Mining Heterogeneous Multivariate Time-Series for Learning Meaningful Patterns: Application to Home Health Telecare

For the last years, time-series mining has become a challenging issue for researchers. An important application lies in most monitoring purposes, which require analyzing large sets of time-series for learning usual patterns. Any deviation from this learned profile is then considered as an unexpected situation. Moreover, complex applications may involve the temporal study of several heterogeneous parameters. In that paper, we propose a method for mining heterogeneous multivariate time-series for learning meaningful patterns. The proposed approach allows for mixed time-series -- containing both pattern and non-pattern data -- such as for imprecise matches, outliers, stretching and global translating of patterns instances in time. We present the early results of our approach in the context of monitoring the health status of a person at home. The purpose is to build a behavioral profile of a person by analyzing the time variations of several quantitative or qualitative parameters recorded through a provision of sensors installed in the home

Fusion de données multicapteurs pour un système de télésurveillance médicale de personnes à domicile

Le développement des systèmes de télésurveillance médicale à domicile est fondamental face au vieillissement de la population et aux capacités limitées d'admission dans les hôpitaux et centres spécialisés. Ce travail de thèse concerne particulièrement la conception d'un assistant intelligent pour l'analyse des données hétérogènes collectées par des capteurs au domicile afin de détecter, voir prévenir, l'occurrence de situations inquiétantes. Il s'agit de concevoir un système d'apprentissage des habitudes de vie d'une personne, tout écart par rapport à ce profil comportemental étant considéré comme critique. L'étude proposée concerne d'une part la conception d'un processus de simulation pour la génération de grandes quantités de données appropriées au contexte expérimental. D'autre part, une méthode générique pour l'extraction non supervisée de motifs dans des séquences temporelles multidimensionnelles et hétérogènes est proposée puis expérimentée dans le contexte de l'identification des comportements récurrents d'une personne dans ses activités quotidiennes. On évalue en particulier les indices de sensibilité (tolérance aux modifications normales de comportement) et de spécificité (rejet des modifications inquiétantes) du systèmes. L'application du système d'apprentissage aux séquences générées par la simulation permet également de vérifier l'extraction possible de comportements récurrents interprétés a posteriori en terme de la réalisation d'activités de la vie quotidienne.GRENOBLE1-BU Sciences (384212103) / SudocSudocFranceF

Health "Smart" home: information technology for patients at home.

International audienceThis article reviews the emerging concept of health "Smart" homes (HSH) and its potential through the use of telemedical information systems and communication technologies. HSH systems provide health care services for people with special needs who wish to remain independent and living in their own home. The large diversity of needs in a home-based patient population requires complex technology. Meeting these needs technically requires the use of a distributed approach and the combination of many hardware and software techniques. We also describe the wide scope of new information, communication, and data-acquisition technologies used in home health care. We offer an introduction to the HSH concept in terms of technical, economic, and human requirements. Examples of HSH projects are presented, including a short description of our own smart home and telehealthcare information system project

Laminar Shear Stress Regulates Endothelial Kinin B1 Receptor Expression and Function. Potential Implication in Atherogenesis.

International audienceOBJECTIVE: The proinflammatory phenotype induced by low laminar shear stress (LSS) is implicated in atherogenesis. The kinin B1 receptor (B1R), known to be induced by inflammatory stimuli, exerts many proinflammatory effects including vasodilatation and leukocyte recruitment. We investigated whether low LSS is a stimulus for endothelial B1R expression and function. METHODS AND RESULTS: Human and mouse atherosclerotic plaques expressed high level of B1R mRNA and protein. In addition, B1R expression was upregulated in the aortic arch (low LSS region) of ApoE(-/-) mice fed a high-fat diet compared to vascular regions of high LSS and animals fed normal chow. Of interest, a greater expression of B1R was noticed in endothelial cells from regions of low LSS in aortic arch of ApoE(-/-) mice. B1R was also upregulated in human umbilical vein endothelial cells (HUVECs) exposed to low LSS (0 to 2 dyn/cm(2)) compared to physiological LSS (6 to 10 dyn/cm(2)): an effect similarly evident in murine vascular tissue perfused ex vivo. Functionally, B1R activation increased prostaglandin and CXCL5 expression in cells exposed to low, but not physiological, LSS. IL-1beta and ox-LDL induced B1R expression and function in HUVECs, a response substantially enhanced under low LSS conditions and inhibited by blockade of NFkappaB activation. CONCLUSIONS: Herein, we show that LSS is a major determinant of functional B1R expression in endothelium. Furthermore, whereas physiological high LSS is a powerful repressor of this inflammatory receptor, low LSS at sites of atheroma are associated with substantial upregulation, identifying this receptor as a potential therapeutic target