In this section
We use perceptual methods, AI, and frugal robotics innovation to deliver transformative diagnostic and treatment solutions.
B415B Bessemer Building
South Kensington Campus
+44 (0)20 3312 5145
The HARMS lab leverages perceptually enabled methodologies, artificial intelligence, and frugal innovation in robotics (such as soft surgical robots) to deliver transformative solutions for diagnosis and treatment. Our research is driven by both problem-solving and curiosity, aiming to build a comprehensive understanding of the actions, interactions, and reactions occurring in the operating room. We focus on using robotic technologies to facilitate procedures that are not yet widely adopted, particularly in endoluminal surgery, such as advanced treatments for gastrointestinal cancer.
Mr Amirhosein Alian
Research Postgraduate
Dr James P Avery
Honorary Lecturer
Mr Junhong Chen
Research Postgraduate
Mr Kaizhong Deng
Research Postgraduate
Mr Hanqi LOU
Research Postgraduate
Dr George Mylonas BEng, MSc, DIC, PhD
Senior Lecturer in Robotics and Technology in Cancer
Dr Adrian Rubio Solis
Research Associate in Sensing and Machine Learning
Dr Jianlin Yang
Research Associate
Mr Zhangxi Zhou
Research Postgraduate
@article{Almukhtar:2024:10.1097/SLA.0000000000006370,
author = {Almukhtar, A and Caddick, V and Naik, R and Goble, M and Mylonas, G and Darzi, A and Orihuela-Espina, F and Leff, D},
doi = {10.1097/SLA.0000000000006370},
journal = {Annals of Surgery},
title = {Objective assessment of cognitive workload in surgery: a systematic review},
url = {http://dx.doi.org/10.1097/SLA.0000000000006370},
year = {2024}
}
TY - JOUR
AB - Objective: To systematically review technologies that objectively measure CWL in surgery, assessing their psychometric and methodological characteristics.Summary Background Data: Surgical tasks involving concurrent clinical decision-making and the safe application of technical and non-technical skills require a substantial cognitive demand and resource utilization. Cognitive overload leads to impaired clinical decision-making and performance decline. Assessing cognitive workload (CWL) could enable interventions to alleviate burden and improve patient safety.Methods: Ovid MEDLINE, OVID Embase, the Cochrane Library and IEEE Xplore databases were searched from inception to August 2023. Full-text, peer-reviewed original studies in a population of surgeons, anesthesiologists or interventional radiologists were considered, with no publication date constraints. Study population, task paradigm, stressor, Cognitive Load Theory (CLT) domain, objective and subjective parameters, statistical analysis and results were extracted. Studies were assessed for a) definition of CWL, b) details of the clinical task paradigm, and c) objective CWL assessment tool. Assessment tools were evaluated using psychometric and methodological characteristics.Results: 10790 studies were identified; 9004 were screened; 269 full studies were assessed for eligibility, of which 67 met inclusion criteria. The most widely used assessment modalities were autonomic (32 eye studies and 24 cardiac). Intrinsic workload (e.g. task complexity) and germane workload (effect of training or expertize) were the most prevalent designs investigated. CWL was not defined in 30 of 67 studies (44.8%). Sensitivity was greatest for neurophysiological instruments (100% EEG, 80% fNIRS); and across modalities accuracy increased with multi-sensor recordings. Specificity was limited to cardiac and ocular metrics, and was found to be sub-optimal (50% and 66.67%). Cardiac sensors were the least intrusive, with 54.2% of studies cond
AU - Almukhtar,A
AU - Caddick,V
AU - Naik,R
AU - Goble,M
AU - Mylonas,G
AU - Darzi,A
AU - Orihuela-Espina,F
AU - Leff,D
DO - 10.1097/SLA.0000000000006370
PY - 2024///
SN - 0003-4932
TI - Objective assessment of cognitive workload in surgery: a systematic review
T2 - Annals of Surgery
UR - http://dx.doi.org/10.1097/SLA.0000000000006370
UR - http://hdl.handle.net/10044/1/112498
ER -
The Hamlyn Centre
Bessemer Building
South Kensington Campus
Imperial College
London, SW7 2AZ
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