Telemonitoring ADL platform based on non-intrusive and privacy-friendly sensors for the care of the elderly in smart homes

International audienceDuring the last years, several sensor-based monitoring systems have been developed to detect in real time frequent problems in older people, such as falls and nocturia. Some devices can also measure different variables of the environment (e.g. temperature, pollution, etc.) to generate alarms and thus help the user's welfare. All these devices generate numerous sensitive data related to the health and behavior of user/patients. The presence of some of these sensors in homes can mean a vulnerability of the user’s privacy. In this article we propose a telemonitoring ADL platform based on non-intrusive sensors for the care of the elderly, restricted by a user-centered protocol that guarantees their privacy and facilitates their acceptance by the user

Cheating to achieve Formal Concept Analysis over a large formal context

International audienceResearchers are facing one of the main problems of the Information Era. As more articles are made electronically available, it gets harder to follow trends in the different domains of research. Cheap, coherent and fast to construct knowledge models of research domains will be much required when information becomes unmanageable. While Formal Concept Analysis (FCA) has been widely used on several areas to construct knowledge artifacts for this purpose (Ontology development, Information Retrieval, Software Refactoring, Knowledge Discovery), the large amount of documents and terminology used on research domains makes it not a very good option (because of the high computational cost and humanly-unprocessable output). In this article we propose a novel heuristic to create a taxonomy from a large term-document dataset using Latent Semantic Analysis and Formal Concept Analysis. We provide and discuss its implementation on a real dataset from the Software Architecture community obtained from the ISI Web of Knowledge (4400 documents)

Well-being and -ageing with chronical disease: the BV2 project

International audienceThe BV2 project aims to propose a monitoring system for wellbeing but also well-aging working on the prevention, detection and monitoring using a System of the Systems (SoS) approach. The project partner already uses the IoT technologies and the BV2 platform will combine the different developed systems. The main originality of the project consist s in the development of a virtual platform by combining the existing system

Academic team formation as evolving hypergraphs

This paper quantitatively explores the social and socio-semantic patterns of constitution of academic collaboration teams. To this end, we broadly underline two critical features of social networks of knowledge-based collaboration: first, they essentially consist of group-level interactions which call for team-centered approaches. Formally, this induces the use of hypergraphs and n-adic interactions, rather than traditional dyadic frameworks of interaction such as graphs, binding only pairs of agents. Second, we advocate the joint consideration of structural and semantic features, as collaborations are allegedly constrained by both of them. Considering these provisions, we propose a framework which principally enables us to empirically test a series of hypotheses related to academic team formation patterns. In particular, we exhibit and characterize the influence of an implicit group structure driving recurrent team formation processes. On the whole, innovative production does not appear to be correlated with more original teams, while a polarization appears between groups composed of experts only or non-experts only, altogether corresponding to collectives with a high rate of repeated interactions

Impact de l'obésité sur les structures sociales et impact des structures sociales sur l'obésité

Titulaire d'un diplôme en Ingénierie Informatique (Université de Valparaíso, Chili), et possédant une fructueuse expérience professionnelle axée principalement sur l'enseignement et la recherche, j'ai obtenu mon Master en Sciences Cognitives à l'Ecole Normale Supérieure (rue d'Ulm, Paris) et ma thèse de doctorat à l'Ecole Polytechnique (Palaiseau, France).I will propose a theoretical framework (conceptualization and formalization) which seeks to model obesity as a process of transformation of one's own body determined by individual (physical and psychological), inter-individual (relational, relationship between the individual and others) and socio-cultural factors (environmental, relationship between the individual and his milieu). Individual and inter-individual factors are tied to each other in a socio-cultural context whose impact is notably related to the visibility of any body being exposed on the public stage in a non-contingent way. To investigate obesity in this multifactorial manner, this paper is divided in two main parts. First, I take into account these inseparable factors to analyze the impact through time that obese individual transformation may have on the social structure. With this aim, I develop a network model in which individual interactions are in part due to homophilic selection/deselection, i.e. preferential attachment and detachment of inter-individual links according to characteristics of the individuals involved. Homophily is here defined as the tendency of an individual to create links with other individuals sharing similar attributes with him and to cut links with other dissimilar individuals. Homophily suggests that individuals tend to interact with those who resemble them. Second, and reciprocally, I study the role which could be played by the structure of the social fabric in the increase and current development of obesity. I evaluate the impact of micro level (i.e : relations between individuals) as well as the impact of meso level (i.e : relations between districts) and between macro level (i.e :countries). This approach highlights the necessity to integrate the dynamics of each scale to better understand the evolution of the pathology. With this aim, I use two stochastic models : epidemiological compartmental model and individual centered network model, considering three influences : exogenous heterogeneous (individual- cultural), exogenous homogeneous (individual-social) and endogenous (individual-individual). All together, this investigation of obesity will allow me to investigate the social and cultural dimension involved in being and transforming one's body.Ce travail porte sur le développement d'un cadre théorique (conceptualisation et formalisation) qui cherche à modéliser l'obésité comme un processus de transformation du corps de l'individu obèse, déterminé par des facteurs individuels, inter-individuels, sociaux et culturels. J'ai d'abord pris en compte ces facteurs indissociables, pour analyser l'impact dans le temps d'une telle transformation individuelle sur la structure sociale. Pour ce faire, j'ai développé un modèle de réseau, dans lequel une partie des interactions individuelles sont dues à une sélection/désélection homophilique, consistant en un détachement et un attachement préférentiels de liens, selon les propriétés des individus. Deuxièmement, et réciproquement, j'étudie le rôle que pourrait jouer la structure du tissu social dans l'actuel développement de l'obésité. J'utilise pour cela deux modèles stochastiques : un modèle épidémiologique à compartiments et un modèle de réseau individu-centré considérant deux types d'influences : exogène (environnement-individu) et endogène (individu-individu)

