• An overview of thermal necrosis: present and future

      Mediouni, Mohamed; Kucklick, Theodore; Poncet, Sébastien; Madiouni, Riadh; Abouaomar, Amine; Madry, Henning; Cucchiarini, Magali; Chopko, Bohdan; Vaughan, Neil; Arora, Manit; et al. (Informa UK Limited, 2019-05-10)
    • Associating Colours with Emotions Detected in Social Media Tweets

      Harvey, Robert; Muncey, Andrew; Vaughan, Neil; University of Chester (The Society for the Study of Artificial Intelligence and Simulation for Behaviour (AISB), 2018-04-06)
      This project involves two major areas of work, the detection of emotions in text from Twitter posts (tweets), and the association of that emotion with colour. Emotion mining is the field of natural language processing which is concerned with the detection and classification. It is a subfield of semantic analysis which contains both emotion and opinion mining. Both tasks depend on an emotion model to classify detected emotions and to associate a colour depending on the location of the emotion in the model. This research paper demonstrates preliminary results from classification of tweets to assign emotion labels. Also designs are presented for a prototype web interface for displaying the assigned colour and emotion associated with tweets.
    • Colour Coded Emotion Classification in Mental Health Social Media

      Vaughan, Neil; Mulvenna, Maurice; Bond, Raymond; Royal Academy of Engineering; University of Chester (BCS, The Chartered Institute for IT, ACM Proceedings, 2018-07-06)
      This research applies emotion detection to messages from online mental health social media. In particular, this focusses on specialised social media for users to report health or mental health problems. Automatically detecting the emotion in social media can help to rapidly identify any concerning problems which could benefit from intervention aiming to prevent self-harming or suicide. Detecting emotions enables messages to be colour coordinated according to the emotion to enhance the human-computer interaction. A supervised classification method is applied to a labelled dataset and results presented. A prototype user interface system is developed based on detecting emotion, colour coding the message to display detected emotions to users in real-time.
    • Comparing and combining time series trajectories using Dynamic Time Warping

      Vaughan, Neil; Gabrys, Bogdan; Bournemouth University (Elsevier, 2016-09-04)
      This research proposes the application of dynamic time warping (DTW) algorithm to analyse multivariate data from virtual reality training simulators, to assess the skill level of trainees. We present results of DTW algorithm applied to trajectory data from a virtual reality haptic training simulator for epidural needle insertion. The proposed application of DTW algorithm serves two purposes, to enable (i) two trajectories to be compared as a similarity measure and also enables (ii) two or more trajectories to be combined together to produce a typical or representative average trajectory using a novel hierarchical DTW process. Our experiments included 100 expert and 100 novice simulator recordings. The data consists of multivariate time series data-streams including multi-dimensional trajectories combined with force and pressure measurements. Our results show that our proposed application of DTW provides a useful time-independent method for (i) comparing two trajectories by providing a similarity measure and (ii) combining two or more trajectories into one, showing higher performance compared to conventional methods such as linear mean. These results demonstrate that DTW can be useful within virtual reality training simulators to provide a component in an automated scoring and assessment feedback system.
    • Device to accurately place Epidural Tuohy needle for Anesthesia Administration

      Vaughan, Neil; Dubey, Venketesh N.; Wee, Michael Y. K.; Isaacs, Richard; Bournemouth University; Poole Hospital NHS Foundation Trust (Copernicus Publications, 2014-01-02)
      The aim of this project is to design two sterile devices for epidural needle insertion which can measure in real time (i) the depth of needle tip during insertion and (ii) interspinous pressure changes through a pressure measurement device as the epidural needle is advanced through the tissue layers. The length measurement device uses a small wireless camera with video processing computer algorithms which can detect and measure the moving needle. The pressure measurement device uses entirely sterile componenets including a pressure transducer to accurately measure syringe saline in mm Hg. The data from these two devices accurately describe a needle insertion allowing comparison or review of insertions. The data was then cross-referenced to pre-measured data from MRI or ultrasound scan to identify how ligemant thickness correlates to our measured depth and pressure data. The developed devices have been tested on a porcine specimen during insertions performed by experienced anaesthetists. We have obtained epidural pressures for each ligament and demonstrated functionality of our devices to measure pressure and depth of epidural needle during insertion. This has not previously been possible to monitor in real-time. The benefits of these devices are (i) to provide an alternative method to identify correct needle placement during the procedure on real patients. (ii) The data describing the speed, depth and pressure during insertion can be used to configure an epidural simulator, simulating the needle insertion procedure. (iii) Our pressure and depth data can be compared to pre-measured MRI and ultrasound to identify previously unknown links between epidural pressure and depth with BMI, obesity and body shapes.
    • Evolution of Neural Networks for Physically Simulated Evolved Virtual Quadruped Creatures

