22 research outputs found

    Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

    Data flow and access control policy models in wireless body area network for healthcare

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    This thesis starts with an investigation of the interactions in terms of data flow between parties involved in body area networks or BANs under healthcare scenarios targeting outdoor and indoor environments. Using these scenarios, data flow requirements are identified between BAN elements and parties involved in BANs such as patients and doctors. Identified requirements are used to generate BAN data flow models. Data flow models and key information security and the privacy requirements were used to design an access control policy model that would allow authorized parties to access medical resources and data securely

    HUMAN ERRORS IN COMPUTER RELATED ABUSES 1

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    The term “Human error ” can simply be defined as an error which made by a human. In fact, Human error is an explanation of malfunctions, unintended consequents from operating a system. There are many factors that cause a person to have an error due to the unwanted error of human. The aim of this paper is to investigate the relationship of human error as one of the factors to computer related abuses. The paper beings by computer-relating to human errors and followed by mechanism mitigate these errors through social and technical perspectives. We present the 25 techniques of computer crime prevention, as a heuristic device that assists. A last section discussing the ways of improving the adoption of security, and conclusion.

    Privacy of fitness applications and consent management in blockchain

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    The rapid advances in fitness wearable devices are redefining privacy around interactions. Fitness wearables devices record a considerable amount of sensitive and private details about exercise, blood oxygen level, and heart rate. Privacy concerns have emerged about the interactions between an individual's raw fitness data and data analysis by the providers of fitness apps and wearable devices. This paper describes the importance of adopting and applying legal frameworks within the fitness tracker ecosystem. In this review, we describe the studies on the current privacy policies of fitness app providers, heuristically evaluate the methods for consent management by fitness providers, summarize the gaps identified in our review of these studies, and discuss potential solutions for filling the gaps identified. We have identified four main problems related to preserving the privacy of users of fitness apps: lack of system transparency, lack of privacy policy legibility, concerns regarding one-time consent, and issues of noncompliance regarding consent management. After discussing feasible solutions, we conclude by describing how blockchain is suitable for solving these privacy issues.Comment: This article has been accepted for publication in a future issue of Australasian Computer Science Week 2022 (ACSW 2022), but has not been fully edited Content may change prior to final publication. Citation information: DOI https://doi.org/10.1145/3511616.3513100, ACSW 202

    A blockchain-based consent mechanism for access to fitness data in the healthcare context

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    Wearable fitness devices are widely used to track an individual's health and physical activities to improve the quality of health services. These devices sense a considerable amount of sensitive data processed by a centralized third party. While many researchers have thoroughly evaluated privacy issues surrounding wearable fitness trackers, no study has addressed privacy issues in trackers by giving control of the data to the user. Blockchain is an emerging technology with outstanding advantages in resolving consent management privacy concerns. As there are no fully transparent, legally compliant solutions for sharing personal fitness data, this study introduces an architecture for a human-centric, legally compliant, decentralized and dynamic consent system based on blockchain and smart contracts. Algorithms and sequence diagrams of the proposed system's activities show consent-related data flow among various agents, which are used later to prove the system's trustworthiness by formalizing the security requirements. The security properties of the proposed system were evaluated using the formal security modeling framework SeMF, which demonstrates the feasibility of the solution at an abstract level based on formal language theory. As a result, we have empirically proven that blockchain technology is suitable for mitigating the privacy issues of fitness providers by recording individuals' consent using blockchain and smart contracts.Comment: This article has been accepted for publication in a future issue of IEEE Access journa
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