Effects of internet-based telemonitoring platforms on the quality of life of oncologic patients: A systematic literature review protocol.

IntroductionTelemonitoring involves the transmission of clinical information through digital means, including internet-connected devices such as smartphones, health tracking apps and video conferencing platforms. This strategy could provide a viable alternative to facilitate follow-up in several conditions, including cancer.ObjectivesTo synthesise the available evidence on the effectiveness of internet-based telemonitoring platforms amongst oncological patients. Relevant endpoints include overall quality of life, the ability to detect postoperative complications, severe toxicity reactions attributable to chemotherapy, reducing the frequency of hospitalisations, emergency department visits and mortality.MethodsA systematic review of published and unpublished randomised and controlled studies will be carried out. Iterative searches in PubMED/MEDLINE, EMBASE, Epistemonikos, LILACS, and Cochrane CENTRAL repositories from January 2000 to January 2023 will be conducted. Grey literature repositories, such as Clinicaltrials, BioRxiv and MedRxiv will be searched as well. The Cochrane risk of bias tool will be used to assess the quality of the eligible studies. If possible, a meta-analysis based on the random-effects model will be conducted to evaluate changes in any of the aforementioned outcomes. Heterogeneity will be assessed with Cochrane's Q and I2 statistics. Its exploration will be carried out using subgroup and sensitivity analyses. Relevant subgroups include the proportion of elderly patients in each study, characteristics of each platform, study type, type of funding and moment of conduction (i.e. before or after the COVID-19 pandemic). Publication bias will be assessed using funnel plots and Egger's test.RegistrationThis systematic review protocol is registered in PROSPERO. Its registration number is CRD42023412705

Additional file 1: of Implementation of a Smartphone application in medical education: a randomised trial (iSTART)

Examples to Clinical Vignettes. (DOCX 112 kb

Sensitivity and Specificity of Patient-Reported Clinical Manifestations to Diagnose COVID-19 in Adults from a National Database in Chile: A Cross-Sectional Study

(1) Background: The diagnosis of COVID-19 is frequently made on the basis of a suggestive clinical history and the detection of SARS-CoV-2 RNA in respiratory secretions. However, the diagnostic accuracy of clinical features is unknown. (2) Objective: To assess the diagnostic accuracy of patient-reported clinical manifestations to identify cases of COVID-19. (3) Methodology: Cross-sectional study using data from a national registry in Chile. Infection by SARS-CoV-2 was confirmed using RT-PCR in all cases. Anonymised information regarding demographic characteristics and clinical features were assessed using sensitivity, specificity, and diagnostic odds ratios. A multivariable logistic regression model was constructed to combine epidemiological risk factors and clinical features. (4) Results: A total of 2,187,962 observations were available for analyses. Male participants had a mean age of 43.1 ± 17.5 years. The most common complaints within the study were headache (39%), myalgia (32.7%), cough (31.6%), and sore throat (25.7%). The most sensitive features of disease were headache, myalgia, and cough, and the most specific were anosmia and dysgeusia/ageusia. A multivariable model showed a fair diagnostic accuracy, with a ROC AUC of 0.744 (95% CI 0.743–0.746). (5) Discussion: No single clinical feature was able to fully confirm or exclude an infection by SARS-CoV-2. The combination of several demographic and clinical factors had a fair diagnostic accuracy in identifying patients with the disease. This model can help clinicians tailor the probability of COVID-19 and select diagnostic tests appropriate to their setting