Research on the feasibility of estimating gripping force based on grasper parameters in laparoscopic surgery
YL Yan, T Ren, L Ding - Proceedings of the 2023 15th International …, 2023 - dl.acm.org
YL Yan, T Ren, L Ding
Proceedings of the 2023 15th International Conference on Bioinformatics and …, 2023•dl.acm.orgLack of force feedback, which is one of the most urgent problems in laparoscopic surgery,
can be solved by installing sensors on the surgical grabbers; however, there are many
limitations such as biocompatibility and sterilization. In order to study the force on soft tissue
during laparoscopic surgery, this paper presents a method to estimate the grasping force
based on the grasper jaw parameters. The grasping action of soft tissues was reduced to the
compression process of soft tissues by a single grasper jaw. A laparoscopic grasping force …
can be solved by installing sensors on the surgical grabbers; however, there are many
limitations such as biocompatibility and sterilization. In order to study the force on soft tissue
during laparoscopic surgery, this paper presents a method to estimate the grasping force
based on the grasper jaw parameters. The grasping action of soft tissues was reduced to the
compression process of soft tissues by a single grasper jaw. A laparoscopic grasping force …
Lack of force feedback, which is one of the most urgent problems in laparoscopic surgery, can be solved by installing sensors on the surgical grabbers; however, there are many limitations such as biocompatibility and sterilization. In order to study the force on soft tissue during laparoscopic surgery, this paper presents a method to estimate the grasping force based on the grasper jaw parameters. The grasping action of soft tissues was reduced to the compression process of soft tissues by a single grasper jaw. A laparoscopic grasping force estimation model was explored by using the parameters of compression speed, compression depth, and contact area between the grasper jaw and the soft tissue. The goodness of fit of the prediction model was 0.992 for the compression force of pig kidney tissue, respectively, which could achieve a good fitting effect. Finally, the calculated value of the prediction model is compared with the measured value. The results show that the reliability and goodness of fit of the prediction are good.
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