Computer Vision without Vision : Methods and Applications of Radio and Audio Based SLAM

The central problem of this thesis is estimating receiver-sender node positions from measured receiver-sender distances or equivalent measurements. This problem arises in many applications such as microphone array calibration, radio antenna array calibration, mapping and positioning using ultra-wideband and mapping and positioning using round-trip-time measurements between mobile phones and Wi-Fi-units. Previous research has explored some of these problems, creating minimal solvers for instance, but these solutions lack real world implementation. Due to the nature of using different media, finding reliable receiver-sender distances is tough, with many of the measurements being erroneous or to a worse extent missing. Therefore in this thesis, we explore using minimal solvers to create robust solutions, that encompass small erroneous measurements and work around missing and grossly erroneous measurements.This thesis focuses mainly on Time-of-Arrival measurements using radio technologies such as Two-way-Ranging in Ultra-Wideband and a new IEEE standard 802.11mc found on many WiFi modules. The methods investigated, also related to Computer Vision problems such as Stucture-from-Motion. As part of this thesis, a range of new commercial radio technologies are characterised in terms of ranging in real world enviroments. In doing so, we have shown how these technologies can be used as a more accurate alternative to the Global Positioning System in indoor enviroments. Further to these solutions, more methods are proposed for large scale problems when multiple users will collect the data, commonly known as Big Data. For these cases, more data is not always better, so a method is proposed to try find the relevant data to calibrate large systems

Robust Phase-Based Positioning Using Massive MIMO with Limited Bandwidth

This paper presents a robust phase-based positioningframework using a massive multiple-input multiple-output(MIMO) system. The phase-based distance estimates of MPCstogether with other parameters are tracked with an ExtendedKalman Filter (EKF), the state dimension of which varies withthe birth-death processes of paths. The iterative maximumlikelihoodestimation algorithm (RIMAX) and the modeling ofdense multipath component (DMC) in the framework furtherenhance the quality of parameter tracking by providing anaccurate initial state and the underlying noise covariance.The tracked MPCs are fed into a time-of-arrival (TOA) selfcalibrationpositioning algorithm for simultaneous trajectoryand environment estimation. Throughout the positioning process,no prior knowledge of the surrounding environment andbase station position is needed. The performance is evaluatedwith the measurement of a 2D complex movement, which wasperformed in a sports hall with an antenna array with 128 portsas base station using a standard cellular bandwidth of 40 MHz.The positioning result shows that the mean deviation of theestimated user equipment trajectory from the ground truth is13 cm. In summary, the proposed framework is a promisinghigh-resolution radio-based positioning solution for current andnext generation cellular systems

Global wealth disparities drive adherence to COVID-safe pathways in head and neck cancer surgery

Peer reviewe

Bi-allelic Loss-of-Function CACNA1B Mutations in Progressive Epilepsy-Dyskinesia.

The occurrence of non-epileptic hyperkinetic movements in the context of developmental epileptic encephalopathies is an increasingly recognized phenomenon. Identification of causative mutations provides an important insight into common pathogenic mechanisms that cause both seizures and abnormal motor control. We report bi-allelic loss-of-function CACNA1B variants in six children from three unrelated families whose affected members present with a complex and progressive neurological syndrome. All affected individuals presented with epileptic encephalopathy, severe neurodevelopmental delay (often with regression), and a hyperkinetic movement disorder. Additional neurological features included postnatal microcephaly and hypotonia. Five children died in childhood or adolescence (mean age of death: 9 years), mainly as a result of secondary respiratory complications. CACNA1B encodes the pore-forming subunit of the pre-synaptic neuronal voltage-gated calcium channel Cav2.2/N-type, crucial for SNARE-mediated neurotransmission, particularly in the early postnatal period. Bi-allelic loss-of-function variants in CACNA1B are predicted to cause disruption of Ca2+ influx, leading to impaired synaptic neurotransmission. The resultant effect on neuronal function is likely to be important in the development of involuntary movements and epilepsy. Overall, our findings provide further evidence for the key role of Cav2.2 in normal human neurodevelopment.MAK is funded by an NIHR Research Professorship and receives funding from the Wellcome Trust, Great Ormond Street Children's Hospital Charity, and Rosetrees Trust. E.M. received funding from the Rosetrees Trust (CD-A53) and Great Ormond Street Hospital Children's Charity. K.G. received funding from Temple Street Foundation. A.M. is funded by Great Ormond Street Hospital, the National Institute for Health Research (NIHR), and Biomedical Research Centre. F.L.R. and D.G. are funded by Cambridge Biomedical Research Centre. K.C. and A.S.J. are funded by NIHR Bioresource for Rare Diseases. The DDD Study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute (grant number WT098051). We acknowledge support from the UK Department of Health via the NIHR comprehensive Biomedical Research Centre award to Guy's and St. Thomas' National Health Service (NHS) Foundation Trust in partnership with King's College London. This research was also supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre. J.H.C. is in receipt of an NIHR Senior Investigator Award. The research team acknowledges the support of the NIHR through the Comprehensive Clinical Research Network. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, Department of Health, or Wellcome Trust. E.R.M. acknowledges support from NIHR Cambridge Biomedical Research Centre, an NIHR Senior Investigator Award, and the University of Cambridge has received salary support in respect of E.R.M. from the NHS in the East of England through the Clinical Academic Reserve. I.E.S. is supported by the National Health and Medical Research Council of Australia (Program Grant and Practitioner Fellowship)

