A QoE evaluation of immersive augmented and virtual reality speech &amp; language assessment applications

Keighrey, Conor; Flynn, Ronan; Murray, Siobhan; Murray, Niall

doi:10.1109/qomex.2017.7965656

Cited by 47 publications

(20 citation statements)

References 8 publications

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“…Elevated values for heart rate and electrodermal activity were correlated with physiological arousal -one of the factors associated with user QoE. The potential and benefits of using these objective metrics as indicators of user QoE for immersive experiences were shown also for augmented reality applications in [Keighrey et al 2017].…”

Section: Mulsemedia and Qoementioning

confidence: 94%

Using Eye Tracking and Heart-Rate Activity to Examine Crossmodal Correspondences QoE in Mulsemedia

Mesfin

Hussain

Covaci

et al. 2019

ACM Trans. Multimedia Comput. Commun. Appl.

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Different senses provide us with information of various levels of precision and enable us to construct a more precise representation of the world. Rich multisensory simulations are thus beneficial for comprehension, memory reinforcement or retention of information. Crossmodal mappings refer to the systematic associations often made between different sensory modalities (e.g., high pitch is matched with angular shapes) and govern multisensory processing. A great deal of research effort has been put in exploring crossmodal correspondences in the field of cognitive science. However, the possibilities they open in the digital world have been relatively unexplored. Mulsemedia-multiple sensorial media-provides a highly immersive experience to the users and enhances their Quality of Experience (QoE) in the digital world. Thus, we consider that studying the plasticity and the effects of crossmodal correspondences in a mulsemedia setup can bring interesting insights about improving the human computer dialogue and experience. In our experiments, we exposed users to videos with certain visual dimensions (brightness, color and shape) and we investigated if the pairing with a crossmodal matching sound (high and low pitch) and the corresponding auto-generated vibrotactile effects (produced by a haptic vest) lead to an enhanced QoE. For this, we captured the eye gaze and the heart rate of users while experiencing mulsemedia and we asked them to fill in a set of questions targeting their enjoyment and perception at the end of the experiment. Results showed differences in eye gaze patterns and heart rate between the experimental and the control group indicating changes in participants' engagement when videos were accompanied by matching crossmodal sounds (this effect was the strongest for the video displaying angular shapes and high pitch audio) and transitively generated crossmodal vibrotactile effects. CCS Concepts: • Human-centered computing → HCI design and evaluation methods;Interaction paradigms;Interaction techniques;Empirical studies in HCI;

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Section: Mulsemedia and Qoementioning

confidence: 94%

Using Eye Tracking and Heart-Rate Activity to Examine Crossmodal Correspondences QoE in Mulsemedia

Mesfin

Hussain

Covaci

et al. 2019

ACM Trans. Multimedia Comput. Commun. Appl.

View full text Add to dashboard Cite

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“…Typically, these devices perform binocular vision augmentation and content presentation, and initial interest is emerging for directly comparing the two approaches in immersive contexts [1]. For AR applications in particular, content is commonly displayed to provide context-dependent information.…”

Section: Introductionmentioning

confidence: 99%

Visual Interface Evaluation for Wearables Datasets: Predicting the Subjective Augmented Vision Image QoE and QoS

Bauman

Seeling

2017

Future Internet

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Abstract:As Augmented Reality (AR) applications become commonplace, the determination of a device operator's subjective Quality of Experience (QoE) in addition to objective Quality of Service (QoS) metrics gains importance. Human subject experimentation is common for QoE relationship determinations due to the subjective nature of the QoE. In AR scenarios, the overlay of displayed content with the real world adds to the complexity. We employ Electroencephalography (EEG) measurements as the solution to the inherent subjectivity and situationality of AR content display overlaid with the real world. Specifically, we evaluate prediction performance for traditional image display (AR) and spherical/immersive image display (SAR) for the QoE and underlying QoS levels. Our approach utilizing a four-position EEG wearable achieves high levels of accuracy. Our detailed evaluation of the available data indicates that less sensors would perform almost as well and could be integrated into future wearable devices. Additionally, we make our Visual Interface Evaluation for Wearables (VIEW) datasets from human subject experimentation publicly available and describe their utilization.

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“…The ordering of how the participants experienced the feedback was randomised. Participants were tested on two different days and the protocol adhered to the approach taken in numerous related works in the literature [17,37,55] and included the steps outlined in Fig 6. During the information phase, each participant was greeted and thanked for their participation. After a brief explanation, written consent was obtained.…”

Section: Experimental Protocolmentioning

confidence: 99%

“…Several authors have used QoE assessment in multimedia systems as a paradigm to quantify how various factors of the system influence perceived quality levels from the user perspective. In [37], user QoE levels were compared in an immersive Virtual Reality and Augmented Reality applications. A sample size of twenty-one participants was divided randomly into two groups.…”

Section: Introductionmentioning

confidence: 99%

A Quality of Experience assessment of haptic and augmented reality feedback modalities in a gait analysis system

et al. 2020

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Gait analysis is a technique that is used to understand movement patterns and, in some cases, to inform the development of rehabilitation protocols. Traditional rehabilitation approaches have relied on expert guided feedback in clinical settings. Such efforts require the presence of an expert to inform the re-training (to evaluate any improvement) and the patient to travel to the clinic. Nowadays, potential opportunities exist to employ the use of digitized "feedback" modalities to help a user to "understand" improved gait technique. This is important as clear and concise feedback can enhance the quality of rehabilitation and recovery. A critical requirement emerges to consider the quality of feedback from the user perspective i.e. how they process, understand and react to the feedback. In this context, this paper reports the results of a Quality of Experience (QoE) evaluation of two feedback modalities: Augmented Reality (AR) and Haptic, employed as part of an overall gait analysis system. The aim of the feedback is to reduce varus/valgus misalignments, which can cause serious orthopedics problems. The QoE analysis considers objective (improvement in knee alignment) and subjective (questionnaire responses) user metrics in 26 participants, as part of a within subject design. Participants answered 12 questions on QoE aspects such as utility, usability, interaction and immersion of the feedback modalities via post-test reporting. In addition, objective metrics of participant performance (angles and alignment) were also considered as indicators of the utility of each feedback modality. The findings show statistically significant higher QoE ratings for AR feedback. Also, the number of knee misalignments was reduced after users experienced AR feedback (35% improvement with AR feedback relative to baseline when compared to haptic). Gender analysis showed significant differences in performance for number of misalignments and time to correct valgus misalignment (for males when they experienced AR feedback). The female group self-reported higher utility and QoE ratings for AR when compared to male group.A QoE assessment of haptic and augmented reality feedback modalities in a gait analysis system PLOS ONE | https://doi.This section contains a critique of related research in terms of multimodal gait feedback systems and QoE assessments approaches for Haptic and AR (not all are specific to gait feedback). Each of these aspects are relevant to the scope of this work. PLOS ONEA QoE assessment of haptic and augmented reality feedback modalities in a gait analysis system PLOS ONE | https://doi.

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A QoE evaluation of immersive augmented and virtual reality speech & language assessment applications

Cited by 47 publications

References 8 publications

Using Eye Tracking and Heart-Rate Activity to Examine Crossmodal Correspondences QoE in Mulsemedia

Using Eye Tracking and Heart-Rate Activity to Examine Crossmodal Correspondences QoE in Mulsemedia

Visual Interface Evaluation for Wearables Datasets: Predicting the Subjective Augmented Vision Image QoE and QoS

A Quality of Experience assessment of haptic and augmented reality feedback modalities in a gait analysis system

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