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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{Virdyawan:2019:10.1109/IROS.2018.8594198,
author = {Virdyawan, V and Rodriguez, y Baena F},
doi = {10.1109/IROS.2018.8594198},
publisher = {IEEE},
title = {Vessel pose estimation for obstacle avoidance in needle steering surgery using multiple forward looking sensors},
url = {http://dx.doi.org/10.1109/IROS.2018.8594198},
year = {2019}
}

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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - During percutaneous interventions in the brain, puncturing a vessel can cause life-threatening complications. To avoid such a risk, current research has been directed towards the development of steerable needles. However, there is a risk that vessels of a size which is close to or smaller than the resolution of commonly used preoperative imaging modalities (0.59 x 0.59 x 1 mm) would not be detected during procedure planning, with a consequent increase in risk to the patient. In this work, we present a novel ensemble of forward-looking sensors based on laser Doppler flowmetry, which are embedded within a biologically inspired steerable needle to enable vessel detection during the insertion process. Four Doppler signals are used to classify the pose of a vessel in front of the advancing needle with a  high degree of accuracy (2$^{\circ}$ and 0.1 mm RMS errors), where relative measurements between sensors are used to correct for ambiguity. By using a robotic-assisted needle insertion process, and thus a precisely controlled insertion speed, we also demonstrate how the setup can be used to discriminate between tissue bulk motion and vessel motion. In doing so, we describe a sensing apparatus applicable to a variety of needle steering systems, with the potential to eliminate the risk of haemorrhage during percutaneous procedures.
AU  - Virdyawan,V
AU  - Rodriguez,y Baena F
DO  - 10.1109/IROS.2018.8594198
PB  - IEEE
PY  - 2019///
TI  - Vessel pose estimation for obstacle avoidance in needle steering surgery using multiple forward looking sensors
UR  - http://dx.doi.org/10.1109/IROS.2018.8594198
UR  - https://ieeexplore.ieee.org/document/8594198
UR  - http://hdl.handle.net/10044/1/62603
ER  -

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