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Related Experiment Video

Updated: Jun 21, 2026

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss
07:12

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Published on: April 11, 2025

Cross-View Multimodal Vision-Based Assessment Framework for Traditional Chinese Medicine Rehabilitation Training.

Francis Xiatian Zhang, Hao Yao, Shengxuan Chen

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |June 19, 2026
    PubMed
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    This study introduces CME-AQA, a novel vision-based system for assessing Traditional Chinese Medicine (TCM) rehabilitation training. The framework improves accuracy in acupuncture and Tuina techniques, making training more effective.

    Area of Science:

    • Computer Vision
    • Rehabilitation Medicine
    • Traditional Chinese Medicine (TCM)

    Background:

    • Vision-based assessment offers cost-effective evaluation for Traditional Chinese Medicine (TCM) rehabilitation.
    • Existing automatic action quality assessment (AQA) frameworks struggle with TCM techniques due to self-occlusion and complex interactions.

    Purpose of the Study:

    • To develop an advanced vision-based assessment framework for TCM rehabilitation training.
    • To enhance the accuracy and robustness of automatic action quality assessment (AQA) in TCM practices like acupuncture and Tuina.

    Main Methods:

    • Proposed CME-AQA: a cross-view, multimodal framework integrating visual-pose fusion.
    • Utilized synchronized first-person and third-person videos for robust training.
    • Collected dual-view datasets (TCMAQA61-A for Acupuncture, TCM-AQA61-T for Tuina) with expert annotations.

    Related Experiment Videos

    Last Updated: Jun 21, 2026

    A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss
    07:12

    A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

    Published on: April 11, 2025

    Main Results:

    • Achieved superior or comparable performance against baselines.
    • Demonstrated over 10% relative improvement in weighted F1 for key rating tasks (e.g., Needle Depth).
    • Reduced mean absolute error in quantitative measures (e.g., insertion time).

    Conclusions:

    • CME-AQA enhances assessment accuracy for structured TCM rehabilitation training.
    • The framework facilitates more convenient and effective training-oriented skill evaluation.
    • Applicable to related simulated clinical skill assessments involving participant motion.