      Vaughan, Neil; Royal Academy of Engineering; University of Chester (Springer-Verlag, 2018-07-07)
      This work develops evolved virtual creatures (EVCs) using neuroevolution as the controller for movement and decisions within a 3D physics simulated environ-ment. Previous work on EVCs has displayed various behaviour such as following a light source. This work is focused on complexifying the range of behaviours available to EVCs. This work uses neuroevolution for learning specific actions combined with other controllers for making higher level decisions about which action to take in a given scenario. Results include analysis of performance of the EVCs in simulated physics environment. Various controllers are compared including a hard coded benchmark, a fixed topology feed forward artificial neural network and an evolving ANN subjected to neuroevolution by applying mutations in both topology and weights. The findings showed that both fixed topology ANNs and neuroevolution did successfully control the evolved virtual creatures in the distance travelling task.
    • Evolutionary Robot Swarm Cooperative Retrieval

      Vaughan, Neil; Royal Academy of Engineering; University of Chester (Springer, 2018-07-07)
      In nature bees and leaf-cutter ants communicate to improve cooperation during food retrieval. This research aims to model communication in a swarm of auton-omous robots. When food is identified robot communication is emitted within a limited range. Other robots within the range receive the communication and learn of the location and size of the food source. The simulation revealed that commu-nication improved the rate of cooperative food retrieval tasks. However a counter-productive chain reaction can occur when robots repeat communications from other robots causing cooperation errors. This can lead to a large number of robots travelling towards the same food source at the same time. The food becomes de-pleted, before some robots have arrived. Several robots continue to communicate food presence, before arriving at the food source to find it gone. Nature-inspired communication can enhance swarm behaviour without requiring a central control-ler and may be useful in autonomous drones or vehicles.
    • Haptic feedback from human tissues of various stiffness and homogeneity.

      Vaughan, Neil; Dubey, Venketesh N.; Wee, Michael Y. K.; Isaacs, Richard; Bournemouth University; Poole Hospital NHS Foundation Trust (Techno-Press, 2014-07-01)
      This work presents methods for haptic modelling of soft and hard tissue with varying stiffness. The model provides visualization of deformation and calculates force feedback during simulated epidural needle insertion. A spring-mass-damper (SMD) network is configured from magnetic resonance image (MRI) slices of patient’s lumbar region to represent varying stiffness throughout tissue structure. Reaction force is calculated from the SMD network and a haptic device is configured to produce a needle insertion simulation. The user can feel the changing forces as the needle is inserted through tissue layers and ligaments. Methods for calculating the force feedback at various depths of needle insertion are presented. Voxelization is used to fill ligament surface meshes with spring mass damper assemblies for simulated needle insertion into soft and hard tissues. Modelled vertebrae cannot be pierced by the needle. Graphs were produced during simulated needle insertions to compare the applied force to haptic reaction force. Preliminary saline pressure measurements during Tuohy epidural needle insertion are also used as a basis for forces generated in the simulation.
    • How effective is Ant Colony Optimisation at Robot Path Planning

      Wolfenden, A.; Vaughan, Neil; University of Chester (The Society for the Study of Artificial Intelligence and Simulation for Behaviour (AISB), 2018-04-06)
      This project involves investigation of the problem robot path planning using ant colony optimisation heuristics to construct the quickest path from the starting point to the end. The project has developed a simulation that successfully simulates as well as demonstrates visually through a graphical user interface, robot path planning using ant colony optimisation. The simulation shows an ability to traverse an unknown environment from a start point to an end and successfully construct a route for others to follow both when the terrain is dynamic and static
    • Morphogenetic Engineering For Evolving Ant Colony Pheromone Communication

