A Novel Low-Cost Sensor Prototype for Nocturia Monitoring in Older People

Indexación: Scopus.This work was supported in part by CORFO - CENS 16CTTS-66390 through the National Center on Health Information Systems, in part by the National Commission for Scientific and Technological Research (CONICYT) through the program STIC-AMSUD 17STIC-03: ‘‘e-MONITOR âĂŞ Chronic Disease: Ambient Assisted Living and vital teleMONOTORing for e-health,’’ FONDEF ID16I10449 ‘‘Sistema inteligente para la gestión y análisis de la dotación de camas en la red asistencial del sector público,’’ and MEC80170097 ‘‘Red de colaboración científica entre universidades nacionales e internacionales para la estructuración del doctorado y magister en informática médica en la Universidad de Valparaíso.’’ The work of V. H. C. de Albuquerque was supported by the Brazilian National Council for Research and Development (CNPq) under Grant #304315/2017-6.Nocturia is frequently defined as the necessity to get out of bed at least one time during the night to urinate, with each of these episodes being preceded and continued by sleep. Several studies suggest that an increase of nocturia is seen with the onset of age, occurring in around 70% of adults over the age of 70. Its appearance is associated with detrimental quality of life for those who present nocturia, since it leads to daytime sleepiness, cognitive dysfunction, among others. Currently, a voiding diary is necessary for nocturia assessment; these are prone to bias due to their inherent subjectivity. In this paper, we present the design of a low-cost device that automatically detects micturition events. The device obtained 73% in sensibility and 81% in specificity; these results show that systems such as the proposed one can be a valuable tool for the medical team when evaluating nocturia. © 2013 IEEE.https://ieeexplore.ieee.org/document/845445

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)

A novel monitoring system for fall detection in older people

Indexación: Scopus.This work was supported in part by CORFO - CENS 16CTTS-66390 through the National Center on Health Information Systems, in part by the National Commission for Scientific and Technological Research (CONICYT) through the Program STIC-AMSUD 17STIC-03: ‘‘MONITORing for ehealth," FONDEF ID16I10449 ‘‘Sistema inteligente para la gestión y análisis de la dotación de camas en la red asistencial del sector público’’, and in part by MEC80170097 ‘‘Red de colaboración científica entre universidades nacionales e internacionales para la estructuración del doctorado y magister en informática médica en la Universidad de Valparaíso’’. The work of V. H. C. De Albuquerque was supported by the Brazilian National Council for Research and Development (CNPq), under Grant 304315/2017-6.Each year, more than 30% of people over 65 years-old suffer some fall. Unfortunately, this can generate physical and psychological damage, especially if they live alone and they are unable to get help. In this field, several studies have been performed aiming to alert potential falls of the older people by using different types of sensors and algorithms. In this paper, we present a novel non-invasive monitoring system for fall detection in older people who live alone. Our proposal is using very-low-resolution thermal sensors for classifying a fall and then alerting to the care staff. Also, we analyze the performance of three recurrent neural networks for fall detections: Long short-term memory (LSTM), gated recurrent unit, and Bi-LSTM. As many learning algorithms, we have performed a training phase using different test subjects. After several tests, we can observe that the Bi-LSTM approach overcome the others techniques reaching a 93% of accuracy in fall detection. We believe that the bidirectional way of the Bi-LSTM algorithm gives excellent results because the use of their data is influenced by prior and new information, which compares to LSTM and GRU. Information obtained using this system did not compromise the user's privacy, which constitutes an additional advantage of this alternative. © 2013 IEEE.https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=842305

Conexiones y/o síntesis entre saberes adquiridos en el aprendizaje del repertorio de contrabajo : un estudio de caso

