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Influence of Hand Tracking as a way of Interaction in Virtual Reality on\n User Experience

2020/04/27 by Jan‐Niklas Voigt‐Antons, Voigt-Antons, Jan-Niklas, Tanja Kojić +5 · 1 citation
Computer Science · Psychology · #Color perception and design #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Multimedia (cs.MM) #Virtual Reality Applications and Impacts

paper · pdf · doi:10.48550/arxiv.2004.12642

openalex publication_date 2020/04/27 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28

Abstract

With the rising interest in Virtual Reality and the fast development and\nimprovement of available devices, new features of interactions are becoming\navailable. One of them that is becoming very popular is hand tracking, as the\nidea to replace controllers for interactions in virtual worlds. This experiment\naims to compare different interaction types in VR using either controllers or\nhand tracking. Participants had to play two simple VR games with various types\nof tasks in those games - grabbing objects or typing numbers. While playing,\nthey were using interactions with different visualizations of hands and\ncontrollers. The focus of this study was to investigate user experience of\nvarying interactions (controller vs. hand tracking) for those two simple tasks.\nResults show that different interaction types statistically significantly\ninfluence reported emotions with Self-Assessment Manikin (SAM), where for hand\ntracking participants were feeling higher valence, but lower arousal and\ndominance. Additionally, task type of grabbing was reported to be more\nrealistic, and participants experienced a higher presence. Surprisingly,\nparticipants rated the interaction type with controllers where both where hands\nand controllers were visualized as statistically most preferred. Finally, hand\ntracking for both tasks was rated with the System Usability Scale (SUS) scale,\nand hand tracking for the task typing was rated as statistically significantly\nmore usable. These results can drive further research and, in the long term,\ncontribute to help selecting the most matching interaction modality for a task.\n

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