Traditional methods of viewing medical images (e.g., the PACS system), typically require surgeons to interact with a computer through physical devices such as keyboards and mice, which may violate the sterile principles of the operating room. To address this issue, this study introduces an augmented reality (AR) technology paired with a user-defined gesture set that aligns with surgeons' mental models, allowing surgeons to access and manipulate the PACS system on AR glasses while maintaining sterile conditions. This study represents a beneficial attempt at participatory design for professional users (surgeons) in a constrained space (sterile interaction zone), offering significant theoretical implications and practical value for sterile interaction of other smart medical devices and future Spatial Computing applications.

In the era of Big Data, augmented reality (AR)-based 3D visualization technology is gradually becoming an essential tool of effective information dissemination. However, 3D data visualization inevitably faces a series of challenges, particularly when visualizing large datasets within limited physical spaces. This often results in high spatial density, characterized by smaller target objects and occlusion of data objects, which greatly complicate object selection and subsequent interaction. To address these issues, this paper proposes a multimodal progressive target selection technique-StarPicker, which integrates the SpotLight metaphor and Clock metaphor. By leveraging wrist rotation and gesture interactions, StarPicker facilitates a coarse-to-fine semantic disambiguation and precise selection of target objects. To validate the effectiveness of StarPicker, a comparative user study was conducted against the state-of-the-art techniques (GridWall and FlowerCone) under high-density (up to 360 objects) and small-target (1cm) conditions. Experimental results demonstrate that StarPicker significantly outperforms the baselines in terms of target selection accuracy and user satisfaction, while achieving comparable or better completion times, especially in denser scenes. This work offers a novel approach to target selection and interaction technology in the field of AR-based 3D Big Data visualization.