A aprendizagem da música acadêmica ocidental a partir da tradição escrita é moldada por um somatório de aspectos relacionados ao conhecimento teórico, ao conhecimento prático, aos aspectos da própria técnica do instrumento e ao distanciamento histórico em relação a uma determinada música. Para aprender, o aluno enfrenta o desafio de ter que tomar decisões, resolver problemas, além de ter que lidar com todas as informações ainda não vivenciadas e processá-las para poder interpretar o repertório disponível para seu próprio instrumento. O objetivo deste trabalho foi investigar as conexões e/ou sínteses entre conhecimentos adquiridos na aprendizagem do repertório de contrabaixo. O delineamento insere-se em uma abordagem qualitativa, contemplando o estudo de caso como estratégia de investigação. Cecília (23 anos), nome fictício do caso estudado, aluna de graduação (6º semestre) no momento da coleta de dados. O repertório de aprendizagem para este semestre foi o Concerto nº 2 de Carl Ditters von Dittersdorf (1739-1799). As técnicas de coleta de dados utilizadas foram: (i) observação da gravação de sessões práticas individuais, (ii) observação de sala de aula e (iii) entrevistas, desenvolvidas nas três instâncias de coleta de dados propostas na metodologia. Como referencial teórico utilizou-se, por um lado, o conceito de mobilização do conhecimento proposto por Charlot (2006) e, por outro lado, o modelo de conhecimento musical proposto por Elliott (1995). Para a análise de dados, categorizações sobre o fenômeno estudado foram construídas sob a ótica da análise de conteúdo de cunho interpretativo, permitindo destacar os aspectos trabalhados em situações de aula e prática musical. Com base nos resultados obtidos, proposições quanto à síntese e conexões foram realizadas. A síntese pode ser observada em situações intencionais (ou cumulativas) de uma dada ação, apontando tanto a vontade de mobilizar-se para aprender (Charlot, 2006) como o sentido de chegar a um ponto (performaticamente pela própria ação/realização musical). Salienta-se ainda que tal chegada a um dado ponto foi corroborada pelo sentimento e demonstração de satisfação com o trabalho realizado. Quanto às conexões, estas foram apresentadas por meio das formas de se conectar com os diferentes conteúdos presentes na prática, bem como aqueles conteúdos que se mostravam externos ao aluno, necessitando serem incorporados em seu processo de aprendizagem.El aprendizaje de la música académica occidental de tradición escrita está moldeado por una sumatoria de aspectos referentes al conocimiento teórico, al conocimiento práctico, vertientes de la técnica propia del instrumento y el distanciamiento histórico respecto de una música en particular. Para aprender, el estudiante se enfrenta al desafío de tener que tomar decisiones, resolver problemas, además de tener que lidiar con toda la información aún no experimentada y procesarla de manera de poder interpretar el repertorio disponible para su propio instrumento. El presente trabajo tuvo como objetivo investigar las conexiones y/o síntesis entre saberes adquiridos en el aprendizaje del repertorio de contrabajo. El diseño se enmarca en un enfoque cualitativo, contemplando el estudio de caso como estrategia de investigación. Cecilia (23 años), nombre ficticio del caso estudiado, estudiante de grado (6º semestre) en el período de la recolección de los datos. El repertorio en aprendizaje em este semestre fue el Concierto N° 2 de Carl Ditters von Dittersdorf (1739-1799). Las técnicas de recolección de datos utilizadas fueron: (i) observación del registro de sesiones de práctica individual, (ii) observación de aula, y (iii) entrevistas, desarrolladas en las tres instancias de recolección de datos propuesta en la metodología. Como referencial teórico se utilizaron, por un lado, el concepto de movilización de conocimientos propuesto por Charlot (2006) y, por otro lado, el modelo de conocimiento musical propuesto por Elliott (1995). Para el análisis de los datos, se construyeron categorizaciones sobre el fenómeno estudiado desde la perspectiva del análisis de contenido de carácter interpretativo, que permitieron resaltar los aspectos trabajados en situaciones de clase y práctica instrumental. Con base en los resultados obtenidos, se realizaron proposiciones acerca de la síntesis y conexiones. La síntesis se puede observar en situaciones intencionales (o acumulativas) de una determinada acción, señalando tanto la voluntad de movilizarse para aprender (Charlot, 2006), como el sentido de llegar a un punto (performaticamente por la propia acción/realización musical). También cabe señalar que dicha llegada a un punto determinado fue corroborada por el sentimiento y demostración de satisfacción por el trabajo realizado. En cuanto a las conexiones, estos fueron presentados a través de formas de conectar con los diferentes contenidos presentes en la práctica, así como aquellos contenidos que eran externos al estudiante y necesitaban ser incorporados a su proceso de aprendizaje.The learning of Western academic music from the written tradition is shaped by a sum of aspects related to theoretical knowledge, practical knowledge, aspects of the instrument's own technique and the historical distance with respect to a particular music. In order to learn, the student faces the challenge of making decisions, solve problems, as well as to deal with all the information not yet experienced and process it in order to be able to perform the repertoire available for his own instrument. The objective of this work was to investigate the connections and/or synthesis between knowledge acquired in learning the double bass repertoire. The research design is part of a qualitative approach, contemplating the case study as an investigation strategy. Cecilia (23 years old), fictitious name of the case studied, a bachelor student (6th semester) at the time of data collection. The learning repertoire for this semester was Concerto No. 2 by Carl Ditters von Dittersdorf (1739-1799). The data collection techniques used were: (i) observation of the recording of individual practice sessions, (ii) classroom observation, and (iii) interviews, developed in the three instances of data collection proposed in the methodology. As a theoretical reference, on the one hand, the concept of knowledge mobilization proposed by Charlot (2006) and, on the other hand, the model of musical knowledge proposed by Elliott (1995) were used. For data analysis, categorizations about the phenomenon studied were built from the perspective of content analysis of an interpretative nature, allowing to highlight the aspects worked on in class situations and instrumental practice. Based on the results obtained, propositions about the synthesis and connections were made. The synthesis can be observed in intentional (or cumulative) situations of a certain action, indicating both the will to mobilize to learn (Charlot, 2006), and the sense of arrive to a point (performatically by the action/musical realization itself). It should also be noted that arrival was corroborated by the feeling and demonstration of satisfaction for the work done. Regarding the connections, these were presented through ways to connect with the different contents present in the practice, as well as those contents that were external to the student and needed to be incorporated into their learning process

