158 research outputs found
Towards an Effectve Arousal Detecton System for Virtual Reality
Immersive technologies offer the potential to drive engagement and create exciting experiences. A better understanding of the emotional state of the user within immersive experiences can assist in healthcare interventions and the evaluation of entertainment technologies. This work describes a feasibility study to explore the effect of affective video content on heart-rate recordings for Virtual Reality applications. A lowcost reflected-mode photoplethysmographic sensor and an electrocardiographic chest-belt sensor were attached on a novel non-invasive wearable interface specially designed for this study. 11 participants responses were analysed, and heart-rate metrics were used for arousal classification. The reported results demonstrate that the fusion of physiological signals yields to significant performance improvement; and hence the feasibility of our new approach
PhysioVR: a novel mobile virtual reality framework for physiological computing
Virtual Reality (VR) is morphing into a ubiquitous
technology by leveraging of smartphones and screenless cases in
order to provide highly immersive experiences at a low price
point. The result of this shift in paradigm is now known as mobile
VR (mVR). Although mVR offers numerous advantages over
conventional immersive VR methods, one of the biggest
limitations is related with the interaction pathways available for
the mVR experiences. Using physiological computing principles,
we created the PhysioVR framework, an Open-Source software
tool developed to facilitate the integration of physiological signals
measured through wearable devices in mVR applications.
PhysioVR includes heart rate (HR) signals from Android
wearables, electroencephalography (EEG) signals from a low cost brain computer interface and electromyography (EMG)
signals from a wireless armband. The physiological sensors are
connected with a smartphone via Bluetooth and the PhysioVR
facilitates the streaming of the data using UDP communication
protocol, thus allowing a multicast transmission for a third party
application such as the Unity3D game engine. Furthermore, the
framework provides a bidirectional communication with the VR
content allowing an external event triggering using a real-time
control as well as data recording options. We developed a demo
game project called EmoCat Rescue which encourage players to
modulate HR levels in order to successfully complete the in-game
mission. EmoCat Rescue is included in the PhysioVR project
which can be freely downloaded. This framework simplifies the
acquisition, streaming and recording of multiple physiological
signals and parameters from wearable consumer devices
providing a single and efficient interface to create novel
physiologically-responsive mVR applications.info:eu-repo/semantics/publishedVersio
Are you there? : Presence in collaborative distance work
doi linkki ei toimi 31.1.2022, ilmoitettu lehteen/USAlready before the pandemic, digitally mediated collaborative work and communication were perceived as challenging. We investigate the attitudes towards emerging technologies and for transforming practises in workplaces. The focus lies on understanding the readiness for appropriating emotional tracking on presence and support for collaboration. The research-based design framework allowed to combine the various perspectives of the transdisciplinary team. Methods included participatory design, design thinking, contextual inquiry and prototype testing for enhancing presence while working with shared objects in video conferencing to explore the appropriation of tools. The findings revealed four indications: 1) awareness of interlocutors’ presence during synchronous communication is crucial. 2) Emotion and behaviour tracking raises concerns about privacy and personal control over what is displayed to others, and technology could be simpler non-distracting the work at hand. 3) The prototype was found to enhance the feeling of presence without disturbing work at hand, and 4) appropriation requires a step-by-step approach.Peer reviewe
A Framework for Psychophysiological Classification within a Cultural Heritage Context Using Interest
This article presents a psychophysiological construct of interest as a knowledge emotion and illustrates the importance of interest detection in a cultural heritage context. The objective of this work is to measure and classify psychophysiological reactivity in response to cultural heritage material presented as visual and audio. We present a data processing and classification framework for the classification of interest. Two studies are reported, adopting a subject-dependent approach to classify psychophysiological signals using mobile physiological sensors and the support vector machine learning algorithm. The results show that it is possible to reliably infer a state of interest from cultural heritage material using psychophysiological feature data and a machine learning approach, informing future work for the development of a real-time physiological computing system for use within an adaptive cultural heritage experience designed to adapt
the provision of information to sustain the interest of the visitor
Plug-in to fear: game biosensors and negative physiological responses to music
The games industry is beginning to embark on an ambitious journey into the world of biometric gaming in search of more exciting and immersive gaming experiences. Whether or not biometric game technologies hold the key to unlock the “ultimate gaming experience” hinges not only on technological advancements alone but also on the game industry’s understanding of physiological responses to stimuli of different kinds, and its ability to interpret physiological data in terms of indicative meaning. With reference to horror genre games and music in particular, this article reviews some of the scientific literature relating to specific physiological responses induced by “fearful” or “unpleasant” musical stimuli, and considers some of the challenges facing the games industry in its quest for the ultimate “plugged-in” experience
Wireless Sensors for Brain Activity—A Survey
Over the last decade, the area of electroencephalography (EEG) witnessed a progressive move from high-end large measurement devices, relying on accurate construction and providing high sensitivity, to miniature hardware, more specifically wireless wearable EEG devices. While accurate, traditional EEG systems need a complex structure and long periods of application time, unwittingly causing discomfort and distress on the users. Given their size and price, aside from their lower sensitivity and narrower spectrum band(s), wearable EEG devices may be used regularly by individuals for continuous collection of user data from non-medical environments. This allows their usage for diverse, nontraditional, non-medical applications, including cognition, BCI, education, and gaming. Given the reduced need for standardization or accuracy, the area remains a rather incipient one, mostly driven by the emergence of new devices that represent the critical link of the innovation chain. In this context, the aim of this study is to provide a holistic assessment of the consumer-grade EEG devices for cognition, BCI, education, and gaming, based on the existing products, the success of their underlying technologies, as benchmarked by the undertaken studies, and their integration with current applications across the four areas. Beyond establishing a reference point, this review also provides the critical and necessary systematic guidance for non-medical EEG research and development efforts at the start of their investigation.</jats:p
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