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Wearable interactive full-body motion tracking and haptic feedback network systems with deep learning

Author

Listed:
  • Sang Uk Park

    (Sungkyunkwan University)

  • Hee Kyu Lee

    (Sungkyunkwan University)

  • Hyun Bin Kim

    (Sungkyunkwan University)

  • Doyoung Kim

    (Sungkyunkwan University)

  • Wooseok Kim

    (Sungkyunkwan University)

  • Janghoon Joo

    (Sungkyunkwan University)

  • Bogeun Kim

    (Sungkyunkwan University)

  • Byeong Woon Lee

    (Sungkyunkwan University)

  • Yei Hwan Jung

    (Hanyang University)

  • Sungjun Park

    (Ajou University
    Ajou University)

  • Il Yong Chun

    (Sungkyunkwan University
    Institute for Basic Science (IBS))

  • Hyoyoung Jeong

    (University of California)

  • Joohoon Kang

    (Yonsei University)

  • Jae-Young Yoo

    (Sungkyunkwan University
    Sungkyunkwan University)

  • Sang Min Won

    (Sungkyunkwan University)

Abstract

The increasing demand for motion tracking systems has been accelerated by advancements in virtual reality (VR) and motion reconstruction technologies. Combined with emerging innovations in the Internet of Things (IoT), these systems have unlocked transformative applications, from immersive user experiences to personalized healthcare solutions. However, conventional motion tracking systems often fall short of delivering sophisticated tracking and feedback capabilities, while systems designed for detailed motion analysis are typically costly and limited to controlled environments. This study introduces a cost-effective motion tracking system that integrates full-body motion analysis with real-time, bidirectional haptic feedback. Utilizing flexible, patch-type epidermal haptic devices alongside a remote machine‑learning framework, the system captures full‑body motion and delivers personalized, time‑synchronized feedback. Its closed‑loop design lays the groundwork for real‑time bidirectional haptic cues that accommodate user responsiveness and engagement.

Suggested Citation

  • Sang Uk Park & Hee Kyu Lee & Hyun Bin Kim & Doyoung Kim & Wooseok Kim & Janghoon Joo & Bogeun Kim & Byeong Woon Lee & Yei Hwan Jung & Sungjun Park & Il Yong Chun & Hyoyoung Jeong & Joohoon Kang & Jae-, 2025. "Wearable interactive full-body motion tracking and haptic feedback network systems with deep learning," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-63644-3
    DOI: 10.1038/s41467-025-63644-3
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    References listed on IDEAS

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