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Estimation of Tool-Tissue Forces in Robot-Assisted Minimally Invasive Surgery Using Neural Networks

Sajeeva Abeywardena, Qiaodi Yuan, Antonia Tzemanaki, Efi Psomopoulou, Λεωνίδας Δρούκας, Melhuish Chris, Sanja Dogramadzi

Year
2019
Citations
32
Access
Open access

Abstract

A new algorithm is proposed to estimate the tool-tissue force interaction in robot-assisted minimally invasive surgery which does not require the use of external force sensing. The proposed method utilizes the current of the motors of the surgical instrument and neural network methods to estimate the force interaction. Offline and online testing is conducted to assess the feasibility of the developed algorithm. Results showed that the developed method has promise in allowing online estimation of tool-tissue force and could thus enable haptic feedback in robotic surgery to be provided.

Keywords

Haptic technologyComputer scienceInvasive surgeryRobotArtificial neural networkArtificial intelligenceRobotic surgerySurgical robotMinimally invasive proceduresSimulation

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