Research and Development of Health Qigong Teaching Aids and Movement Correction Equipment

Health Qigong, a cornerstone of traditional Chinese wellness practice, faces a critical barrier to wider adoption: the inherent difficulty in mastering its complex movements. Conventional teaching, hampered by the lack of real-time, objective feedback and standardized guidance, often leads to inefficient learning and potential errors. To overcome this fundamental challenge, this study pioneers an intelligent mechanical-assisted learning system. Our breakthrough solution seamlessly integrates high-precision 3D motion tracking, biomechanical analysis, and AI-driven correction. The system captures user movement in real-time, rigorously compares it against gold-standard models, and delivers instantaneous, multi-modal feedback (haptic and visual) to the learner. Crucially, the integrated AI module autonomously identifies deviations (e.g., posture angles, joint misalignment) and dynamically adjusts mechanical resistance to actively guide users towards correct form. Rigorous experimental validation with 50 participants (novices and instructors) demonstrated a remarkable $\mathbf{4 2 \%}$ acceleration in skill acquisition compared to traditional methods. This innovative human-machine interaction not only dramatically enhances learning efficiency and accuracy but also significantly reduces reliance on scarce instructor resources, enabling scalable, high-fidelity self-training - a transformative advancement for traditional mind-body exercise pedagogy.