Papers

7

Total Citations

77

H-Index

5

About

Xiangqian Chen is a biomedical robotics researcher whose work sits at the intersection of surgical navigation, medical robotics, and minimally invasive thoracic surgery. His most significant contributions center on developing robotic-assisted navigation systems for the localization and resection of small pulmonary nodules — a notoriously difficult challenge in video-assisted thoracoscopic surgery, where lesions are often neither visible nor palpable during the procedure. Chen's 2019 pioneering work on a surgical navigation puncture robot system (25 citations) established a foundation for CT-guided robotic localization, a line of research he has continued to refine through phantom studies, animal models, and clinical pilot trials, collectively accumulating over 70 citations. His 2023 pilot study on robotic-assisted navigation for preoperative lung nodule localization (22 citations) demonstrated meaningful advances in accuracy over conventional manual techniques, directly addressing limitations in early-stage lung cancer diagnosis and treatment. Beyond thoracic applications, Chen has explored six-degrees-of-freedom robotic arm kinematics for orthopedic navigation and admittance control strategies for respiratory motion compensation during needle placement. His evolving body of work reflects a sustained commitment to improving the precision, safety, and feasibility of robot-assisted surgical interventions, making his research particularly relevant to clinicians and engineers working on the future of image-guided surgery.

Research Focus

Key Achievements

5
H-Index
7
Papers
77
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Intraoperative localization of small pulmonary nodules to assist surgical resection: A novel approach using a surgical navigation puncture robot system
25 citations · 2019
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 45
🏛 Institutions: Beihang University, True (United States), Guangdong Polytechnic of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago