Clifford wavelets for fetal ECG extraction

Analysis of the fetal heart rate during pregnancy is essential for monitoring the proper development of the fetus. Current fetal heart monitoring techniques lack the accuracy in fetal heart rate monitoring and features acquisition, resulting in diagnostic medical issues. The challenge lies in the extraction of the fetal ECG from the mother's ECG during pregnancy. This approach has the advantage of being a reliable and non-invasive technique. For this aim, we propose in this paper a wavelet/multi-wavelet method allowing to extract perfectly the feta ECG parameters from the abdominal mother ECG. The method is essentially due to the exploitation of Clifford wavelets as recent variants in the field. We prove that these wavelets are more efficient and performing against classical ones. The experimental results are therefore due to two basic classes of wavelets and multi-wavelets. A first-class is the classical Haar Schauder, and a second one is due to Clifford valued wavelets and multi-wavelets. These results showed that wavelets/multiwavelets are already good bases for the FECG processing, provided that Clifford ones are the best.Comment: 21 pages, 8 figures, 1 tabl

VI Workshop on Computational Data Analysis and Numerical Methods: Book of Abstracts

The VI Workshop on Computational Data Analysis and Numerical Methods (WCDANM) is going to be held on June 27-29, 2019, in the Department of Mathematics of the University of Beira Interior (UBI), Covilhã, Portugal and it is a unique opportunity to disseminate scientific research related to the areas of Mathematics in general, with particular relevance to the areas of Computational Data Analysis and Numerical Methods in theoretical and/or practical field, using new techniques, giving especial emphasis to applications in Medicine, Biology, Biotechnology, Engineering, Industry, Environmental Sciences, Finance, Insurance, Management and Administration. The meeting will provide a forum for discussion and debate of ideas with interest to the scientific community in general. With this meeting new scientific collaborations among colleagues, namely new collaborations in Masters and PhD projects are expected. The event is open to the entire scientific community (with or without communication/poster)

Personalised Finite-Element Models using Image Registration in Parametric Space

Heart failure (HF) is a chronic clinical condition in which the heart fails to pump enough blood to meet the metabolic needs of the body. Patients have reduced physical performance and can see their quality of life severely impaired; around 40-70% of patients diagnosed of HF die within the first year following diagnosis. It is underestimated that 900,000 people in the UK currently suffer from HF. HF has a big impact on the NHS, representing 1 million inpatient bed, 5% of all emergency medical admission to hospitals and costs 2% of the total NHS budget. The annual incidence of new diagnoses is reported as 93,000 people in England alone – and this figure is already increasing at a rate above that at which population is ageing [1]. Cardiac resynchronisation therapy (CRT) has become established as an effective solution to treat selected patients with HF. The research presented in this thesis has been conducted as part of a large EPSRC-Funded project on the theme of Grand Challenges in Heathcare, with co-investigators from King’s College London (KCL), Imperial College London, University College London (UCL) and the University of Sheffield. The aim is to develop and to apply modelling techniques to simulate ventricular mechanics and CRT therapy in patient cohorts from Guy’s Hospital (London) and from the Sheffield Teaching Hospitals Trust. This will lead to improved understanding of cardiac physiological behaviour and how diseases affect normal cardiac performance, and to improved therapy planning by allowing candidate interventions to be simulated before they are applied on patients. The clinical workflow within the hospital manages the patient through the processes of diagnosis, therapy planning and follow-up. The first part of this thesis focuses on the development of a formal process for the integration of a computational analysis workflow, including medical imaging, segmentation, model construction, model execution and analysis, into the clinical workflow. During the early stages of the project, as the analysis workflow was being compiled, a major bottle-neck was identified regarding the time required to build accurate, patient-specific geometrical meshes from the segmented images. The second part of this thesis focuses on the development of a novel approach based on the use of image registration to improve the process of construction of a high-quality personalised finite element mesh for an individual patient. Chapter 1 summarises the clinical context and introduces the tools and processes that are applied in this thesis. Chapter 2 describes the challenges and the implementation of a computational analysis workflow and its integration into a clinical environment. Chapter 3 describes the theoretical underpinnings of the image registration algorithm that has been developed to address the problem of construction of high-quality personalised meshes. The approach includes the use of regularisation terms that are designed to improve the mesh quality. The selection and implementation of the regularisation terms is discussed in detail in Chapter 4. Chapter 5 describes the application of the method to a series of test problems, whilst Chapter 6 describes the application to the patient cohort in the clinical study. Chapter 7 demonstrates that the method, developed for robust mesh construction, can readily be applied to determine boundary conditions for computational fluid dynamics (CFD) analysis. Chapter 8 provides a summary of the achievements of the thesis, together with suggestions for further work

Imaging studies of peripheral nerve regeneration induced by porous collagen biomaterials

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references.There is urgent need to develop treatments for inducing regeneration in injured organs. Porous collagen-based scaffolds have been utilized clinically to induce regeneration in skin and peripheral nerves, however still there is no complete explanation about the underlying mechanism. This thesis utilizes advanced microscopy to study the expression of contractile cell phenotypes during wound healing, a phenotype believed to affect significantly the final outcome. The first part develops an efficient pipeline for processing challenging spectral fluorescence microscopy images. Images are segmented into regions of objects by refining the outcome of a pixel-wide model selection classifier by an efficient Markov Random Field model. The methods of this part are utilized by the following parts. The second part extends the image informatics methodology in studying signal transduction networks in cells interacting with 3D matrices. The methodology is applied in a pilot study of TGFP signal transduction by the SMAD pathway in fibroblasts seeded in porous collagen scaffolds. Preliminary analysis suggests that the differential effect of TGFP1 and TGFP3 to cells could be attributed to the "non-canonical" SMADI and SMAD5. The third part is an ex vivo imaging study of peripheral nerve regeneration, which focuses on the formation of a capsule of contractile cells around transected rat sciatic nerves grafted with collagen scaffolds, 1 or 2 weeks post-injury. It follows a recent study that highlights an inverse relationship between the quality of the newly formed nerve tissue and the size of the contractile cell capsule 9 weeks post-injury. Results suggest that "active" biomaterials result in significantly thinner capsule already 1 week post-injury. The fourth part describes a novel method for quantifying the surface chemistry of 3D matrices. The method is an in situ binding assay that utilizes fluorescently labeled recombinant proteins that emulate the receptor of , and is applied to quantify the density of ligands for integrins a113, a2p1 on the surface of porous collagen scaffolds. Results provide estimates for the density of ligands on "active" and "inactive" scaffolds and demonstrate that chemical crosslinking can affect the surface chemistry of biomaterials, therefore can affect the way cells sense and respond to the material.by Dimitrios S. Tzeranis.Ph. D

New Foundation in the Sciences: Physics without sweeping infinities under the rug

It is widely known among the Frontiers of physics, that “sweeping under the rug” practice has been quite the norm rather than exception. In other words, the leading paradigms have strong tendency to be hailed as the only game in town. For example, renormalization group theory was hailed as cure in order to solve infinity problem in QED theory. For instance, a quote from Richard Feynman goes as follows: “What the three Nobel Prize winners did, in the words of Feynman, was to get rid of the infinities in the calculations. The infinities are still there, but now they can be skirted around . . . We have designed a method for sweeping them under the rug. [1] And Paul Dirac himself also wrote with similar tune: “Hence most physicists are very satisfied with the situation. They say: Quantum electrodynamics is a good theory, and we do not have to worry about it any more. I must say that I am very dissatisfied with the situation, because this so-called good theory does involve neglecting infinities which appear in its equations, neglecting them in an arbitrary way. This is just not sensible mathematics. Sensible mathematics involves neglecting a quantity when it turns out to be small—not neglecting it just because it is infinitely great and you do not want it!”[2] Similarly, dark matter and dark energy were elevated as plausible way to solve the crisis in prevalent Big Bang cosmology. That is why we choose a theme here: New Foundations in the Sciences, in order to emphasize the necessity to introduce a new set of approaches in the Sciences, be it Physics, Cosmology, Consciousness etc

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal