HaptMR: Smart Haptic Feedback for Mixed Reality Based on Computer Vision Semantic

Zhang, Yueze; Liang, Ruoxin; Sun, Zhanglei; Koch, Maximilian

doi:10.1007/978-3-030-77599-5_18

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…Also, for privacy reasons, some participants may turn off their videos providing no visuals at all for the assessment. To improve participants' learning experience and performance over time, sending personalized feedback via real-time computer vision-based motion analysis (Zhang, Liang, Sun, & Koch, 2021) and automatic performance assessment (Chen, He, & Hsu, 2018) would be effective.…”

Section: Discussionmentioning

confidence: 99%

An Observational Study Investigating Verbal Communication Differences in Online vs. In-person Group Exercise Training

Islam

Sayani

Harden

et al. 2022

Proceedings of the Human Factors and Ergonomics Society Annual

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Section: Discussionmentioning

confidence: 99%

An Observational Study Investigating Verbal Communication Differences in Online vs. In-person Group Exercise Training

Islam

Sayani

Harden

et al. 2022

Proceedings of the Human Factors and Ergonomics Society Annual

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Sensitivity to Vibrotactile Stimulation in the Hand and Wrist: Effects of Motion, Temporal Patterns, and Biological Sex

Tajdari,

Forsyth,

Lim

2024

Hum Factors

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Objective We investigated the impact of low-tempo, repetitive hand movements on vibrotactile sensitivity by employing various temporal and spatial patterns in the hand and wrist area. Background The investigation of a human’s ability to perceive vibrotactile stimuli during dynamic hand movements remains understudied, despite the prevalence of slow to mild hand motions in applications such as hand navigation or gesture control using haptic gloves in Virtual Reality (VR) and Augmented Reality (AR). Method We investigated vibrotactile sensitivity, analyzing the impact of various factors, including Motion (static and low-tempo repetitive hand movements), Temporal Patterns (Single or Double vibrations with varying onset times), Tactor Placements (hand and wrist), Spatial Patterns, and Biological Sex. Results Our study revealed that Motion significantly influences vibrotactile sensitivity in the hand and wrist areas, leading to reduced accuracy rates during dynamic conditions. Additionally, as the stimulus onset approached in Double vibrations, accuracy rates markedly decreased. Notably, Hand Placement resulted in significantly higher accuracy rates compared to the Wrist Placement. Conclusion Our findings underscore the impact of motion in reducing vibrotactile sensitivity on the back of the hand and around the wrist. Application This research has wide-ranging practical applications, particularly in the field of VR/AR experiences, rehabilitation programs, and accessibility solutions through the use of haptic gloves. Insights from our study can be harnessed to enhance the efficacy of haptic gloves in conveying vibrotactile cues within these contexts.

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HaptMR: Smart Haptic Feedback for Mixed Reality Based on Computer Vision Semantic

Cited by 2 publications

References 24 publications

An Observational Study Investigating Verbal Communication Differences in Online vs. In-person Group Exercise Training

An Observational Study Investigating Verbal Communication Differences in Online vs. In-person Group Exercise Training

Sensitivity to Vibrotactile Stimulation in the Hand and Wrist: Effects of Motion, Temporal Patterns, and Biological Sex

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