Human Factors for Designing a Haptic Interface for Interaction with a Virtual Environment

Zadeh, Mehrdad Hosseini; Wang, D.; Kubica, Eric

doi:10.1109/have.2007.4371580

Cited by 13 publications

(6 citation statements)

References 6 publications

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“…In all these applications, unlike previous research, the motion of a user's hand and the virtual haptic object is important. The result in [16,11,31,30] shows a significant variation in human perception and the force thresholds while the velocity of the subject's hand is changed, albeit in a different scenario than is studied in this paper.…”

Section: Related Workmentioning

confidence: 96%

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Active Manipulation of Users in Haptic-Enabled Virtual Environments

Zadeh¹,

Wang²,

Kubica³

2008

Proceedings of the First International Conference on Ambient Media and Systems

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The main goal of this research is to study the effect of subthreshold forces on human performance in a haptic-enabled virtual reality system. A multi-modal task similar to Fitts is used to study the effects of the sub-threshold forces on user performance. Each user's movement is manipulated using controlled forces such that the user is not aware of the forces. Subjects can see the position of the haptic probe in a virtual environment where they are manipulated using sub-threshold forces. The multi-modal task is used to measure the accuracy of subjects in two experiments. During the experiments, the effects of force intensity and the relative direction of applied forces to the direction of user's hand motion in the presence of visual cues are investigated. A performance index is also introduced that can be used to evaluate human performance in the application of subthreshold forces. A psychophysical method is utilized to ensure that the applied forces on the user's hand are below the force threshold of the human haptic system. Results indicate that user performance is affected by both the intensity and direction of sub-threshold forces even when the users could control their actions through visual feedbacks.

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Section: Related Workmentioning

confidence: 96%

“…Zadeh et. al [30] derived Just Noticeable Differences (JND) for human force sensing. They found that the effect of force direction on the force JND is dependent on the increasing or decreasing of the force.…”

Section: Related Workmentioning

confidence: 99%

Active Manipulation of Users in Haptic-Enabled Virtual Environments

Zadeh¹,

Wang²,

Kubica³

2008

Proceedings of the First International Conference on Ambient Media and Systems

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“…Because of these constraints, mobile devices could benefit from special considerations when accessing information over the Internet. In fact, there is a major issue with rendering web content on mobile devices [12], which leads to a low web browsing QoE of the end user.…”

Section: B Mobile Web Qoe (Mwqoe)mentioning

confidence: 99%

MWQoE: A user-centered context-aware model for evaluating the Mobile Web Quality of Experience

Antoniou

Allayiotis

2017

2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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This article presents a human-system interaction modelling approach for quantifying Web Quality of Experience (Web QoE) for mobile devices. It builds on current QoE and Web QoE research, and by fusing together data that is available on modern mobile devices, constructs a novel Mobile Web QoE (MWQoE) model that is user-centered and context-aware. The MWQoE model uses Bayesian Networks and works under uncertainty, while the MWQoE metric uses Utility Theory and delivers a quantified characterization of MWQoE on a single scale in specific scenarios. The importance of MWQoE lies in the fact that online content and service providers need insights into their users in order to understand how the experience in using their products is perceived.

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“…Many studies exist which investigate human motor and sensory performance. Stocco and Salcudean surveyed human hand capabilities to inform haptic interface design [10] while others have tested maximum hand torque [11] or just-noticeable-differences (JND) in force [12]. Of particular interest are the visual-motor response time (RT), frequency response of the hand, and accuracy in positioning and force exertion.…”

Section: Introductionmentioning

confidence: 99%

Human-as-a-Robot Performance in Augmented Reality Teleultrasound

Black¹,

Moradi²,

Salcudean³

2023

Preprint

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Purpose: In “human teleoperation” [1], augmented reality (AR) and haptics are used to tightly couple an expert leader to a human follower. To determine the feasibility of human teleoperation, we quantify the abil- ity of humans to track a position and/or force trajectory via AR cues. The human response time, precision, frequency response, and step response were characterized, and several rendering methods were compared. Methods: Volunteers (n=11) performed a series of tasks as the fol- lower in our human teleoperation system. The tasks involved tracking pre-recorded series of motions and forces, each time with a different rendering method. The order of tasks and rendering methods was ran- domized to avoid learning effects and bias. The volunteers then performed a series of frequency response tests and filled out a questionnaire. Results: Rendering the full ultrasound probe as a position target with an error bar displaying force led to the best position and force tracking. Following force and pose simultaneously was more difficult but did not lead to significant performance degradation versus following one at a time. On average, subjects tracked positions, orientations, and forces with rms tracking errors of 6.2 ± 1.9 mm, 5.9 ± 1.9˚, 1.0 ± 0.3 N, steady-state errors of 2.8 ± 2.1 mm, 0.26 ± 0.2 N, and lags of 345.5 ± 87.6 ms respectively. Performance decreased with input frequency, until the person could no longer follow, depending on the input amplitude. Conclusion: This paper characterizes human tracking ability in aug- mented reality human teleoperation, which shows the system’s feasi- bility and good performance, and is important for designing future human computer interfaces using augmented and virtual reality.

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Human Factors for Designing a Haptic Interface for Interaction with a Virtual Environment

Cited by 13 publications

References 6 publications

Active Manipulation of Users in Haptic-Enabled Virtual Environments

Active Manipulation of Users in Haptic-Enabled Virtual Environments

MWQoE: A user-centered context-aware model for evaluating the Mobile Web Quality of Experience

Human-as-a-Robot Performance in Augmented Reality Teleultrasound

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