Publications by year
2022
Russon CL, Vaughan N, Carr ALJ, Pulsford RM, Allen M, Andrews RC (2022). An increase in recording interval in continuous glucose monitors results in the identification of fewer hypoglycaemic episodes but interpolation can help to identify some of these missed episodes.
Diabetic Medicine,
39 Full text.
Russon C, Vaughan N, Pulsford R, Andrews R, Allen M (2022). Glycaemic events during exercise can be effectively predicted with machine learning using only start glucose and duration. European Association for the Study of Diabetes (EASD). 19th - 23rd Sep 2022.
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2021
Russon C, Vaughan N, Andrews R (2021). Accuracy Analysis of Interpolation Methods. on Flash Glucose Monitoring Data.
Diabetic Medicine,
Volume 38(Issue S1).
Abstract:
Accuracy Analysis of Interpolation Methods. on Flash Glucose Monitoring Data
Background: Flash glucose monitoring is increasingly used by people with type 1 diabetes. Flash glucose monitoring data contains gaps between measurements with measurements only measured every 15 minutes. Estimating what the glucose is between scan readings might lead to more accurate metrics such as time in range.
Aims: to determine if statistical interpolation methods could be used to estimate what the blood glucose (BG) was between scan readings, at various blood glucose levels and different times of day, at rest and during exercise.
Methods: 36 people with Type 1 diabetes training for the Swansea half marathon completed a training diary and wore a Flash-glucose-monitor for 8 weeks prior to the event. Missing intervals within data were identified and multiple interpolation algorithms were applied to estimate BG values during gaps. Predictions were verified using manual flash measurements.
Results: Interpolated BGs correlation (R2) with manual scanned readings were very good. However, the best method for doing the interpolation varied by time-of-day, blood glucose levels and on whether exercising or not. In addition, the variations around the estimate (RMSE) also varied by time-of-day, blood glucose levels and whether exercising or not. For example RMSE was often lower during exercise compared to at rest, with higher RMSE during day than at night.
Discussion: Interpolation might improve the accuracy of time in range of flash glucose monitoring. However different methods of interpolation will be needed to be used for different times of the day, for different blood glucoses and whether exercising or at rest.
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Vaughan N (2021). Chair’s introduction. Visualisation of Genetic and Evolutionary Computation (VizGEC), GECCO 2021. 10th - 14th Jul 2021.
Russon C, Vaughan N, Andrews R (2021). Interpolation of Fgm Data for the Improved Identification of Hypoglycaemic Episodes. Insulin100 Scientific Symposium. 15th Apr - 16th Mar 2021.
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Rees N, Beever L, Vaughan N, Powell C, Fletcher A, John N (2021). Virtual reality training in cardiopulmonary resuscitation in schools.
Journal of Paramedic Practice Full text.
2020
Vaughan N (2020). Chair’s introduction. Visualisation of Genetic and Evolutionary Computation (VizGEC) at GECCO 2020. 8th - 12th Jul 2020.
Vaughan N (2020). Evolving a model of the retina for eyesight loss. Medical applications of Genetic and Evolutionary Computation (MedGEC), GECCO 2020. 8th - 12th Jul 2020.
Vaughan N, Vargiu E, Mariani S, Montagna S, Schumacher M (2020). Healthcare Intelligent Multi Agent Systems.
Journal of Medical Systems,
44, 138-138.
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Vaughan N (2020). Keynote Talk: Evolving Eye Model for Medical Applications. the Evolutionary Computation in Healthcare (TECH2020), World Congress on Computational Intelligence (WCCI 2020). 19th - 24th Jul 2020.
Vaughan N, Rees N, John N, Day T, Dorrington K (2020). ParaVR: a Virtual Reality Training Simulator for Paramedic Skills maintenance.
Journal of Paramedic Practice: the clinical monthly for emergency care professionals,
12(12).
