Development and Validation of a Robot-Assisted Retraction System for Orthopedic Surgery

Tissue retraction, one of the basic steps in orthopedic surgery, is related to the smooth entry of surgical instruments into the surgical area and provides a clear surgical perspective for surgeons. This work introduces the first robot-assisted retraction system (RARS) specifically designed for orthopedic surgery. The RARS allows surgeons to set a safe retraction force and roughly set the posture of the retraction device at the beginning. To ensure that the RARS automatically completes the task in a safe manner, we propose a safety control framework that employs iterative enhanced control based on interaction model to handle the retraction interaction problem, and avoids interference with the operation of surgeons through null-space optimization. First, we performed a performance test of the RARS on a phantom model, and the results showed that the maximum tracking error of the retraction force was 0.51N, demonstrating satisfactory tracking performance. Second, we validated the effectiveness of null-space optimization by observing the evolution of joint positions. Finally, we conducted experiments on in-vivo animal and the results showed that the proposed RARS exhibited superior performance in safe retraction force tracking accuracy and tissue damage compared to traditional manual retractions.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Medical Robotics and Bionics
Published
2025-03-12
DOI
https://doi.org/10.1109/tmrb.2025.3550648
Citations
5
Primary Topic
Surgical Simulation and Training
Type
article
Field-Weighted Citation Impact
10.03
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and Validation of a Robot-Assisted Retraction System for Orthopedic Surgery

Yuzhen Jiang, Xingguang Duan, Changsheng Li, Xiaolong Zhu et al.
5 citations
IEEE Transactions on Medical Robotics and Bionics
Surgical Simulation and Training
10.03
article

Development and Validation of a Robot-Assisted Retraction System for Orthopedic Surgery

Yuzhen Jiang, Xingguang Duan, Changsheng Li, Xiaolong Zhu, Rui He
article en
5 citations

Abstract

Tissue retraction, one of the basic steps in orthopedic surgery, is related to the smooth entry of surgical instruments into the surgical area and provides a clear surgical perspective for surgeons. This work introduces the first robot-assisted retraction system (RARS) specifically designed for orthopedic surgery. The RARS allows surgeons to set a safe retraction force and roughly set the posture of the retraction device at the beginning. To ensure that the RARS automatically completes the task in a safe manner, we propose a safety control framework that employs iterative enhanced control based on interaction model to handle the retraction interaction problem, and avoids interference with the operation of surgeons through null-space optimization. First, we performed a performance test of the RARS on a phantom model, and the results showed that the maximum tracking error of the retraction force was 0.51N, demonstrating satisfactory tracking performance. Second, we validated the effectiveness of null-space optimization by observing the evolution of joint positions. Finally, we conducted experiments on in-vivo animal and the results showed that the proposed RARS exhibited superior performance in safe retraction force tracking accuracy and tissue damage compared to traditional manual retractions.

IEEE Transactions on Medical Robotics and BionicsVol. 7(2)
Beijing Institute of Technology (CN), Capital Medical University (CN), Peking University (CN), Beijing Jishuitan Hospital (CN)
Openalex Percentile: Top 2%
Surgical Simulation and Training
10.03
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.