emteq Ltd laboratory, Faceteq can enable new avenues for virtual reality research through combination of high performance patented dry sensor technologies, proprietary algorithms and real-time data acquisition and streaming. Emteq founded the Faceteq project with the aim to provide a human-centered additional tool for emotion expression, affective human-computer interaction and social virtual environments. The proposed demonstration will exhibit the hardware and its functionality by allowing attendees to experience three of the showcasing applications we developed this year.
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)
(2015) A comparative study of electrical potential sensors and Ag/AgCl electrodes for characterising spontaneous and event related electroencephalagram signals. Journal of Neuroscience Methods, This version is available from Sussex Research Online: http://sro.sussex.ac.uk/54264/ This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the URL above for details on accessing the published version. Copyright and reuse:Sussex Research Online is a digital repository of the research output of the University.Copyright and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable, the material made available in SRO has been checked for eligibility before being made available.Copies of full text items generally can be reproduced, displayed or performed and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. AbstractFor exactly 90 years researchers have used electroencephalography (EEG) as a window into the activities of the brain. Even now its high temporal resolution coupled with relatively low cost compares favourably to other neuroimaging techniques such as magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). For the majority of this time the standard electrodes used for non-invasive monitoring of electrical activities of the brain have been Ag/AgCl metal electrodes. Although these electrodes provide a reliable method for recording EEG they suffer from noise, such as offset potential drift, and usability issues, for example, difficult skin preparation and cross-coupling of adjacent electrodes. In order to tackle these issues a prototype Electric Potential Sensor (EPS) device based on an auto-zero operational amplifier has been developed and evaluated. The absence of 1/f noise in these devices makes them ideal for use with signal frequencies of ~10 Hz or less. The EPS is a novel active ultrahigh impedance capacitively coupled sensor. The active electrodes are designed to be physically and electrically robust and chemically and biochemically inert. They are electrically insulated (anodized) and scalable. A comprehensive study was undertaken to compare the results of neural signals recorded by the EPS with a standard commercial EEG system. These studies comprised measurements of both free running EEG and Event Related Potentials (ERPs). Results demonstrate that the EPS provides a promising alternative, with many added benefits compared to standard EEG sensors, including reduced setup time, elimination of sensor cross-coupling, l...
The paper presents the emteqPRO tm system, which uses a facemounted multi-sensor mask to measure the facial physiological responses, facial muscle activations, and motions from the user. These responses are then analyzed by machine learning algorithms to recognize and better understand the user's affective state and context, i.e., emotions, arousal, valence, stress response, activities, etc. The system can work by itself, as an open mask, or can be combined with a commercial Virtual Reality head mounted display. It comprises 3 sensor modalities: a 7-contact f-EMG sensor, a PPG sensor, and a 3-axis IMU, enabling it to measure the affective state of the user in real time. We will demonstrate how the system is used in practice in a Virtual Reality environment. This newly developed technology has the potential to significantly improve the way we collect data, design experiences, and interact within Virtual, Mixed and Augmented Realities.
No abstract
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.