2,366 research outputs found

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

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    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)

    Studies on Spinal Fusion from Computational Modelling to ‘Smart’ Implants

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    Low back pain, the worldwide leading cause of disability, is commonly treated with lumbar interbody fusion surgery to address degeneration, instability, deformity, and trauma of the spine. Following fusion surgery, nearly 20% experience complications requiring reoperation while 1 in 3 do not experience a meaningful improvement in pain. Implant subsidence and pseudarthrosis in particular present a multifaceted challenge in the management of a patient’s painful symptoms. Given the diversity of fusion approaches, materials, and instrumentation, further inputs are required across the treatment spectrum to prevent and manage complications. This thesis comprises biomechanical studies on lumbar spinal fusion that provide new insights into spinal fusion surgery from preoperative planning to postoperative monitoring. A computational model, using the finite element method, is developed to quantify the biomechanical impact of temporal ossification on the spine, examining how the fusion mass stiffness affects loads on the implant and subsequent subsidence risk, while bony growth into the endplates affects load-distribution among the surrounding spinal structures. The computational modelling approach is extended to provide biomechanical inputs to surgical decisions regarding posterior fixation. Where a patient is not clinically pre-disposed to subsidence or pseudarthrosis, the results suggest unilateral fixation is a more economical choice than bilateral fixation to stabilise the joint. While finite element modelling can inform pre-surgical planning, effective postoperative monitoring currently remains a clinical challenge. Periodic radiological follow-up to assess bony fusion is subjective and unreliable. This thesis describes the development of a ‘smart’ interbody cage capable of taking direct measurements from the implant for monitoring fusion progression and complication risk. Biomechanical testing of the ‘smart’ implant demonstrated its ability to distinguish between graft and endplate stiffness states. The device is prepared for wireless actualisation by investigating sensor optimisation and telemetry. The results show that near-field communication is a feasible approach for wireless power and data transfer in this setting, notwithstanding further architectural optimisation required, while a combination of strain and pressure sensors will be more mechanically and clinically informative. Further work in computational modelling of the spine and ‘smart’ implants will enable personalised healthcare for low back pain, and the results presented in this thesis are a step in this direction

    Utilization of big data to improve management of the emergency departments. Results of a systematic review

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    Background. The emphasis on using big data is growing exponentially in several sectors including biomedicine, life sciences and scientific research, mainly due to advances in information technologies and data analysis techniques. Actually, medical sciences can rely on a large amount of biomedical information and Big Data can aggregate information around multiple scales, from the DNA to the ecosystems. Given these premises, we wondered if big data could be useful to analyze complex systems such as the Emergency Departments (EDs) to improve their management and eventually patient outcomes. Methods. We performed a systematic review of the literature to identify the studies that implemented the application of big data in EDs and to describe what have already been done and what are the expectations, issues and challenges in this field. Results. Globally, eight studies met our inclusion criteria concerning three main activities: the management of ED visits, the ED process and activities and, finally, the prediction of the outcome of ED patients. Although the results of the studies show good perspectives regarding the use of big data in the management of emergency departments, there are still some issues that make their use still difficult. Most of the predictive models and algorithms have been applied only in retrospective studies, not considering the challenge and the costs of a real-time use of big data. Only few studies highlight the possible usefulness of the large volume of clinical data stored into electronic health records to generate evidence in real time. Conclusion. The proper use of big data in this field still requires a better management information flow to allow real-time application

    Insights into infusion-based targeted drug delivery in brain: perspectives, challenges and opportunities

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    Targeted drug delivery in the brain is instrumental in the treatment of lethal brain diseases, such as glioblastoma multiforme, the most aggressive primary central nervous system tumour in adults. Infusion-based drug delivery techniques, which directly administer to the tissue for local treatment, as in convection-enhanced delivery (CED), provide an important opportunity; however, poor understanding of the pressure-driven drug transport mechanisms in the brain has hindered its ultimate success in clinical applications. In this review, we focus on the biomechanical and biochemical aspects of infusion-based targeted drug delivery in the brain and look into the underlying molecular level mechanisms. We discuss recent advances and challenges in the complementary field of medical robotics and its use in targeted drug delivery in the brain. A critical overview of current research in these areas and their clinical implications is provided. This review delivers new ideas and perspectives for further studies of targeted drug delivery in the brain

    A review and consideration on the kinematics of reach-to-grasp movements in macaque monkeys

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    The bases for understanding the neuronal mechanisms that underlie the control of reach-to-grasp movements among nonhuman primates, particularly macaques, has been widely studied. However, only a few kinematic descriptions of their prehensile actions are available. A thorough understanding of macaques' prehensile movements is manifestly critical, in light of their role in biomedical research as valuable models for studying neuromotor disorders and brain mechanisms, as well as for developing brain-machine interfaces to facilitate arm control. This article aims to review the current state of knowledge on the kinematics of grasping movements that macaques perform in naturalistic, semi-naturalistic, and laboratory settings, to answer the following questions: Are kinematic signatures affected by the context within which the movement is performed? In what ways is kinematics of humans' and macaques' prehensile actions similar/dissimilar? Our analysis reflects the challenges involved in making comparisons across settings and species due to the heterogeneous picture in terms of the number of subjects, stimuli, conditions, and hands used. The kinematics of free-ranging macaques are characterized by distinctive features that are exhibited neither by macaques in laboratory setting nor human subjects. The temporal incidence of key kinematic landmarks diverges significantly between species, indicating disparities in the overall organization of movement. Given such complexities, we attempt a synthesis of extant body of evidence, intending to generate some significant implications for directions that future research might take, to recognize the remaining gaps and pursue the insights and resolutions to generate an interpretation of movement kinematics that accounts for all settings and subjects

    Automated analysis of human cochlea shape variability from segmented μCT images

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    International audienceThe aim of this study is to define an automated and reproducible framework for cochlear anatomical analysis from high-resolution segmented images and to provide a comprehensive and objective shape variability study suitable for cochlear implant design and surgery planning. For the scala tympani (ST), the scala vestibuli (SV) and the whole cochlea, the variability of the arc lengths and the radial and longitudinal components of the lateral, central and modiolar paths are studied. The robustness of the automated cochlear coordinate system estimation is validated with synthetic and real data. Cochlear cross-sections are statistically analyzed using area, height and width measurements. The cross-section tilt angle is objectively measured and this data documents a significant feature for occurrence of surgical trauma
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