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Vaughan N, Gabrys B (2020). Scoring and assessment in medical VR training simulators with dynamic time series classification.
Engineering Applications of Artificial Intelligence,
94 Full text.
Lee W, Vaughan N, Kim D (2020). Task Allocation into a Foraging Task with a Series of Subtasks in Swarm Robotic System.
IEEE Access,
8, 107549-107561.
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Mediouni M, Madiouni R, Gardner M, Vaughan N (2020). Translational medicine: Challenges and new orthopaedic vision (Mediouni-Model).
Current Orthopaedic Practice,
31(2), 196-200.
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2019
Mediouni M, Kucklick T, Poncet S, Madiouni R, Abouaomar A, Madry H, Cucchiarini M, Chopko B, Vaughan N, Arora M, et al (2019). An overview of thermal necrosis: present and future.
Curr Med Res Opin,
35(9), 1555-1562.
Abstract:
An overview of thermal necrosis: present and future.
Introduction: Many orthopaedic procedures require drilling of bone, especially fracture repair cases. Bone drilling results in heat generation due to the friction between the bone and the drill bit. A high-level of heat generation kills bone cells. Bone cell death results in resorption of bone around bone screws.Methods: We searched in the literature for data on parameters that influence drilling bone and could lead to thermal necrosis. The points of view of many orthopaedists and neurosurgeons based upon on previous practices and clinical experience are presented.Results: Several potential complications that lead to thermal necrosis are discussed and highlighted.Discussion: Even in the face of growing evidence as to the negative effects of heat induction during drilling, simple and effective methods for monitoring and cooling in real-time are not in widespread usage today. For that purpose, we propose some suggestions for the future of bone drilling, taking note of recent advances in autonomous robotics, intelligent systems and computer simulation techniques.Conclusions: These advances in prevention of thermal necrosis during bone drilling surgery are expected to reduce the risk of patient injury and costs for the health service.
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Vaughan N, John N, Rees N (2019). CPR virtual reality training simulator for schools.
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CPR virtual reality training simulator for schools
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Vaughan N (2019). Evolution of Biological Eye in Computer Simulation.
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Evolution of Biological Eye in Computer Simulation
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Vaughan N, John N, Rees N (2019). ParaVR: Paramedic virtual reality training simulator. International Conference on Cyberworlds. 10th - 12th May 2019.
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ParaVR: Paramedic virtual reality training simulator
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2018
Harvey R, Muncey A, Vaughan N (2018). Associating colours with emotions detected in social media tweets. Artificial Intelligence and Simulation of Behaviour (AISB) Convention 2018.
Abstract:
Associating colours with emotions detected in social media tweets
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Vaughan N (2018). Evolution of Neural Networks for Physically Simulated Evolved Virtual Quadruped Creatures.
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Vaughan N (2018). Evolutionary Robot Swarm Cooperative Retrieval.
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Wolfenden A, Vaughan N (2018). How effective is ant colony optimisation at robot path planning.
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How effective is ant colony optimisation at robot path planning
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Vaughan N (2018). Morphogenetic engineering for evolving ant colony pheromone communication.
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Morphogenetic engineering for evolving ant colony pheromone communication
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Vaughan N (2018). Multi-agent reinforcement learning for swarm retrieval with evolving neural network. Conference on Biomimetic and Biohybrid Systems.
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Multi-agent reinforcement learning for swarm retrieval with evolving neural network
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Vaughan N (2018). Swarm Communication by Evolutionary Algorithms.
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2017
Vaughan N, Dubey VN, Hickish T, Cole J, ASME (2017). A SMART DEVICE TO SUBSTITUTE THE NEUROTHESIOMETER.
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Vaughan N, Dubey V (2017). Interpreting Ultrasound Images for Accurate Epidural Needle Insertion.
Journal of Medical Devices, Transactions of the ASME,
11(3) Full text.
Vaughan N, Dubey VN (2017). Interpreting ultrasound images for accurate epidural needle insertion.
