1. Clinical Research and Innovation in Orthopedic Trauma
Focused on promoting multidisciplinary co-management models for elderly hip fractures, significantly reducing preoperative waiting time, lowering complication rates, and accelerating patient recovery, thereby establishing a distinctive clinical practice model within the hospital.
Proposed and internationally published a novel surgical technique for subtrochanteric femoral fractures in the prone position (Injury, 2017), addressing the global challenge of difficult reduction and maintenance in such fractures. This technique simplifies the reduction process, reduces the burden on assistants, and shortens operative time, and was presented at the 2018 SICOT Congress.
Pioneered the use of musculoskeletal ultrasound for intraoperative guidance of femoral fracture reduction (Arch Orthop Trauma Surg, 2018), reducing ionizing radiation exposure for both patients and healthcare providers. This work was presented at the 2019 4th AO Trauma Asia Pacific Scientific Congress.
Participated in the research project “A Series of Studies on Osteoporotic Hip Fractures in the Elderly”, which received the First Prize of the Huaxia Medical Science and Technology Award in 2014 (ranked fifth contributor).
2. Application of Advanced Technologies in Orthopedic Clinical Practice
Integrated emerging technologies—including MEMS, Internet of Things (IoT), augmented reality (AR), artificial intelligence (AI), and surgical robotics—into the full spectrum of orthopedic diagnosis and treatment, enhancing processes from outpatient diagnosis and intraoperative navigation to robotic-assisted surgery and patient management.
Developed an AI-assisted diagnostic system for osteoarthritis based on Microsoft Kinect depth cameras, combining machine learning and computer vision (World Congress on Medical Physics and Biomedical Engineering, 2018), with algorithmic pattern recognition (Computerized Medical Imaging and Graphics, 2020, Chinese Journal of Orthopaedics 2021), enabling automated and efficient diagnosis of osteoarthritis.
Established a pedicle screw placement system using ultrasound-based registration and AR navigation (Int J CARS, 2017); validated its feasibility through model and animal experiments. Further developed a hybrid optical–magnetic tracking system for AR-guided interlocking screw implantation (Med Robotics Comput Assist Surg, 2018), and the approach was validated through model experiments.
Applied robotic technology to pelvic fracture surgery, developing fluoroscopy-based intraoperative displacement detection algorithms (BMC Medical Imaging, 2015) and a computer-assisted reduction device (Journal of Orthopaedic Research, 2015), which demonstrated favorable outcomes (BioMed Research International, 2018). Led the development of a multi-task intelligent orthopedic surgical robot incorporating AI and aerospace control technologies, granted two Chinese invention patents (ZL 2017 1 0361356.1, ZL 2017 1 1018537.0) and one US patent (US 10,874,469 B2). Created a real-time structured light-guided spinal navigation robot (Int J CARS, 2020), simplifying the system structure and surgical workflow.
Integrated MEMS sensors into orthopedic implants to develop smart implants capable of IoT-based patient monitoring. This project was supported by the Precision Medicine Fund of Beijing Tsinghua Changgung Hospital (CNY 100,000) and is entering the animal testing phase.
3. Development of Intelligent Orthopedic Implants Based on Big Data and AI
Conducted systematic studies on femoral canal curvature, angulation, and isthmus morphology, with results published in Biomed Res Int (2015) and widely cited.
Developed high-performance automated medical image segmentation algorithms (IEEE J Biomed Health Inform, 2019) and a method for anatomical measurement using non-rigid registration and statistical shape modeling (Computerized Medical Imaging and Graphics, 2020), enabling automated measurement of anatomical parameters based on clinical knowledge. Applied unsupervised machine learning to classify femoral canal morphologies in the Chinese population into three types (IEEE J Biomed Health Inform, 2018), with clinical relevance verified via simulated internal fixation experiments. This research received support from the Clinical Technology Innovation Project of the Beijing Hospital Authority (XMLX202141), with a funding amount of CNY 300,000.
Based on this system, completed the design and translation of novel implants including an anatomically guided acetabular locking plate (ZL201610648185.6), a medially stabilized proximal femoral intramedullary nail (Injury, 2019), and a sliding locking plate for femoral neck fractures (ZL 2018 1 0430019.8) (J Orthop Surg Res, 2019), which are now in clinical use by Shandong Wego Orthopaedic Device Co.,ltd. As the lead designer, also developed a modular minimally invasive intramedullary pinning system for hands and feet (ZL201720209892.5) and a one-time integrated version (ZL201720210513.4), commercialized by Beijing Wego Yahua Artificial Joint Co., Ltd. The project also received support from the Beijing Municipal Science and Technology Commission’s “Medical Synergy Innovation Research” Program (CNY 900,000).
