A Standardized Workflow for Artificial Intelligence-Assisted Digital Reconstruction of Therapeutic Qigong from Classical Chinese Medical Texts

Therapeutic Qigong exercises documented in classical Chinese medical texts represent a potentially valuable source of rehabilitation interventions; however, many are preserved primarily as concise textual descriptions and lack standardized movement protocols and visual resources for contemporary application. This study established a standardized workflow for transforming historically documented therapeutic Qigong exercises into structured operating protocols and artificial intelligence (AI)-assisted digital resources. The workflow comprised five sequential stages: literature retrieval and exercise selection, exercise standardization, expert review and protocol refinement, AI-assisted digital reconstruction, and quality evaluation. Classical descriptions were transcribed into modern Chinese, operational movement components were extracted, and ambiguous elements were documented before standardized reconstruction. Historically documented components were distinguished from modern additions, including exercise-prescription parameters and safety considerations. The preliminary protocols were reviewed by eight multidisciplinary experts and refined before being used to guide live-action recording and AI-assisted digital reconstruction. The workflow was applied to ten representative therapeutic Qigong exercises corresponding to the five organ systems. All ten reconstructed exercises underwent internal review, independent evaluation by two reviewers, predefined visual artifact screening, and two-dimensional key-frame comparison. The independent reviewers confirmed all six predefined evaluation criteria for all ten exercises. No predefined visual artifacts were recorded across 50 evaluation points. Two-dimensional comparison of representative key postures yielded a mean absolute angular error of 4.46°, with individual errors ranging from 0.40° to 8.20°. This protocol provides a structured methodological framework for converting therapeutic exercises documented in classical Chinese medical texts into standardized and visualized digital resources. The resulting materials represent standardized reconstructions based on defined historical and methodological references rather than exact reproductions of historical practice. The workflow may support future research, education, and digital development of traditional movement-based rehabilitation interventions.