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Mechatronics in Medicine | MiM Lab

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.

Why is it important

The integration of mechatronics into medicine addresses critical challenges in modern healthcare by enhancing the precision, safety, and efficiency of surgical procedures. Traditional surgeries often involve significant risks and extended recovery times. By developing robotic systems that offer greater accuracy and control, we aim to minimise these risks and reduce invasiveness. Our research contributes to the advancement of minimally invasive techniques, which are essential for improving patient outcomes and optimising healthcare resources. Furthermore, our work supports the training of the next generation of surgeons, equipping them with cutting-edge tools and methodologies that reflect the evolving landscape of medical technology.

How can it benefit patients

Patients stand to gain significantly from the innovations developed at the Mechatronics in Medicine Laboratory. Our robotic systems are designed to perform surgeries with enhanced precision, leading to fewer complications and faster recovery times. Minimally invasive procedures facilitated by our technologies result in less postoperative pain and reduced scarring, improving the overall patient experience. Additionally, the increased accuracy of our systems can lead to better surgical outcomes, such as more complete tumour removals or more precise joint replacements, thereby improving long-term health prospects. By pushing the boundaries of medical robotics, we strive to make advanced surgical care more accessible and effective for patients worldwide.

Meet the team

Dr Daniel Bautista Salinas
Research Associate

Dr Kaiwen Chen
Research Associate

Dr Zejian Cui
Research Associate

Mr Connor Daly
Research Postgraduate

Emeritus Professor Brian L Davies FREng
Emeritus Professor

Dr Hisham M Iqbal
Honorary Research Associate

Mr Alex Tian Jie Ranne
Casual - Lib. Ass, Clerks & Gen. Admin Assistants

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{Secoli:2016:10.1109/BIOROB.2016.7523603,
author = {Secoli, R and Rodriguez, y Baena F},
doi = {10.1109/BIOROB.2016.7523603},
publisher = {IEEE},
title = {Adaptive path-following control for bio-inspired steerable needles},
url = {http://dx.doi.org/10.1109/BIOROB.2016.7523603},
year = {2016}
}

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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Needle steering systems have shown potential ad-vantages in minimally invasive surgery in soft-tissue due to theirability to reach deep-seated targets while avoiding obstacles. Ingeneral, the control strategies employed to drive the insertionuse  simplified  kinematic  models,  providing  limited  control  ofthe trajectory between an entry site and a deep seated targetin  cases  of  unmodelled  tissue-needle  dynamics.  In  this  work,we present the first Adaptive Path-Following (APF) controllerfor a bio-inspired multi-part needle, able to steer along three-dimensional (3D) paths within a compliant medium by meansof the cyclical motion of interlocked segments and without theneed for duty-cycle spinning along the insertion axis.The control strategy is outlined in two parts: a high-level con-troller, which provides driving commands to follow a predefined3D path smoothly; and a low-level controller, able to counteractunmodelled  tissue-needle  nonlinearities  and  kinematic  modeluncertainties. A simulation that mimics the needle’s mechanicalbehavior during insertion is achieved by using an ExperimentalFitting  Model  (EFM),  obtained  from  previous  experimentaltrials. The Simulation results demonstrate the robustness andadaptability of the proposed control strategy.
AU  - Secoli,R
AU  - Rodriguez,y Baena F
DO  - 10.1109/BIOROB.2016.7523603
PB  - IEEE
PY  - 2016///
TI  - Adaptive path-following control for bio-inspired steerable needles
UR  - http://dx.doi.org/10.1109/BIOROB.2016.7523603
ER  -

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