In this section
The MIM Lab develops robotic and mechatronics surgical systems for a variety of procedures.
Prof Ferdinando Rodriguez y Baena
B415C Bessemer Building
South Kensington Campus
+44 (0)20 7594 7046
⇒ X: @fmryb
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.
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.
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.
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
@inproceedings{Matheson:2020:10.1109/iros40897.2019.8967604,
author = {Matheson, E and Secoli, R and Galvan, S and Baena, FRY},
doi = {10.1109/iros40897.2019.8967604},
publisher = {IEEE},
title = {Human-robot visual interface for 3D steering of a flexible, bioinspired needle for neurosurgery},
url = {http://dx.doi.org/10.1109/iros40897.2019.8967604},
year = {2020}
}
TY - CPAPER
AB - Robotic minimally invasive surgery has been a subject of intense research and development over the last three decades, due to the clinical advantages it holds for patients and doctors alike. Particularly for drug delivery mechanisms, higher precision and the ability to follow complex trajectories in three dimensions (3D), has led to interest in flexible, steerable needles such as the programmable bevel-tip needle (PBN). Steering in 3D, however, holds practical challenges for surgeons, as interfaces are traditionally designed for straight line paths. This work presents a pilot study undertaken to evaluate a novel human-machine visual interface for the steering of a robotic PBN, where both qualitative evaluation of the interface and quantitative evaluation of the performance of the subjects in following a 3D path are measured. A series of needle insertions are performed in phantom tissue (gelatin) by the experiment subjects. User could adequately use the system with little training and low workload, and reach the target point at the end of the path with millimeter range accuracy.
AU - Matheson,E
AU - Secoli,R
AU - Galvan,S
AU - Baena,FRY
DO - 10.1109/iros40897.2019.8967604
PB - IEEE
PY - 2020///
TI - Human-robot visual interface for 3D steering of a flexible, bioinspired needle for neurosurgery
UR - http://dx.doi.org/10.1109/iros40897.2019.8967604
UR - https://ieeexplore.ieee.org/document/8967604
ER -
The Hamlyn Centre
Bessemer Building
South Kensington Campus
Imperial College
London, SW7 2AZ
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