1,354 research outputs found

    Ontology-based Activity Recognition Framework and Services

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    This paper introduces an ontology-based integrated framework for activity modeling, activity recognition and activity model evolution. Central to the framework is ontological activity modeling and semantic-based activity recognition, which is supported by an iterative process that incrementally improves the completeness and accuracy of activity models. In addition, the paper presents a service-oriented architecture for the realization of the proposed framework which can provide activity context-aware services in a scalable distributed manner. The paper further describes and discusses the implementation and testing experience of the framework and services in the context of smart home based assistive living

    Portal Design for the Open Data Initiative: A Preliminary Study

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    The Open Data Initiative (ODI) has been previously proposed to facilitate the sharing of annotated datasets within the pervasive health care research community. This paper outlines the requirements for the ODI portal based on the ontological data model of the ODI and its typical usage scenarios. In the context of an action research framework, the paper outlines the ODI platform, the design of a prototype user interface for the purposes of initial evaluation and its technical review by third-party researchers (n = 3). The main findings from the technical review were found to be the need for a more flexible user interface to reflect the different experimental configurations in the research community, provision for describing dataset usage, and dissemination conditions. The technical review also identified the value of permitting datasets with variable quality, as noisy datasets are useful in the testing of activity recognition algorithms. Revisions to the ODI ontology and platform are proposed based on the findings from this study

    Learning Behaviour for Service Personalisation and Adaptation

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    Context-aware applications within pervasive environments are increasingly being developed as services and deployed in the cloud. As such these services are increasingly required to be adaptive to individual users to meet their specific needs or to reflect the changes of their behavior. To address this emerging challenge this paper introduces a service-oriented personalisation framework for service personalisation with special emphasis being placed on behavior learning for user model and service function adaptation. The paper describes the system architecture and the underlying methods and technologies including modelling and reasoning, behavior analysis and a personalisation mechanism. The approach has been implemented in a service-oriented prototype system, and evaluated in a typical scenario of providing personalised travel assistance for the elderly using the help-on-demand services deployed on smartphone

    Safe Beacon: A Bluetooth Based Solution to Monitor Egress of Dementia Sufferers within a Residential Setting

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    The global population is ageing, as a consequence of this there will be a greater incidence of ageing related illnesses which cause cognitive impairment–such as Alzheimer’s disease. Within residential care homes, such cognitive impairment can lead to wandering of individuals beyond the boundaries of safety provided. This wandering, particularly in urban areas can be life threatening. This study introduces a novel solution to detect, and alert caregivers of, egress of at-risk inhabitants of a care home. This solution operates through a combination of wearable Bluetooth beacons and beam-formed listening devices. In an evaluation process involving 275 egress events, this solution proved to offer accurate operation with no incidence of false positives. Notably, this solution has been deployed within a real residential care home environment for over 12 months. Proposed future work discusses improvements to this solution

    Susceptibility testing and reporting of new antibiotics with a focus on tedizolid: an international working group report

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    Inappropriate use and overuse of antibiotics are among the most important factors in resistance development, and effective antibiotic stewardship measures are needed to optimize outcomes. Selection of appropriate antimicrobials relies on accurate and timely antimicrobial susceptibility testing. However, the availability of clinical breakpoints and in vitro susceptibility testing often lags behind regulatory approval by several years for new antimicrobials. A Working Group of clinical/medical microbiologists from Brazil, Canada, Mexico, Saudi Arabia, Russia and the UK recently examined issues surrounding antimicrobial susceptibility testing for novel antibiotics. While commercially available tests are being developed, potential surrogate antibiotics may be used as marker of susceptibility. Using tedizolid as an example of a new antibiotic, this special report makes recommendations to optimize routine susceptibility reporting

    Which circulating antioxidant vitamins are confounded by socioeconomic deprivation? The MIDSPAN family study

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    <p><b>Background:</b> Antioxidant vitamins are often described as having “independent” associations with risk of cancer, cardiovascular disease (CVD) and mortality. We aimed to compare to what extent a range of antioxidant vitamins and carotenoids are associated with adulthood and childhood markers of socioeconomic deprivation and to adverse lifestyle factors.</p> <p><b>Methods and Findings:</b> Socioeconomic and lifestyle measures were available in 1040 men and 1298 women from the MIDSPAN Family Study (30–59 years at baseline) together with circulating levels of vitamins A, C, E, and carotenoids (α-carotene, β-carotene, lutein and lycopene). Markers of socioeconomic deprivation in adulthood were consistently as strongly associated with lower vitamin C and carotenoid levels as markers of adverse lifestyle; the inverse association with overcrowding was particularly consistent (vitamin C and carotenoids range from 19.1% [95% CI 30.3–6.0] to 38.8% [49.9–25.3] lower among those in overcrowded residencies). These associations were consistent after adjusting for month, classical CVD risk factors, body mass index, physical activity, vitamin supplements, dietary fat and fibre intake. Similar, but weaker, associations were seen for childhood markers of deprivation. The association of vitamin A or E were strikingly different; several adult adverse lifestyle factors associated with higher levels of vitamin A and E, including high alcohol intake for vitamin A (9.5% [5.7–13.5]) and waist hip ratio for vitamin E (9.5% [4.8–14.4]), with the latter associations partially explained by classical risk factors, particularly cholesterol levels.</p> <p><b>Conclusions:</b> Plasma vitamin C and carotenoids have strong inverse associations with adulthood markers of social deprivation, whereas vitamin A and E appear positively related to specific adverse lifestyle factors. These findings should help researchers better contextualize blood antioxidant vitamin levels by illustrating the potential limitations associated with making causal inferences without consideration of social deprivation.</p&gt

    The Database for Aggregate Analysis of ClinicalTrials.gov (AACT) and Subsequent Regrouping by Clinical Specialty

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    BACKGROUND: The ClinicalTrials.gov registry provides information regarding characteristics of past, current, and planned clinical studies to patients, clinicians, and researchers; in addition, registry data are available for bulk download. However, issues related to data structure, nomenclature, and changes in data collection over time present challenges to the aggregate analysis and interpretation of these data in general and to the analysis of trials according to clinical specialty in particular. Improving usability of these data could enhance the utility of ClinicalTrials.gov as a research resource. METHODS/PRINCIPAL RESULTS: The purpose of our project was twofold. First, we sought to extend the usability of ClinicalTrials.gov for research purposes by developing a database for aggregate analysis of ClinicalTrials.gov (AACT) that contains data from the 96,346 clinical trials registered as of September 27, 2010. Second, we developed and validated a methodology for annotating studies by clinical specialty, using a custom taxonomy employing Medical Subject Heading (MeSH) terms applied by an NLM algorithm, as well as MeSH terms and other disease condition terms provided by study sponsors. Clinical specialists reviewed and annotated MeSH and non-MeSH disease condition terms, and an algorithm was created to classify studies into clinical specialties based on both MeSH and non-MeSH annotations. False positives and false negatives were evaluated by comparing algorithmic classification with manual classification for three specialties. CONCLUSIONS/SIGNIFICANCE: The resulting AACT database features study design attributes parsed into discrete fields, integrated metadata, and an integrated MeSH thesaurus, and is available for download as Oracle extracts (.dmp file and text format). This publicly-accessible dataset will facilitate analysis of studies and permit detailed characterization and analysis of the U.S. clinical trials enterprise as a whole. In addition, the methodology we present for creating specialty datasets may facilitate other efforts to analyze studies by specialty groups
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