In this section

Mechatronics in Medicine

The MIM Lab develops robotic and mechatronics surgical systems for a variety of procedures.

Head of Group

B415C Bessemer Building
South Kensington Campus

+44 (0)20 7594 7046

What we do

The Mechatronics in Medicine Laboratory develops robotic and mechatronics surgical systems for a variety of procedures including neuro, cardiovascular, orthopaedic surgeries, and colonoscopies. Examples include bio-inspired catheters that can navigate along complex paths within the brain (such as EDEN2020), soft robots to explore endoluminal anatomies (such as the colon), and virtual reality solutions to support surgeons during knee replacement surgeries.

Meet the team

Mr Ayhan Aktas
Casual - Student demonstrator - lower rate

Dr Daniel Bautista Salinas
Research Associate

Dr Kaiwen Chen
Research Associate

Mr Zejian Cui
Research Assistant

Mr Connor Daly
Research Postgraduate

Emeritus Professor Brian L Davies FREng
Emeritus Professor

Mr Zhaoyang Jacopo Hu
Research Postgraduate

Dr Hisham M Iqbal
Research Associate

Mr Alex Ranne
Research Postgraduate

Professor Ferdinando M Rodriguez y Baena
Co-Director of Hamlyn Centre, Professor of Medical Robotics

Dr Jialei Shi
Research Associate

Mr Spyridon Souipas
Casual - Other work

Ms Emilia Zari
Research Postgraduate

Citation

BibTex format

@inproceedings{Favaro:2021:10.1109/IROS45743.2020.9340847,
author = {Favaro, A and Secoli, R and Rodriguez, y Baena F and DeMomi, E},
doi = {10.1109/IROS45743.2020.9340847},
pages = {3232--3238},
publisher = {IEEE},
title = {Optimal pose estimation method for a multi-segment, programmable bevel-tip steerable needle},
url = {http://dx.doi.org/10.1109/IROS45743.2020.9340847},
year = {2021}
}

Download

RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Pose tracking is fundamental to achieve preciseand safe insertion of a surgical tool for minimally invasiveinterventions. In this work, a method for the estimation of thefull pose of steerable needles is presented. Our approach uses aProgrammable Bevel Tip (PBN) needle with four-segment designas a case study. A novel 3D kinematic model of the PBN isdeveloped and used to predict the full needle pose during theinsertion. The pose prediction is estimated through an ExtendedKalman Filter using the position measurements provided byan electromagnetic sensor located at each tip of the needlesegments. The method estimates also the torsion of the needleshaft that can arise over the insertion of the needle becauseof the shear forces exerted between the needle and the insertionmedium. The feasibility of the proposed solution was validated ina number of experiments in gelatin demonstrating a small errorin position reconstruction (RMSE<0.6mm) and good accuracy incomparison to a bespoke geometric pose reconstruction method.
AU  - Favaro,A
AU  - Secoli,R
AU  - Rodriguez,y Baena F
AU  - DeMomi,E
DO  - 10.1109/IROS45743.2020.9340847
EP  - 3238
PB  - IEEE
PY  - 2021///
SP  - 3232
TI  - Optimal pose estimation method for a multi-segment, programmable bevel-tip steerable needle
UR  - http://dx.doi.org/10.1109/IROS45743.2020.9340847
UR  - https://ieeexplore.ieee.org/abstract/document/9340847
UR  - http://hdl.handle.net/10044/1/81315
ER  -