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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

@article{Pinzi:2019:10.1007/s11548-019-01923-3,
author = {Pinzi, M and Galvan, S and Rodriguez, y Baena F},
doi = {10.1007/s11548-019-01923-3},
journal = {International Journal of Computer Assisted Radiology and Surgery},
pages = {659--670},
title = {The adaptive hermite fractal tree (AHFT): a novel surgical 3D path planning approach with curvature and heading constraints},
url = {http://dx.doi.org/10.1007/s11548-019-01923-3},
volume = {14},
year = {2019}
}

Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - PurposeIn the context of minimally invasive neurosurgery, steerable needles such as the one developed within the Horizon2020-funded EDEN2020 project (Frasson et al. in Proc Inst Mech Eng Part H J Eng Med 224(6):775–88, 2010.  https://doi.org/10.1243/09544119JEIM663; Secoli and y Baena in IEEE international conference on robotics and automation, 2013) aspire to address the clinical challenge of better treatment for cancer patients. The direct, precise infusion of drugs in the proximity of a tumor has been shown to enhance its effectiveness and diffusion in the surrounding tissue (Vogelbaum and Aghi in Neuro-Oncology 17(suppl 2):ii3–ii8, 2015.  https://doi.org/10.1093/neuonc/nou354). However, planning for an appropriate insertion trajectory for needles such as the one proposed by EDEN2020 is challenging due to factors like kinematic constraints, the presence of complex anatomical structures such as brain vessels, and constraints on the required start and target poses.MethodsWe propose a new parallelizable three-dimensional (3D) path planning approach called Adaptive Hermite Fractal Tree (AHFT), which is able to generate 3D obstacle-free trajectories that satisfy curvature constraints given a specified start and target pose. The AHFT combines the Adaptive Fractal Tree algorithm’s efficiency (Liu et al. in IEEE Robot Autom Lett 1(2):601–608, 2016.  https://doi.org/10.1109/LRA.2016.2528292) with optimized geometric Hermite (Yong and Cheng in Comput Aided Geom Des 21(3):281–301, 2004.  https://doi.org/10.1016/j.cagd.2003.08.003) curves, which are able to handle heading constraints.ResultsSimulated results demonstrate the robustness of the AHFT to perturbations of the target position and target heading. Additionally, a simulated preoperative environment, where the surgeon is able to select a desired entry pose on the patient’s skull, confirms the ability of the method to generate multiple feasible trajectories for a patient-specific case
AU  - Pinzi,M
AU  - Galvan,S
AU  - Rodriguez,y Baena F
DO  - 10.1007/s11548-019-01923-3
EP  - 670
PY  - 2019///
SN  - 1861-6429
SP  - 659
TI  - The adaptive hermite fractal tree (AHFT): a novel surgical 3D path planning approach with curvature and heading constraints
T2  - International Journal of Computer Assisted Radiology and Surgery
UR  - http://dx.doi.org/10.1007/s11548-019-01923-3
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000461349600009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
VL  - 14
ER  -