Advancing Virtual and Extended Reality: Innovations in Therapy, Training, and Data-Driven Research

The research landscape in the field of virtual and extended reality (XR) is rapidly evolving, with a strong focus on enhancing user experiences and developing innovative applications across various domains such as healthcare, education, and manufacturing. A notable trend is the integration of advanced technologies like virtual reality (VR) and augmented reality (AR) into therapeutic and training contexts, demonstrating significant potential for improving cognitive and motor skills. Studies are also exploring the use of XR in addressing social and psychological challenges, particularly for aging populations and internal migrants, by leveraging the immersive capabilities of the metaverse to foster resilience and social integration. Additionally, there is a growing emphasis on the development and analysis of large-scale datasets to support empirical research and the advancement of XR technologies, ensuring scalability and usability. Methodological innovations, such as the use of motion capture and robotics to assess VR accuracy, are contributing to the optimization of VR experiences. Overall, the field is advancing towards more personalized, effective, and scalable XR solutions, driven by interdisciplinary research and the integration of diverse technological approaches.

Sources

'Being there together for health': A Systematic Review on the Feasibility, Effectiveness and Design Considerations of Immersive Collaborative Virtual Environments in Health Applications

Preliminary Study on Virtual Reality Framework for Effective Prospective Memory Training: Integration of Visual Imagery and Daily-life Simulations

Metamemory: Exploring the Resilience of Older Internal Migrants

How Accurate is the Positioning in VR? Using Motion Capture and Robotics to Compare Positioning Capabilities of Popular VR Headsets

XRZoo: A Large-Scale and Versatile Dataset of Extended Reality (XR) Applications

Zeitgebers-Based User Time Perception Analysis and Data-Driven Modeling via Transformer in VR

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