Vaughan N, Dubey VN (2017). Monitoring Rehabilitation Parameters in Stroke Patients. International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE 2017). 6th - 9th Aug 2017.
Mediouni M, Schlatterer DR, Khoury A, Von Bergen T, Shetty SH, Arora M, Dhond A, Vaughan N, Volosnikov A (2017). Optimal parameters to avoid thermal necrosis during bone drilling: a finite element analysis.
J Orthop Res,
35(11), 2386-2391.
Abstract:
Optimal parameters to avoid thermal necrosis during bone drilling: a finite element analysis.
The drilling bone may potentially cause excessive frictional heat, which can lead to local bone necrosis. This heat generation and local necrosis has been suggested to contribute to the resorption of bone around the placed screws, ending in loss of screw purchase in the bone and inadvertent loosening and/or the bone-implant construct. In vivo studies on this subject have inherent obstacles not the least of which is controlling the variables and real time bone temperature data acquisition. Theoretical models can be generated using computer software and the inclusion of known constants for the mechanical properties of metal and bone. These known Data points for the variables (drill bit and bone) enables finite element analysis of various bone drilling scenarios. An elastic-plastic three-dimensional (3D) acetabular bone mode was developed and finite element model analysis (FEA) was applied to various simulated drilling procedures. The FEA results clearly indicate that the depth of drilling and the drill speed both have a significant effect on the temperature during drilling procedures. The reduction of the feeding speed leads to a reduction in bone temperature. Our data suggests that reducing the feeding speed regardless of RPMs and pressure applied could be a simple useful and effective way to reduce drilling temperatures. This study is the first step in helping any surgeon who drills bone and places screws to better understand the ideal pressure to apply and drill speed to employ and advance rate to avoid osteonecrosis. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2386-2391, 2017.
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Wee MYK (2017). Quantification of the pressures generated during insertion of an epidural needle in labouring women of varying body mass indices.
International Journal of Clinical Anesthesia and Research, 024-027.
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Vaughan N, Dubey V (2017). Virtual Hip Replacement Simulator for 3D Printed Implants.
Journal of Medical Devices, Transactions of the ASME,
11(3) Full text.
Vaughan N, Dubey VN (2017). Virtual hip replacement simulator for 3D printed implants.
2016
Vaughan N, Dubey VN, Wainwright TW, Middleton RG (2016). A review of virtual reality based training simulators for orthopaedic surgery.
Med Eng Phys,
38(2), 59-71.
Abstract:
A review of virtual reality based training simulators for orthopaedic surgery.
This review presents current virtual reality based training simulators for hip, knee and other orthopaedic surgery, including elective and trauma surgical procedures. There have not been any reviews focussing on hip and knee orthopaedic simulators. A comparison of existing simulator features is provided to identify what is missing and what is required to improve upon current simulators. In total 11 hip replacements pre-operative planning tools were analysed, plus 9 hip trauma fracture training simulators. Additionally 9 knee arthroscopy simulators and 8 other orthopaedic simulators were included for comparison. The findings are that for orthopaedic surgery simulators in general, there is increasing use of patient-specific virtual models which reduce the learning curve. Modelling is also being used for patient-specific implant design and manufacture. Simulators are being increasingly validated for assessment as well as training. There are very few training simulators available for hip replacement, yet more advanced virtual reality is being used for other procedures such as hip trauma and drilling. Training simulators for hip replacement and orthopaedic surgery in general lag behind other surgical procedures for which virtual reality has become more common. Further developments are required to bring hip replacement training simulation up to date with other procedures. This suggests there is a gap in the market for a new high fidelity hip replacement and resurfacing training simulator.
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Vaughan N, Gabrys B, Dubey VN (2016). An overview of self-adaptive technologies within virtual reality training.
Computer Science Review,
22, 65-87.
