Knowledge Commons of Institute of Automation，CAS
| Robotic Automatic Drilling for Craniotomy: Algorithms and In Vitro Animal Experiments | |
Bian, Gui-Bin1 ; Wei, Bing-Ting1; Li, Zhen1; Ge, Peicong2; Chen, Zhang1,3; Qian, Chen1; Wang, Jie1,4; Fu, Pan1,4; Zhao, Jizong2
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| 发表期刊 | IEEE-ASME TRANSACTIONS ON MECHATRONICS
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| ISSN | 1083-4435 |
| 2023-05-05 | |
| 页码 | 12 |
| 通讯作者 | Bian, Gui-Bin(guibin.bian@ia.ac.cn) |
| 摘要 | Craniotomy is used in the treatment of various craniocerebral diseases and injuries. However, there are still many complications in craniotomy, and the detection and protection of the dura mater during the drilling of the skull is a clinical challenge. Preserving the integrity of the dura mater is very important for maintaining the anatomical integrity of the brain, protecting the brain tissue, and preventing complications such as infection, hemorrhage, and cerebrospinal fluid leakage. In this study, a feed velocity and thrust force constraint control method for automatic skull-drilling is proposed. A skull-dura boundary detection algorithm based on monitoring the change of thrust force is proposed. A model that describes the relationship between the thrust force and the displacement of the cranial perforator (CP) during skull drilling-through is derived. A cranial drilling robot-assisted system is built, and experiments on animal skulls are carried out. Across 72 in vitro drilling experiments, the success rate of detecting skull penetration is 93.06$\%$. After the skull-dura boundary is detected, the extra displacement of the CP is less than 1 mm. The proposed robot-assisted system not only improves the safety of cranial drilling but also reduces the difficulty and burden of operation for surgeons, and provides a platform for improving the intelligence of neurosurgery. |
| 关键词 | Drilling Robots Force Robot sensing systems Skull Feeds Service robots Autonomous drilling craniotomy robot feed velocity and force constraint control in vitro experiment skull-dura boundary detection |
| DOI | 10.1109/TMECH.2023.3268111 |
| 关键词[WOS] | FORCE ; TOOL ; BREAKTHROUGH ; PLUNGE |
| 收录类别 | SCI |
| 语种 | 英语 |
| 资助项目 | National Natural Science Foundation of China[62027813] ; National Natural Science Foundation of China[U20A20196] ; National Natural Science Foundation of China[62176266] ; CAS Interdisciplinary Innovation Team[JCTD-2019-07] ; Beijing Science Fund for Distinguished Young Scholars[JQ21016] |
| 项目资助者 | National Natural Science Foundation of China ; CAS Interdisciplinary Innovation Team ; Beijing Science Fund for Distinguished Young Scholars |
| WOS研究方向 | Automation & Control Systems ; Engineering |
| WOS类目 | Automation & Control Systems ; Engineering, Manufacturing ; Engineering, Electrical & Electronic ; Engineering, Mechanical |
| WOS记录号 | WOS:000988501200001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/53382 |
| 专题 | 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Bian, Gui-Bin |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 2.Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, Beijing 100070, Peoples R China 3.Hebei Univ Technol, Sch Artificial Intelligence & Data Sci, Tianjin 300131, Peoples R China 4.Beijing Informat Sci & Technol Univ, Sch Automat, Beijing 100101, Peoples R China |
| 第一作者单位 | 中国科学院自动化研究所 |
| 通讯作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Bian, Gui-Bin,Wei, Bing-Ting,Li, Zhen,et al. Robotic Automatic Drilling for Craniotomy: Algorithms and In Vitro Animal Experiments[J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS,2023:12. |
| APA | Bian, Gui-Bin.,Wei, Bing-Ting.,Li, Zhen.,Ge, Peicong.,Chen, Zhang.,...&Zhao, Jizong.(2023).Robotic Automatic Drilling for Craniotomy: Algorithms and In Vitro Animal Experiments.IEEE-ASME TRANSACTIONS ON MECHATRONICS,12. |
| MLA | Bian, Gui-Bin,et al."Robotic Automatic Drilling for Craniotomy: Algorithms and In Vitro Animal Experiments".IEEE-ASME TRANSACTIONS ON MECHATRONICS (2023):12. |
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