RestfulRaycast: Exploring Ergonomic Rigging and Joint Amplification for Precise Hand Ray Selection in XR

Hand Gesture RecognitionFull-Body Interaction & Embodied InputSoftware Engineers & DevelopersHCI Researchers

Hand raycasting is widely used in extended reality (XR) for selection and interaction, but prolonged use can lead to arm fatigue (e.g., "gorilla arm"). Traditional techniques often require a large range of motion where the arm is extended and unsupported, exacerbating this issue. In this paper, we explore hand raycast techniques aimed at reducing arm fatigue, while minimizing impact to precision selection. In particular, we present Joint-Amplified Raycasting (JAR)---a technique which scales and combines the orientations of multiple joints in the arm to enable more ergonomic raycasting. Through a comparative evaluation with the commonly used industry standard---Shoulder-Palm Raycast (SP) and two other ergonomic alternatives---Offset Shoulder-Palm Raycast (OSP) and Wrist-Palm Raycast (WP)---we demonstrate that JAR results in higher selection throughput and reduced fatigue. A follow-up study highlights the effects of different JAR joint gains on target selection and shows users prefer JAR over SP in a representative UI task.

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https://hci.top/en/papers/dis/200556/2025

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DIS
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Year
2025
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5 authors
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Hand Gesture Recognition, Full-Body Interaction & Embodied Input
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Software Engineers & Developers, HCI Researchers
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