Abstract:
An overview of self-adaptive technologies within virtual reality training
This overview presents the current state-of-the-art of self-adaptive technologies within virtual reality (VR) training. Virtual reality training and assessment is increasingly used for five key areas: medical, industrial & commercial training, serious games, rehabilitation and remote training such as Massive Open Online Courses (MOOCs). Adaptation can be applied to five core technologies of VR including haptic devices, stereo graphics, adaptive content, assessment and autonomous agents. Automation of VR training can contribute to automation of actual procedures including remote and robotic assisted surgery which reduces injury and improves accuracy of the procedure. Automated haptic interaction can enable tele-presence and virtual artefact tactile interaction from either remote or simulated environments. Automation, machine learning and data driven features play an important role in providing trainee-specific individual adaptive training content. Data from trainee assessment can form an input to autonomous systems for customised training and automated difficulty levels to match individual requirements. Self-adaptive technology has been developed previously within individual technologies of VR training. One of the conclusions of this research is that while it does not exist, an enhanced portable framework is needed and it would be beneficial to combine automation of core technologies, producing a reusable automation framework for VR training.
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Vaughan N, Gabrys B (2016). Comparing and combining time series trajectories using Dynamic Time Warping.
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS: PROCEEDINGS OF THE 20TH INTERNATIONAL CONFERENCE KES-2016,
96, 474-483.
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Vaughan N, Dubey VN, ASME (2016). HIP REPLACEMENT SIMULATOR FOR PREDICTING DISLOCATION RISK.
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Mediouni M, Vaughan N, Shetty SH, Arora M, Volosnikov A, Khoury A (2016). How Challenging is the “Scaling Up” of Orthopaedic Simulation?. Open Journal of Orthopedics and Rheumatology, 1(1), 012-014.
Vaughan N, Dubey VN, Wee MYK, Isaacs R (2016). Mechanism for Adaptive Virtual Reality Feedback.
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Vaughan N, Dubey V, Hickish T, Cole J (2016). Neuropathy Assessment Device.
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Neuropathy Assessment Device
Neuropathy Assessment Device
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Vaughan N (2016). Visual Navigation in Simulated Pigeons.
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Vaughan N (2016). Visual navigation in simulated pigeons.
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Visual navigation in simulated pigeons
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2015
R I, MYK W, Dubey VN, N V (2015). A survey of trainees’ perspectives on epidural training in the United Kingdom. Global Anesthesia and Perioperative Medicine, 1(4).
Vaughan N, Dubey VN, Wainwright TW, Middleton RG, IEEE (2015). Can Virtual-Reality Simulators Assess Experience and Skill Level of Orthopaedic Surgeons?.
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Vaughan N, Dubey VN, Wainwright TW, Middleton RG, IEEE (2015). Does Virtual-Reality Training on Orthopaedic Simulators Improve Performance in the Operating Room?.
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Vaughan N, Dubey VN (2015). Surface Mesh Density Extraction of Orthopedic Magnetic Resonance Image with Hue Saturation Value Filtering.
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Vaughan N, IEEE (2015). Swapping Algorithm and Meta-heuristic Solutions for Combinatorial Optimization n-Queens Problem.
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2014
Vaughan N, Dubey VN, Wee MYK, Isaacs R, ASME (2014). ARTIFICIAL NEURAL NETWORK TO PREDICT PATIENT BODY CIRCUMFERENCES AND LIGAMENT THICKNESSES.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R, ASME (2014). BODY SHAPE AND SIZE MODELLING USING REGRESSION ANALYSIS AND NEURAL NETWORK PREDICTION.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R (2014). Development of Epidural Simulators: Towards Hybrid Virtual Reality Training. In (Ed)
Virtual Reality: Technologies, Medical Applications and Challenges, 83-124.
Abstract:
Development of Epidural Simulators: Towards Hybrid Virtual Reality Training
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Vaughan N, Dubey VN, Wee MYK, Isaacs R (2014). Devices for accurate placement of epidural Tuohy needle for Anaesthesia administration.
