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The emergence of next-generation XR smart glasses presents unprecedented opportunities for personalized digital rehabilitation. This study introduces G-BALANCE FIT (Global Balance Fitness Intelligence Training), a comprehensive theoretical framework for personality-aware AR gait training systems targeting the Google-Samsung-Gentle Monster XR ecosystem. Our methodology integrates the HEXACO personality model with advanced multimodal feedback mechanisms for global applications. Building upon established smartphone-based multimodal gait training approaches [33, 34] and our previous AI-based real-time gait and HAI interaction research [35], drawing on systematic literature analysis and computational modeling grounded in existing research evidence, we develop theoretical projections for potential improvements in gait rehabilitation effectiveness and cross-cultural engagement. The framework emphasizes HEXACO dimensions for global health applications, with theoretical modeling suggesting that personality-based adaptations may enhance rehabilitation outcomes through context-dependent advantages in specific domains. This research establishes foundational design principles for personality-aware multimodal human-AI interaction systems in next-generation XR rehabilitation applications and offers a clear roadmap for implementation when consumer XR hardware becomes commercially available.

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Intelligent Personality-Aware AR Gait Training Using Smart Glasses: Personalized Multimodal Feedback for Next-Generation Digital Rehabilitation

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Eunseon Jo,
  • Han-jin Lee

摘要

The emergence of next-generation XR smart glasses presents unprecedented opportunities for personalized digital rehabilitation. This study introduces G-BALANCE FIT (Global Balance Fitness Intelligence Training), a comprehensive theoretical framework for personality-aware AR gait training systems targeting the Google-Samsung-Gentle Monster XR ecosystem. Our methodology integrates the HEXACO personality model with advanced multimodal feedback mechanisms for global applications. Building upon established smartphone-based multimodal gait training approaches [33, 34] and our previous AI-based real-time gait and HAI interaction research [35], drawing on systematic literature analysis and computational modeling grounded in existing research evidence, we develop theoretical projections for potential improvements in gait rehabilitation effectiveness and cross-cultural engagement. The framework emphasizes HEXACO dimensions for global health applications, with theoretical modeling suggesting that personality-based adaptations may enhance rehabilitation outcomes through context-dependent advantages in specific domains. This research establishes foundational design principles for personality-aware multimodal human-AI interaction systems in next-generation XR rehabilitation applications and offers a clear roadmap for implementation when consumer XR hardware becomes commercially available.