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<p>Human movement is a complex cognitive process that is not entirely automatic, contrary to common perception. Increase in cognitive load from using head-mounted displays (HMDs) while walking, may interfere with working memory and provoke compensatory locomotor behaviour that deviates from normal movement patterns. This interference can present critical implications for understanding cognitive load and situational awareness during locomotion. Despite the importance of such data, existing publicly available datasets suffer significant limitations, typically featuring either a limited number of participants or simplified task complexity. To address this gap, the presented dataset provides a comprehensive set of walking movement patterns collected from 47 individuals under three distinct conditions: without an HMD, while wearing an optical-see-through (OST) HMD, and while using a video see-through (VST) HMD). The dataset offers a robust normative reference of human motion during typical functional tasks. This dataset provides researchers and developers a valuable resource for detecting inattentional blindness, assessing cognitive load, and developing predictive models of movement adaptation.</p>

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A Comprehensive Full Body Kinematics Dataset with and without Head-Mounted AR/VR Display

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月4日

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  • Ted Yeung,
  • Biruthuvan Keeran Balachandran,
  • Vibhava Leelaratna,
  • Thor Besier,
  • Mark Billinghurst,
  • Alexander Stamenkovic,
  • Stephan Lukosch,
  • Arash Mahnan

摘要

Human movement is a complex cognitive process that is not entirely automatic, contrary to common perception. Increase in cognitive load from using head-mounted displays (HMDs) while walking, may interfere with working memory and provoke compensatory locomotor behaviour that deviates from normal movement patterns. This interference can present critical implications for understanding cognitive load and situational awareness during locomotion. Despite the importance of such data, existing publicly available datasets suffer significant limitations, typically featuring either a limited number of participants or simplified task complexity. To address this gap, the presented dataset provides a comprehensive set of walking movement patterns collected from 47 individuals under three distinct conditions: without an HMD, while wearing an optical-see-through (OST) HMD, and while using a video see-through (VST) HMD). The dataset offers a robust normative reference of human motion during typical functional tasks. This dataset provides researchers and developers a valuable resource for detecting inattentional blindness, assessing cognitive load, and developing predictive models of movement adaptation.