Visual Attention Based Cognitive Human–Robot Collaboration for Pedicle Screw Placement in Robot-Assisted Orthopedic Surgery

Current orthopedic robotic systems largely focus on navigation, aiding surgeons in positioning a guiding tube but still requiring manual drilling and screw placement. The automation of this task not only demands high precision and safety due to the intricate physical interactions between the surgical tool and bone but also poses significant risks when executed without adequate human oversight. As it involves continuous physical interaction, the robot should collaborate with the surgeon, understand the human intent, and always include the surgeon in the loop. To achieve this, this paper proposes a new cognitive human–robot collaboration framework, including the intuitive AR-haptic human–robot interface, the visual-attention-based surgeon model, and the shared interaction control scheme for the robot. User studies on a robotic platform for orthopedic surgery are presented to illustrate the performance of the proposed method. The results demonstrate that the proposed human– robot collaboration framework outperforms full robot and full human control in terms of safety and ergonomics.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10801930
Citations
2
Primary Topic
Medical Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.37

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article

Visual Attention Based Cognitive Human–Robot Collaboration for Pedicle Screw Placement in Robot-Assisted Orthopedic Surgery

Mingrui Yu, Yuhang Song, Chen Chen, Senqiang Zhu et al.
2 citations
Medical Imaging and Analysis
0.37
article

Visual Attention Based Cognitive Human–Robot Collaboration for Pedicle Screw Placement in Robot-Assisted Orthopedic Surgery

Mingrui Yu, Yuhang Song, Chen Chen, Senqiang Zhu, Shiji Song, Xiang Li, Qikai Zou
article en
2 citations

Abstract

Current orthopedic robotic systems largely focus on navigation, aiding surgeons in positioning a guiding tube but still requiring manual drilling and screw placement. The automation of this task not only demands high precision and safety due to the intricate physical interactions between the surgical tool and bone but also poses significant risks when executed without adequate human oversight. As it involves continuous physical interaction, the robot should collaborate with the surgeon, understand the human intent, and always include the surgeon in the loop. To achieve this, this paper proposes a new cognitive human–robot collaboration framework, including the intuitive AR-haptic human–robot interface, the visual-attention-based surgeon model, and the shared interaction control scheme for the robot. User studies on a robotic platform for orthopedic surgery are presented to illustrate the performance of the proposed method. The results demonstrate that the proposed human– robot collaboration framework outperforms full robot and full human control in terms of safety and ergonomics.

Harbin Institute of Technology (CN), Midea Group (China) (CN), Tsinghua University (CN)
National Natural Science Foundation of China, Tsinghua University
Openalex Percentile: Top 41%
Medical Imaging and Analysis
0.37
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