Integrating Metaverse-based Data Logging for Personalized Golf Coaching: A Comprehensive Design and Implementation

• Kijung Ryu,
• Hyeonmoon Kim,
• Sungwon Cho,
• Sangjoon Bae,
• Woohyun Lee,
• Dongho Kim,

Vol. 20, No. 2, February 28, 2026
10.3837/tiis.2026.02.013, Download Paper (Free):

• Metaverse
• Golf Coaching
• Motion Capture
• Motor Skill Training

Abstract

As an emerging paradigm for the future of the internet, the metaverse aspires to build a fully immersive, hyper-spatiotemporal, and self-sustaining virtual shared realm where individuals can engage in a range of experiences, from leisure to work and socialization. One of the promising applications of the metaverse is in sports coaching, specifically in golf, a sport that demands high precision and technique. Traditional golf coaching methods rely heavily on imitation, where players attempt to mimic skilled professionals. However, beginners often struggle with identifying keyframes and understanding which specific movements or body parts need correction. Our research leverages a combination of outdoor device data and video recordings to provide comprehensive, multi-perspective analysis of player performance. By integrating data from a lightweight deep learning-based skeleton tracking algorithm and a launch monitor with outdoor golf logging data, we deliver personalized coaching feedback that is both data-driven and remotely accessible. This approach offers players a more precise and effective training experience than imitation alone. This paper outlines the technical framework of our comprehensive virtual golf coaching service, highlighting the integration of diverse data sources and the application of metaverse-based virtual coaching to deliver personalized, real-time guidance for skill refinement.

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