Towards Effective Human Performance in XR Space Framework based on Real-time Eye Tracking Biofeedback
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866916867384279040 |
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| author | Karpowicz, Barbara Kowalewski, Tomasz Zinevych, Pavlo Kuzdraliński, Adam Wójcik, Grzegorz Marcin Kopeć, Wiesław |
| author_facet | Karpowicz, Barbara Kowalewski, Tomasz Zinevych, Pavlo Kuzdraliński, Adam Wójcik, Grzegorz Marcin Kopeć, Wiesław |
| contents | This paper proposes an eye tracking module for the XR Space Framework aimed at enhancing human performance in XR-based applications, specifically in training, screening, and teleoperation. This framework provides a methodology and components that streamline the development of adaptive real-time virtual immersive systems. It contains multimodal measurements - declarative in the form of in-VR questionnaires and objective, including eye tracking, body movement, and psychophysiological data (e.g., ECG, GSR, PPG). A key focus of this paper is the integration of real-time eye tracking data into XR environments to facilitate a biofeedback loop, providing insight into user attention, cognitive load, and engagement. Given the relatively high measurement frequency of eye tracking - recognized as a noninvasive yet robust psychophysiological measure - this technology is particularly well suited for real-time adjustments in task difficulty and feedback to enhance learning and operational effectiveness. Despite its established role in cognitive and attentional studies, implementing eye tracking metrics within dynamic, real-time XR environments poses unique challenges, particularly given the complex moving visuals presented in head-mounted displays (HMDs). This paper addresses these challenges by focusing on the essential aspects of integrating eye tracking in immersive systems based on real-time engines, ultimately facilitating more efficient, adaptive XR applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_21000 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Effective Human Performance in XR Space Framework based on Real-time Eye Tracking Biofeedback Karpowicz, Barbara Kowalewski, Tomasz Zinevych, Pavlo Kuzdraliński, Adam Wójcik, Grzegorz Marcin Kopeć, Wiesław Human-Computer Interaction This paper proposes an eye tracking module for the XR Space Framework aimed at enhancing human performance in XR-based applications, specifically in training, screening, and teleoperation. This framework provides a methodology and components that streamline the development of adaptive real-time virtual immersive systems. It contains multimodal measurements - declarative in the form of in-VR questionnaires and objective, including eye tracking, body movement, and psychophysiological data (e.g., ECG, GSR, PPG). A key focus of this paper is the integration of real-time eye tracking data into XR environments to facilitate a biofeedback loop, providing insight into user attention, cognitive load, and engagement. Given the relatively high measurement frequency of eye tracking - recognized as a noninvasive yet robust psychophysiological measure - this technology is particularly well suited for real-time adjustments in task difficulty and feedback to enhance learning and operational effectiveness. Despite its established role in cognitive and attentional studies, implementing eye tracking metrics within dynamic, real-time XR environments poses unique challenges, particularly given the complex moving visuals presented in head-mounted displays (HMDs). This paper addresses these challenges by focusing on the essential aspects of integrating eye tracking in immersive systems based on real-time engines, ultimately facilitating more efficient, adaptive XR applications. |
| title | Towards Effective Human Performance in XR Space Framework based on Real-time Eye Tracking Biofeedback |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2507.21000 |