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

Sajeeva Abeywardena; Qiaodi Yuan; Antonia Tzemanaki; Efi Psomopoulou; Leonidas Droukas; Chris Melhuish; Sanja Dogramadzi

doi:10.3389/frobt.2019.00056

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

Front Robot AI. 2019 Jul 16:6:56. doi: 10.3389/frobt.2019.00056. eCollection 2019.

Authors

Sajeeva Abeywardena¹, Qiaodi Yuan¹, Antonia Tzemanaki¹, Efi Psomopoulou¹, Leonidas Droukas¹, Chris Melhuish¹, Sanja Dogramadzi¹

Affiliation

¹ Bristol Robotics Laboratory, University of the West of England, Bristol, United Kingdom.

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: force estimation; haptic feedback; minimally invasive surgery; neural networks; sensor-less sensing.