Intelligent knee arthroplasty based on digital twin and mixed reality： system design， collaborative process and prospects

The advent of medical robots has transformed the landscape of surgery. Compared to traditional surgical methods, the use of surgical robots provides significant advantages in enhancing precision and reducing the workload for surgeons. However, due to resource constraints, fully automated, end-to-end surgical robots are poised to become a key trend in the development of metaverse medicine. Existing knee surgery robots predominantly operate in a semi-active mode, serving as assistants to surgeons, while a limited number of "fully automated" robots can only achieve full automation during the intraoperative phase. This paper proposes an intelligent knee replacement surgery approach based on digital twin and mixed reality technologies, adopting a model of human pre-operative rehearsal and supervision, machine planning, and robotic execution. This shifts the paradigm from "semi-active" to "semi-automated" (covering the full process), serving as a transitional step toward fully automated end-to-end surgery. By ensuring safety and gaining acceptance from both medical professionals and patients, this approach enables high-quality surgical outcomes. It aligns better with current technological foundations and practical requirements while also offering potential for advancements in quantitative surgical assessment within the realm of metaverse medicine.

Key Words: knee arthroplasty; digital twin; metaverse medicine; surgical robot