{"title":"A New Suture Needle State estimation Method Based on Electrical Impedance Sensing","authors":"K. Schwaner, Zhuoqi Cheng, T. Savarimuthu","doi":"10.31256/hsmr2023.79","DOIUrl":null,"url":null,"abstract":"Autonomous surgical task execution has the potential to improve surgeons’ working conditions, increase hos- pital throughput, and better patient outcomes in the future. While fully autonomous robotic minimally inva- sive surgery (RMIS) is currently unrealistic for several reasons, partly automated surgery – or task autonomy [1] – is being explored for different surgical tasks. One such task is suturing, which involves complex motions in a challenging environment. Automating the suturing task using surgical robots has been attracting research interest (see, e.g., [2]–[4] for recent studies). Despite these advances, automated suturing is still lim- ited to controlled environments and is not yet applicable in realistic surgical settings. This paper presents a step towards autonomous robotic suturing. Specifically, we propose a method for suture needle state estimation during insertion into soft tissue based on electrical bioimpedance (EBI) sensing. EBI is an advantageous sensing modality in RMIS, given that it is non-invasive and requires only minor modifications to existing surgical instruments. In this study, we equip a surgical robot with EBI sensing capabilities, allowing the robot to measure the electrical impedance between a needle driver instrument and a common ground elec- trode. The proposed method requires a suture needle with insulation coating except for its tip, end, and notch in the middle. We conducted an experiment for concept validation based on ex vivo animal tissue where we obtained a 98.8 % prediction accuracy on four different suture needle insertion states. Most interestingly, we could accurately determine when the needle tip exits after being pushed through soft tissue, which is chal- lenging to do with, e.g., computer vision due to the needle’s small size and occlusions. The needle tip exiting is valuable information as often one wishes to grasp the needle tip with a second manipulator to complete the suture throw by pulling the needle through the tissue.","PeriodicalId":129686,"journal":{"name":"Proceedings of The 15th Hamlyn Symposium on Medical Robotics 2023","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of The 15th Hamlyn Symposium on Medical Robotics 2023","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31256/hsmr2023.79","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Autonomous surgical task execution has the potential to improve surgeons’ working conditions, increase hos- pital throughput, and better patient outcomes in the future. While fully autonomous robotic minimally inva- sive surgery (RMIS) is currently unrealistic for several reasons, partly automated surgery – or task autonomy [1] – is being explored for different surgical tasks. One such task is suturing, which involves complex motions in a challenging environment. Automating the suturing task using surgical robots has been attracting research interest (see, e.g., [2]–[4] for recent studies). Despite these advances, automated suturing is still lim- ited to controlled environments and is not yet applicable in realistic surgical settings. This paper presents a step towards autonomous robotic suturing. Specifically, we propose a method for suture needle state estimation during insertion into soft tissue based on electrical bioimpedance (EBI) sensing. EBI is an advantageous sensing modality in RMIS, given that it is non-invasive and requires only minor modifications to existing surgical instruments. In this study, we equip a surgical robot with EBI sensing capabilities, allowing the robot to measure the electrical impedance between a needle driver instrument and a common ground elec- trode. The proposed method requires a suture needle with insulation coating except for its tip, end, and notch in the middle. We conducted an experiment for concept validation based on ex vivo animal tissue where we obtained a 98.8 % prediction accuracy on four different suture needle insertion states. Most interestingly, we could accurately determine when the needle tip exits after being pushed through soft tissue, which is chal- lenging to do with, e.g., computer vision due to the needle’s small size and occlusions. The needle tip exiting is valuable information as often one wishes to grasp the needle tip with a second manipulator to complete the suture throw by pulling the needle through the tissue.