Research in surgical robotics has an established track record at Imperial College, and a number of research and commercial surgical robot platforms have been developed over the years. The Hamlyn Centre is a champion for technological innovation and clinical adoption of robotic, minimally invasive surgery. We work in partnership with major industrial leaders in medical devices and surgical robots, as well as developing our own platforms such as the i-Snake® and Micro-IGES platforms. The Da Vinci surgical robot is used extensively for endoscopic radical prostatectomy, hiatal hernia surgery, and low pelvic and rectal surgery, and in 2003, St Mary’s Hospital carried out its first Totally Endoscopic Robotic Coronary Artery Bypass (TECAB).

The major focus of the Hamlyn Centre is to develop robotic technologies that will transform conventional minimally invasive surgery, explore new ways of empowering robots with human intelligence, and develop[ing miniature 'microbots' with integrated sensing and imaging for targeted therapy and treatment. We work closely with both industrial and academic partners in open platforms such as the DVRK, RAVEN and KUKA. The Centre also has the important mission of driving down costs associated with robotic surgery in order to make the technology more accessible, portable, and affordable. This will allow it to be fully integrated with normal surgical workflows so as to benefit a much wider patient population.

The Hamlyn Centre currently chairs the UK Robotics and Autonomous Systems (UK-RAS) Network. The mission of the Network is to to provide academic leadership in Robotics and Autonomous Systems (RAS), expand collaboration with industry and integrate and coordinate activities across the UK Engineering and Physical Sciences Research Council (EPSRC) funded RAS capital facilities and Centres for Doctoral Training (CDTs).


BibTex format

author = {Cameron, SJS and Bodai, Z and Temelkuran, B and Perdones-Montero, A and Bolt, F and Burke, A and Alexander-Hardiman, K and Salzet, M and Fournier, I and Rebec, M and Takáts, Z},
doi = {10.1038/s41598-019-39815-w},
journal = {Scientific Reports},
title = {Utilisation of Ambient Laser Desorption Ionisation Mass Spectrometry (ALDI-MS) improves lipid-based microbial species level identification},
url = {},
volume = {9},
year = {2019}

RIS format (EndNote, RefMan)

AB - The accurate and timely identification of the causative organism of infection is important in ensuring the optimum treatment regimen is prescribed for a patient. Rapid evaporative ionisation mass spectrometry (REIMS), using electrical diathermy for the thermal disruption of a sample, has been shown to provide fast and accurate identification of microorganisms directly from culture. However, this method requires contact to be made between the REIMS probe and microbial biomass; resulting in the necessity to clean or replace the probes between analyses. Here, optimisation and utilisation of ambient laser desorption ionisation (ALDI) for improved speciation accuracy and analytical throughput is shown. Optimisation was completed on 15 isolates of Escherichia coli, showing 5 W in pulsatile mode produced the highest signal-to-noise ratio. These parameters were used in the analysis of 150 clinical isolates from ten microbial species, resulting in a speciation accuracy of 99.4% - higher than all previously reported REIMS modalities. Comparison of spectral data showed high levels of similarity between previously published electrical diathermy REIMS data. ALDI does not require contact to be made with the sample during analysis, meaning analytical throughput can be substantially improved, and further, increases the range of sample types which can be analysed in potential direct-from-sample pathogen detection.
AU - Cameron,SJS
AU - Bodai,Z
AU - Temelkuran,B
AU - Perdones-Montero,A
AU - Bolt,F
AU - Burke,A
AU - Alexander-Hardiman,K
AU - Salzet,M
AU - Fournier,I
AU - Rebec,M
AU - Takáts,Z
DO - 10.1038/s41598-019-39815-w
PY - 2019///
SN - 2045-2322
TI - Utilisation of Ambient Laser Desorption Ionisation Mass Spectrometry (ALDI-MS) improves lipid-based microbial species level identification
T2 - Scientific Reports
UR -
UR -
UR -
VL - 9
ER -