使用神经网络估计机器人辅助微创手术中的工具-组织力。

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

作者信息

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

机构信息

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

出版信息

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

DOI:10.3389/frobt.2019.00056

PMID:33501071

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7805956/

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.

摘要

提出了一种新算法，用于估计机器人辅助微创手术中的工具-组织力相互作用，该算法无需使用外力传感。所提出的方法利用手术器械电机的电流和神经网络方法来估计力相互作用。进行了离线和在线测试，以评估所开发算法的可行性。结果表明，所开发的方法有望实现工具-组织力的在线估计，从而能够在机器人手术中提供触觉反馈。