      Vaughan, Neil; University of Chester (The Society for the Study of Artificial Intelligence and Simulation for Behaviour (AISB), 2018-04-06)
      This research investigates methods for evolving swarm communication in a simulated colony of ants using pheromone when foriaging for food. This research implemented neuroevolution and obtained the capability to learn pheromone communication autonomously. Building on previous literature on pheromone communication, this research applies evolution to adjust the topology and weights of an artificial neural network which controls the ant behaviour. Comparison of performance is made between a hard-coded benchmark algorithm, a fixed topology ANN and neuroevolution of the ANN topology and weights. The resulting neuroevolution produced a neural network which was successfully evolved to achieve the task objective, to collect food and return it to the nest.
    • Multi-Agent Reinforcement Learning for Swarm Retrieval with Evolving Neural Network

      Vaughan, Neil; Royal Academy of Engineering; University of Chester (Springer-Verlag,, 2018-07-07)
      This research investigates methods for evolving swarm communica-tion in a sim-ulated colony of ants using pheromone when foriaging for food. This research implemented neuroevolution and obtained the capability to learn phero-mone communication autonomously. Building on previous literature on phero-mone communication, this research applies evolution to adjust the topology and weights of an artificial neural network (ANN) which controls the ant behaviour. Compar-ison of performance is made between a hard-coded benchmark algorithm (BM1), a fixed topology ANN and neuroevolution of the ANN topology and weights. The resulting neuroevolution produced a neural network which was suc-cessfully evolved to achieve the task objective, to collect food and return it to a location.
    • An overview of self-adaptive technologies within virtual reality training

      Vaughan, Neil; Gabrys, Bogdan; Dubey, Venketesh; University of Chester
      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.
    • An overview of thermal necrosis: present and future

      Mediouni, M.; Kucklick, T.; Poncet, S.; Madiouni, R.; Abouaomar, A.; Madry, H.; Cucchiarini, M.; Chopko, B.; Vaughan, Neil; Arora, M.; et al. (Taylor & Francis, 2019-05-10)
      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. Materials and 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 are discussed and highlighted that lead to thermal necrosis. 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.
    • Parametric model of human body shape and ligaments for patient-specific epidural simulation

      Vaughan, Neil; Dubey, Venketesh N.; Wee, Michael Y. K.; Isaacs, Richard; Bournemouth University; Poole Hospital NHS Foundation Trust (Elsevier, 2014-09-04)
      Objective: This work builds 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 scan (MRI) 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 23088 patients. Results: The ANN can predict subscapular skinfold thickness within 3.54mm, waist circumference 3.92cm, thigh circumference 2.00cm, arm circumference 1.21cm, calf circumference 1.40cm, triceps skinfold thickness 3.43mm. Alternative regression analysis method gave overall slightly less accurate predictions for subscapular skinfold thickness within 3.75mm, waist circumference 3.84cm, thigh circumference 2.16cm, arm circumference 1.34cm, calf circumference 1.46cm, triceps skinfold thickness 3.89mm. 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.
    • ParaVR: A Virtual Reality Training Simulator for Paramedic Skills maintenance

      Rees, Nigel; Dorrington, Keith; Rees, Lloyd; Day, Thomas W; Vaughan, Neil; John, Nigel W; Welsh Ambulance Services NHS Trust, University of Chester
      Background, Virtual Reality (VR) technology is emerging as a powerful educational tool which is used in medical training and has potential benefits for paramedic practice education. Aim The aim of this paper is to report development of ParaVR, which utilises VR to address skills maintenance for paramedics. Methods Computer scientists at the University of Chester and the Welsh Ambulance Services NHS Trust (WAST) developed ParaVR in four stages: 1. Identifying requirements and specifications 2. Alpha version development, 3. Beta version development 4. Management: Development of software, further funding and commercialisation. Results Needle Cricothyrotomy and Needle Thoracostomy emerged as candidates for the prototype ParaVR. The Oculus Rift head mounted display (HMD) combined with Novint Falcon haptic device was used, and a virtual environment crafted using 3D modelling software, ported (a computing term meaning transfer (software) from one system or machine to another) onto Oculus Go and Google cardboard VR platform. Conclusion VR is an emerging educational tool with the potential to enhance paramedic skills development and maintenance. The ParaVR program is the first step in our development, testing, and scaling up of this technology.
    • Quantification of the pressures generated during insertion of an epidural needle in labouring women of varying body mass indices