MECHANICAL SCIENCES,
5(1), 1-6.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R (2014). Epidural Pressure Measurements from Various BMI Obstetric Patients.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R, ASME (2014). HETEROGENEOUS TISSUE LAYER DEFORMATION WITH HAPTIC FEEDBACK.
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Vaughan N, Dubey V, Wee MYK, Isaacs R (2014). Hybrid Epidural Simulator: Augmented Physical Simulation with Virtual Reality Underlays. In (Ed)
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Hybrid Epidural Simulator: Augmented Physical Simulation with Virtual Reality Underlays
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Vaughan N, Dubey VN, Wee MYK, Isaacs R, ASME (2014). IN-VIVO OBSTETRIC PRESSURE MEASUREMENTS FOR PATIENT-SPECIFIC EPIDURAL SIMULATOR.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R (2014). In-Vivo Obstetric Pressure Measurements for Patient-Specific Epidural Simulator. Volume 1A: 34th Computers and Information in Engineering Conference.
Isaacs R, Wee M, Parker B, Dubey V, Vaughan N (2014). Measurement of epidural insertion pressures in labouring women of varying body mass indices and imaging of the lumbar spine to develop a high-fidelity epidural simulator for training.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R (2014). Parametric model of human body shape and ligaments for patient-specific epidural simulation.
Artif Intell Med,
62(2), 129-140.
Abstract:
Parametric model of human body shape and ligaments for patient-specific epidural simulation.
OBJECTIVE: This work is to build upon the concept of matching a person's weight, height and age to their overall body shape to create an adjustable three-dimensional model. A versatile and accurate predictor of body size and shape and ligament thickness is required to improve simulation for medical procedures. A model which is adjustable for any size, shape, body mass, age or height would provide ability to simulate procedures on patients of various body compositions. METHODS: Three methods are provided for estimating body circumferences and ligament thicknesses for each patient. The first method is using empirical relations from body shape and size. The second method is to load a dataset from a magnetic resonance imaging (MRI) scan or ultrasound scan containing accurate ligament measurements. The third method is a developed artificial neural network (ANN) which uses MRI dataset as a training set and improves accuracy using error back-propagation, which learns to increase accuracy as more patient data is added. The ANN is trained and tested with clinical data from 23,088 patients. RESULTS: the ANN can predict subscapular skinfold thickness within 3.54 mm, waist circumference 3.92 cm, thigh circumference 2.00 cm, arm circumference 1.21 cm, calf circumference 1.40 cm, triceps skinfold thickness 3.43 mm. Alternative regression analysis method gave overall slightly less accurate predictions for subscapular skinfold thickness within 3.75 mm, waist circumference 3.84 cm, thigh circumference 2.16 cm, arm circumference 1.34 cm, calf circumference 1.46 cm, triceps skinfold thickness 3.89 mm. These calculations are used to display a 3D graphics model of the patient's body shape using OpenGL and adjusted by 3D mesh deformations. CONCLUSIONS: a patient-specific epidural simulator is presented using the developed body shape model, able to simulate needle insertion procedures on a 3D model of any patient size and shape. The developed ANN gave the most accurate results for body shape, size and ligament thickness. The resulting simulator offers the experience of simulating needle insertions accurately whilst allowing for variation in patient body mass, height or age.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R, ASME (2014). SPINE FLEXION AND EXTENSION MODEL FOR EPIDURAL SIMULATOR.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R (2014). Synthetic Methods for Ultrasound-Guided Epidural Insertion Simulation.
JOURNAL OF MEDICAL DEVICES-TRANSACTIONS OF THE ASME,
8(2).
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Vaughan N, Dubey VN, Wee MYK, Isaacs R, ASME (2014). VIDEO TRACKING OF TUOHY NEEDLE FOR AN ENHANCED EPIDURAL SIMULATOR USER INTERFACE.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R (2014). Virtual Reality Simulation Based Assessment Objectives for Epidural Training.
