Measuring the human side of virtual reality

Whalen, Tara; Noël, Sylvie; Stewart, John A.

doi:10.1109/vecims.2003.1227022

Cited by 12 publications

(10 citation statements)

References 11 publications

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“…As Jain puts it [Jain 2004], we require improved performance measures over the well-established QoS measures to deal with the subjectivity of the user. Whalen et al [2003] discuss some of the methods and challenges in determining those performance measures in the context of VR.…”

Section: Measuring Qoe In Virtual Realitymentioning

confidence: 99%

“…Traditionally, there are three recognized methods for assessing the user's feedback and responses in a virtual environment (VE): subjective, performance-based, and physiological measures [Whalen et al 2003]. Each method enables the collection of a specific type of information regarding the user's responses to the application.…”

Section: Measuring Qoe In Virtual Realitymentioning

confidence: 99%

“…Karam et al [2009] state their intention to add biometric measures for physiological evaluation of an audio-tactile display in the future (such as respiration and heart rate) to reinforce the user's evaluation. Specific to the QoE, Whalen et al [2003] suggest the use of physiological measures to determine the QoE of VR applications. With stress as an example, the authors argue that the sympathetic nervous system is activated and blood volume, heart rate, and respiration rate all increase.…”

Section: Measuring Qoe In Virtual Realitymentioning

confidence: 99%

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A Quality of Experience Model for Haptic Virtual Environments

Hamam

Saddik

Alja’am

2014

ACM Trans. Multimedia Comput. Commun. Appl.

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Haptic-based Virtual Reality (VR) applications have many merits. What is still obscure, from the designer's perspective of these applications, is the experience the users will undergo when they use the VR system. Quality of Experience (QoE) is an evaluation metric from the user's perspective that unfortunately has received limited attention from the research community. Assessing the QoE of VR applications reflects the amount of overall satisfaction and benefits gained from the application in addition to laying the foundation for ideal user-centric design in the future. In this article, we propose a taxonomy for the evaluation of QoE for multimedia applications and in particular VR applications. We model this taxonomy using a Fuzzy logic Inference System (FIS) to quantitatively measure the QoE of haptic virtual environments. We build and test our FIS by conducting a users' study analysis to evaluate the QoE of a haptic game application. Our results demonstrate that the proposed FIS model reflects the user's estimation of the application's quality significantly with low error and hence is suited for QoE evaluation.

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Section: Measuring Qoe In Virtual Realitymentioning

confidence: 99%

Section: Measuring Qoe In Virtual Realitymentioning

confidence: 99%

Section: Measuring Qoe In Virtual Realitymentioning

confidence: 99%

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A Quality of Experience Model for Haptic Virtual Environments

Hamam

Saddik

Alja’am

2014

ACM Trans. Multimedia Comput. Commun. Appl.

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“…Aside from the difficulty of creating easy ways to navigate and manipulate objects in 3D there were the difficulties in communication produced by the use of avatars as intermediaries. NML decided to investigate ways in which to improve interactions for users in a virtual world [Whalen et al 2003]. …”

Section: Usability Solutionsmentioning

confidence: 99%

A decade of NML networked graphics

Stewart

Dumoulin

Noël

2010

Proceedings of the 15th International Conference on Web 3D Technology

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“…QoE can be measured through subjective assessment or estimated through a model based on parameters of content, specific user, and specific context. Nowadays there are three approaches for measuring QoE: subjective, performance-based, physiological measures, and hybrid approaches [34]. Each method enables the collection of specific type of information regarding the user's experience.…”

Section: Introductionmentioning

confidence: 99%

A model to measure QoE for virtual personal assistant

Saad

Afzal

El-Issawi

et al. 2016

Multimed Tools Appl

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Until now the virtual assistants (like Siri, Google Now and Cortana) have primarily been confined to voice input and output only. Is there a justification for voice only confinement or can we enhance the user experience by adding a visual output? We hypothesized that providing a higher level of visual/auditory immersion would enhance the quality of user experience. In order to test this hypothesis, we first developed 4 variants of virtual assistant, each with a different audio/visual level of immersion. Developed virtual assistant systems were the following; audio only, audio and 2D visual display, audio and 3D visual display and audio and immersive 3D visual display. We developed a plan for usability testing of all 4 variants. The usability testing was conducted with 30 subjects against eight (8) dependent variables included presence, involvement, attention, reliability, dependency, easiness, satisfaction and expectations. Each subject rated these dependent variables based on a scale of 1-5, 5 being the highest value. The raw data collected from usability testing was then analyzed through several tools in order to determine the factors contributing towards the quality of experience for each of the 4 variants. The significant factors were then used develop a model that measures the quality of user experience. It was found that each variant had a different set of significant variables. Hence, in order to rate each system there is a need to develop a scale that is dependent upon the unique set of variables for the respective variant. Furthermore, it was found that variant 4 scored the highest rate for Quality of Experience (QoE). Lastly several other qualitative conclusions were also drawn from this research that will guide future work in the field of virtual assistants.

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Measuring the human side of virtual reality

Cited by 12 publications

References 11 publications

A Quality of Experience Model for Haptic Virtual Environments

A Quality of Experience Model for Haptic Virtual Environments

A decade of NML networked graphics

A model to measure QoE for virtual personal assistant

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