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

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

Research output: Contribution to journalArticle (Academic Journal)peer-review

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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 utilises 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.
Original languageEnglish
Article number56
Number of pages11
JournalFrontiers in Robotics and AI
Volume6
Early online date16 Jul 2019
DOIs
Publication statusE-pub ahead of print - 16 Jul 2019

Keywords

  • sensor-less sensing
  • neural networks
  • minimally invasive surgery
  • haptic feedback
  • force estimation

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