JOURNAL OF MEDICAL DEVICES-TRANSACTIONS OF THE ASME,
8(2).
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2013
Vaughan N, Dubey VN, Wee MYK, Isaacs R (2013). A review of epidural simulators: where are we today?.
Med Eng Phys,
35(9), 1235-1250.
Abstract:
A review of epidural simulators: where are we today?
Thirty-one central neural blockade simulators have been implemented into clinical practice over the last thirty years either commercially or for research. This review aims to provide a detailed evaluation of why we need epidural and spinal simulators in the first instance and then draws comparisons between computer-based and manikin-based simulators. This review covers thirty-one simulators in total; sixteen of which are solely epidural simulators, nine are for epidural plus spinal or lumbar puncture simulation, and six, which are solely lumbar puncture simulators. All hardware and software components of simulators are discussed, including actuators, sensors, graphics, haptics, and virtual reality based simulators. The purpose of this comparative review is to identify the direction for future epidural simulation by outlining necessary improvements to create the ideal epidural simulator. The weaknesses of existing simulators are discussed and their strengths identified so that these can be carried forward. This review aims to provide a foundation for the future creation of advanced simulators to enhance the training of epiduralists, enabling them to comprehensively practice epidural insertion in vitro before training on patients and ultimately reducing the potential risk of harm.
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Vaughan N, Dubey V, Wee M, Isaacs R (2013). Biomedical Engineering in Epidural Anaesthesia Research. In Andrade A, Pereira AA, Naves ELM, Soares AB (Eds.)
Practical Applications in Biomedical Engineering, BoD – Books on Demand.
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Biomedical Engineering in Epidural Anaesthesia Research
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Vaughan N, Dubey VN, Wee MYK, Isaacs R (2013). Epidural Simulation for Patients of Various BMI and Body Shapes.
JOURNAL OF MEDICAL DEVICES-TRANSACTIONS OF THE ASME,
7(3).
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Vaughan N, Dubey VN, Wee MYK, Isaacs R (2013). Real-time length measurement of epidural Tuohy needle during insertion.
IET SCIENCE MEASUREMENT & TECHNOLOGY,
7(4), 215-222.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R (2013). Towards a realistic in vitro experience of epidural Tuohy needle insertion.
Proc Inst Mech Eng H,
227(7), 767-777.
Abstract:
Towards a realistic in vitro experience of epidural Tuohy needle insertion.
The amount of pressure exerted on the syringe and the depth of needle insertion are the two key factors for successfully carrying out epidural procedure. The force feedback from the syringe plunger is helpful in judging the loss of pressure, and the depth of the needle insertion is crucial in identifying when the needle is precisely placed in the epidural space. This article presents the development of two novel wireless devices to measure these parameters to precisely guide the needle placement in the epidural space. These techniques can be directly used on patients or implemented in a simulator for improving the safety of procedure. A pilot trial has been conducted to collect depth and pressure data with the devices on a porcine cadaver. These measurements are then combined to accurately configure a haptic device for creating a realistic in vitro experience of epidural needle insertion.
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2012
Vaughan N, Dubey VN, Wee MYK, Isaacs R (2012). Advanced epidural simulator with 3d flexible spine and haptic interface. Journal of Medical Devices, Transactions of the ASME, 6(1), 1-1.
Vaughan N, Dubey VN, Wee MYK, Isaacs R (2012). Epidural needle length measurement by video processing.
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Epidural needle length measurement by video processing
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Vaughan N, Dubey VN, Wee MYK, Isaacs R, ASME (2012). HAPTIC INTERFACE ON MEASURED DATA FOR EPIDURAL SIMULATION.
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Vaughan N, Dubey VN, Wee MYK, Isaacs R, ASME (2012). VIRTUAL REALITY BASED ENHANCED VISUALIZATION OF EPIDURAL INSERTION.
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