      Wee, M. Y. K.; Isaacs, R. A.; Vaughan, Neil; Dubey, V. N.; Parker, B.; University of Chester; Bournemouth University; Poole Hospital NHS Trust; West Hertfordshire NHS Trust; Southampton University Hospital (Heighten Science Publications, 2017-12-01)
      Objective: The primary aim of this study was to measure pressure generated on a Tuohy needle during the epidural procedure in labouring women of varying body mass indices (BMI) with a view of utilising the data for the future development of a high fi delity epidural simulator. High-fi delity epidural simulators have a role in improving training and safety but current simulators lack a realistic experience and can be improved. Methods: This study was approved by the National Research Ethics Service Committee South Central, Portsmouth (REC reference 11/SC/0196). After informed consent epidural needle insertion pressure was measured using a Portex 16-gauge Tuohy needle, loss-of-resistance syringe, a three-way tap, pressure transducer and a custom-designed wireless transmitter. This was performed in four groups of labouring women, stratified according to BMI kg/m2: 18-24.9; 25-34.9; 35-44.9 and >=45. One-way ANOVA was used to compare difference in needle insertion pressure between the BMI groups. A paired t-test was performed between BMI group 18-24.9 and the three other BMI groups. Ultrasound images of the lumbar spine were undertaken prior to the epidural procedure and lumbar magnetic resonance imaging (MRI) was performed within 72h post-delivery. These images will be used in the development of a high fi delity epidural simulator. Results: The mean epidural needle insertion pressure of labouring women with BMI 18-24.9 was 461mmHg; BMI 25-34.9 was 430mmHg; BMI 35-44.9 was 415mmHg and BMI >=45 was 376mmHg, (p=0.52). Conclusion: Although statistically insignifi cant, the study did show a decreasing trend of epidural insertion pressure with increasing body mass indices.
    • Swarm Communication by Evolutionary Algorithms

      Vaughan, Neil; University of Chester (IEEE, 2018-05-27)
      This research has applied evolutionary algorithms to evolve swarm communication. Controllers were evolved for colonies of artificial simulated ants during a food foriaging task which communicate using pheromone. Neuroevolution enables both weights and the topology of the artificial neural networks to be optimized for food foriaging. The developed model results in evolution of ants which communicate using pheromone trails. The ants successfully collect and return food to the nest. The controller has evolved to adjust the strength of pheromone which provides a signal to guide the direction of other ants in the colony by hill climbing strategy. A single ANN controller for ant direction successfully evolved which exhibits many separate skills including food search, pheromone following, food collection and retrieval to the nest.
    • Translational Medicine: Challenges and new orthopaedic vision (Mediouni-Model)

      Mediouni, Mohamed; Madiouni, Riadh; Gardner, Michael; Vaughan, Neil; University of Chester, UK
      Background: In North America and three European countries Translational Medicine (TM) funding has taken center stage as the National Institutes of Health (NIH), for example, has come to recognize that delays are common place in completing clinical trials based upon benchside advancements. Recently, there are several illustrative examples whereby the translation of research had untoward outcomes requiring immediate action. Methods: Focus more on three-dimensional (3D) simulation, biomarkers, and Artificial Intelligence may allow orthopaedic surgeons to predict the ideal practices before orthopaedic surgery. Using the best medical imaging techniques may improve the accuracy and precision of tumor resections. Results: This article is directed at the young surgeon scientist and in particular orthopaedic residents and all other junior physicians in training to help them better understand TM and position themselves in career paths and hospital systems that strive for optimal TM. It serves to hasten the movement of knowledge garnered from the benchside and move it quickly to the bedside. Conclusions: Communication is ongoing in a bidirectional format. It is anticipated that more and more medical Centers and institutions will adopt TM models of healthcare delivery.