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Simultaneous Reconstruction of Respiratory and Cardiac Motion from Cine Magnetic Resonance Imaging

Cardiovascular diseases are currently the leading cause of death in the world, which killed nearly 17 million people in 2011. For this reason, research in Cardiovascular diseases are of the up-most importance. In this thesis, real-time Cardiac Magnetic Resonance Imaging data is used to create simulated cardiac cycles for multiple phases of the respiratory cycle. By exploring image classification of both cardiac and respiratory cycles with a combination of cycle detection methods (Fast Fourier Transforms, Watershed Segmentation, K-means and locating maximas and minimas) and using a RANSAC method for robustness, interpolated volumes for each respiratory cycle can be created. The use of different interpolation methods are also explored to discover how to produce the best results. In conclusion a Monotonic Piecewise Cubic Spline Interpolation in combination with the use of an optimisation method, to select the most suitable images, proved to be the most accurate method to produce simulated cardiac cycles. The ejection fraction obtained at expiration, from the simulated cardiac cycle, has a value of 55.6962 +/- 1.6199% which is within the current standard normal range of 55-70\% determined at the same respiratory phase

Robust Time-of-Arrival Self Calibration with Missing Data and Outliers

The problem of estimating receiver-sender node positionsfrom measured receiver-sender distances is a key issue indifferent applications such as microphone array calibration, radioantenna array calibration, mapping and positioning using ultrawidebandand mapping and positioning using round-trip-timemeasurements between mobile phones and Wi-Fi-units. Thanks torecent research in this area we have an increased understandingof the geometry of this problem. In this paper, we study theproblem of missing information and the presence of outliers inthe data. We propose a novel hypothesis and test frameworkthat efficiently finds initial estimates of the unknown parametersand combine such methods with optimization techniques toobtain accurate and robust systems. The proposed systems areevaluated against current state-of-the-art methods on a large setof benchmark tests. This is evaluated further on Wi-Fi roundtriptime and ultra-wideband measurements to give a realisticexample of self calibration for indoor localization

Towards Real-time Time-of-Arrival Self-Calibration using Ultra-Wideband Anchors

Indoor localisation is a currently a key issue, from robotics to the Internet of Things. With hardware advancements making Ultra-Wideband devices more accurate and low powered (potentially even passive), this unlocks the potential of having such devices in common place around factories and homes, enabling an alternative method of navigation. Therefore, anchor calibration indoors becomes a key problem in order to implement these devices efficiently and effectively. In this paper, we study the possibility for sequentially gathering Ultra-Wideband Time-of-Arrival measurements and using previously studied robust solvers, merge solutions together in order to calculate anchor positions in 3D in real-time. Here it is assumed that there is no prior knowledge of the anchor positions. This is then validated using Ultra-Wideband Time-of-Arrival data gathered by a Bitcraze Crazyflie quadcopter in 2D motion, 3D motion and full flight

Quality of Academic Writing for Engineering Students at Lund University

The development of good writing skills is fundamental not only to publish scientific results, but also to have a deeper understanding of complex subjects. However reports from the Swedish Higher Education Authority from 2012-2015 suggest that engineering students at Lund University have unsatisfactory academic writing skills. Our paper investigates how students of the Faculty of Engineering at Lund University perceive academic writing and the effects of a writing intervention.To obtain information on students’ education in, attitude, perception of its difficulty and their own skill towards academic writing, we constructed a survey which was sent out to engineering students at Lund University. This yielded 62 responses showing that students want more opportunities to develop their writing, but that they grade their writing skill high and the difficulty low.The effects of a simple writing intervention, briefly discussing the importance of good writing practices during a laboratory session, was investigated for one student group. This was done using a random selection of laboratory reports for one control group and one intervention group. The overall quality of the students’ writing was not significantly improved with the intervention. However the quality of the conclusions, the report section with the lowest quality rating, was higher for the intervention group