78 research outputs found

    On Modeling the Quality of Nutrition for Healthy Ageing Using Fuzzy Cognitive Maps

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    Modelling dietary intake of older adults can prevent nutritional deficiencies and diet-related diseases, improving their quality of life. Towards such direction, a Fuzzy Cognitive Map (FCM)-based modelling approach that models the interdependencies between the factors that affect the Quality of Nutrition (QoN) is presented here. The proposed FCM-QoN model uses a FCM with seven input-one output concepts, i.e., five food groups of the UK Eatwell Plate, Water (H2O), and older adult’s Emotional State (EmoS), outputting the QoN. The weights incorporated in the FCM structure were drawn from an experts’ panel, via a Fuzzy Logic-based knowledge representation process. Using various levels of analysis (causalities, static/feedback cycles), the role of EmoS and H2O in the QoN was identified, along with the one of Fruits/Vegetables and Protein affecting the sustainability of effective food combinations. In general, the FCM-QoN approach has the potential to explore different dietary scenarios, helping health professionals to promote healthy ageing and providing prognostic simulations for diseases effect (such as Parkinson’s) on dietary habits, as used in the H2020 i-Prognosis project (www.i-prognosis.eu)

    An Integrated Platform Supporting Intangible Cultural Heritage Learning and Transmission: Definition of Requirements and Evaluation Criteria

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    The paper offers an experience-based viewpoint on two key phases of the development of an Information and Communication Technologies (ICTs)-based system: the definition of requirements and identification of related criteria and methodology for its evaluation. In doing so, it refers to the unique context of the i-Treasures EU project, which deals with the development of an innovative integrated platform to support the learning and transmission of Intangible Cultural Heritage (ICH). The i-Treasures integrated platform is conceived to support both traditional learning approaches and innovative and active learning processes, based on extensive use of sensor-technologies. In this light, during the development process, particular attention has been devoted to the definition of requirements with specific reference to sensor-mediated Human Computer Interaction (HCI) issues and the evaluation process was designed accordingly, in coherence with the specific advanced features of the integrated platform. The paper offers a view of the complexity of the design of ICT-based tools supporting the preservation and transmission of ICH and also provides an insight (and this could have a broader impact) into the methodology adopted to harmonize the requirements and the evaluation phases which are key pillars for the construction of any educationally effective ICT-based learning system

    Rare and contemporary dance as cultural mediators within a b-learning mode: the fuzzy logic perspective

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    The concept of cultural mediation via undergraduate courses in rare and contemporary dance within a blended learning (b-learning) mode is approached here through a fuzzy logic (FL)-based.modelling perspective. Students’ online interaction on the Moodle Learning Management System (LMS).during such b-learning courses was logged over an entire academic year, and the resulting data were.analysed using FL, in order to estimate users’ LMS Quality of Interaction (QoI). Using documental.analysis, the pedagogical design strategies per semester were transformed into concept maps and related.with the dynamically (per week) estimated QoIs. The latter were used by the teachers at the end of the.first semester to reflect upon and update their pedagogical planning, so as to enhance QoI in the second.semester. The results show the beneficial role of QoI in supporting more dynamic design of educational.scenarios, yet considering the inherent tendencies/attitudes of users’ interaction within different cultural.expressions

    Bayesian Wavelet Shrinkage of the Haar-Fisz Transformed Wavelet Periodogram.

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    It is increasingly being realised that many real world time series are not stationary and exhibit evolving second-order autocovariance or spectral structure. This article introduces a Bayesian approach for modelling the evolving wavelet spectrum of a locally stationary wavelet time series. Our new method works by combining the advantages of a Haar-Fisz transformed spectrum with a simple, but powerful, Bayesian wavelet shrinkage method. Our new method produces excellent and stable spectral estimates and this is demonstrated via simulated data and on differenced infant electrocardiogram data. A major additional benefit of the Bayesian paradigm is that we obtain rigorous and useful credible intervals of the evolving spectral structure. We show how the Bayesian credible intervals provide extra insight into the infant electrocardiogram data

    EEG-Based Tonic Cold Pain Characterization Using Wavelet Higher Order Spectral Features

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    Digital Health Technologies for Long-term Self-management of Osteoporosis: Systematic Review and Meta-analysis

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    BackgroundOsteoporosis is the fourth most common chronic disease worldwide. The adoption of preventative measures and effective self-management interventions can help improve bone health. Mobile health (mHealth) technologies can play a key role in the care and self-management of patients with osteoporosis. ObjectiveThis study presents a systematic review and meta-analysis of the currently available mHealth apps targeting osteoporosis self-management, aiming to determine the current status, gaps, and challenges that future research could address, as well as propose appropriate recommendations. MethodsA systematic review of all English articles was conducted, in addition to a survey of all apps available in iOS and Android app stores as of May 2021. A comprehensive literature search (2010 to May 2021) of PubMed, Scopus, EBSCO, Web of Science, and IEEE Xplore was conducted. Articles were included if they described apps dedicated to or useful for osteoporosis (targeting self-management, nutrition, physical activity, and risk assessment) delivered on smartphone devices for adults aged ≥18 years. Of the 32 articles, a random effects meta-analysis was performed on 13 (41%) studies of randomized controlled trials, whereas the 19 (59%) remaining studies were only included in the narrative synthesis as they did not provide enough data. ResultsIn total, 3906 unique articles were identified. Of these 3906 articles, 32 (0.81%) articles met the inclusion criteria and were reviewed in depth. The 32 studies comprised 14,235 participants, of whom, on average, 69.5% (n=9893) were female, with a mean age of 49.8 (SD 17.8) years. The app search identified 23 relevant apps for osteoporosis self-management. The meta-analysis revealed that mHealth-supported interventions resulted in a significant reduction in pain (Hedges g −1.09, 95% CI −1.68 to −0.45) and disability (Hedges g −0.77, 95% CI −1.59 to 0.05). The posttreatment effect of the digital intervention was significant for physical function (Hedges g 2.54, 95% CI −4.08 to 4.08) but nonsignificant for well-being (Hedges g 0.17, 95% CI −1.84 to 2.17), physical activity (Hedges g 0.09, 95% CI −0.59 to 0.50), anxiety (Hedges g −0.29, 95% CI −6.11 to 5.53), fatigue (Hedges g −0.34, 95% CI −5.84 to 5.16), calcium (Hedges g −0.05, 95% CI −0.59 to 0.50), vitamin D intake (Hedges g 0.10, 95% CI −4.05 to 4.26), and trabecular score (Hedges g 0.06, 95% CI −1.00 to 1.12). ConclusionsOsteoporosis apps have the potential to support and improve the management of the disease and its symptoms; they also appear to be valuable tools for patients and health professionals. However, most of the apps that are currently available lack clinically validated evidence of their efficacy and focus on a limited number of symptoms. A more holistic and personalized approach within a cocreation design ecosystem is needed. Trial RegistrationPROSPERO 2021 CRD42021269399; https://tinyurl.com/2sw454a
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