Extreme Value at Risk and Expected Shortfall during Financial Crisis

This paper investigates Value at Risk and Expected Shortfall for CAC 40, S&P 500, Wheat and Crude Oil indexes during the 2008 financial crisis. We show an underestimation of the risk of loss for the unconditional VaR models as compared with the conditional models. This underestimation is stronger using the historical VaR approach than when using the extreme values theory VaR model. Even in 2008 financial crisis, the conditional EVT model is more accurate and reliable for predicting the asset risk losses. Banks have no interest in using it because the Basel II agreement penalizes banks using accuracy models like the conditional EVT model, and this is the case for the assets being studied in this paper.Market risk; Value at Risk; EVT; GARCH; Financial crisis; Basel requirements

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

Highly-efficient fog-based deep learning AAL fall detection system

[EN] Falls is one of most concerning accidents in aged population due to its high frequency and serious repercussion; thus, quick assistance is critical to avoid serious health consequences. There are several Ambient Assisted Living (AAL) solutions that rely on the technologies of the Internet of Things (IoT), Cloud Computing and Machine Learning (ML). Recently, Deep Learning (DL) have been included for its high potential to improve accuracy on fall detection. Also, the use of fog devices for the ML inference (detecting falls) spares cloud drawback of high network latency, non-appropriate for delay-sensitive applications such as fall detectors. Though, current fall detection systems lack DL inference on the fog, and there is no evidence of it in real environments, nor documentation regarding the complex challenge of the deployment. Since DL requires considerable resources and fog nodes are resource-limited, a very efficient deployment and resource usage is critical. We present an innovative highly-efficient intelligent system based on a fog-cloud computing architecture to timely detect falls using DL technics deployed on resource-constrained devices (fog nodes). We employ a wearable tri-axial accelerometer to collect patient monitoring data. In the fog, we propose a smart-IoT-Gateway architecture to support the remote deployment and management of DL models. We deploy two DL models (LSTM/GRU) employing virtualization to optimize resources and evaluate their performance and inference time. The results prove the effectiveness of our fall system, that provides a more timely and accurate response than traditional fall detector systems, higher efficiency, 98.75% accuracy, lower delay, and service improvement.This research was supported by the Ecuadorian Government through the Secretary of Higher Education, Science, Technology, and Innovation (SENESCYT) and has received funding from the European Union's Horizon 2020 research and innovation program as part of the ACTIVAGE project under Grant 732679.Sarabia-Jácome, D.; Usach, R.; Palau Salvador, CE.; Esteve Domingo, M. (2020). Highly-efficient fog-based deep learning AAL fall detection system. Internet of Things. 11:1-19. https://doi.org/10.1016/j.iot.2020.100185S11911“World Population Ageing.” [Online]. Available: http://www.un.org/esa/population/publications/worldageing19502050/. [Accessed: 23-Sep-2018].“Falls, ” World Health Organization. [Online]. Available: http://www.who.int/news-room/fact-sheets/detail/falls. [Accessed: 20-Sep-2018].Rashidi, P., & Mihailidis, A. (2013). A Survey on Ambient-Assisted Living Tools for Older Adults. IEEE Journal of Biomedical and Health Informatics, 17(3), 579-590. doi:10.1109/jbhi.2012.2234129Bousquet, J., Kuh, D., Bewick, M., Strandberg, T., Farrell, J., Pengelly, R., … Bringer, J. (2015). Operative definition of active and healthy ageing (AHA): Meeting report. Montpellier October 20–21, 2014. European Geriatric Medicine, 6(2), 196-200. doi:10.1016/j.eurger.2014.12.006“WHO | What is Healthy Ageing?”[Online]. Available: http://www.who.int/ageing/healthy-ageing/en/. [Accessed: 19-Sep-2018].Fei, X., Shah, N., Verba, N., Chao, K.-M., Sanchez-Anguix, V., Lewandowski, J., … Usman, Z. (2019). CPS data streams analytics based on machine learning for Cloud and Fog Computing: A survey. Future Generation Computer Systems, 90, 435-450. doi:10.1016/j.future.2018.06.042W. Zaremba, “Recurrent neural network regularization,” no. 2013, pp. 1–8, 2015.Hochreiter, S., & Schmidhuber, J. (1997). Long Short-Term Memory. Neural Computation, 9(8), 1735-1780. doi:10.1162/neco.1997.9.8.1735J. Chung, C. Gulcehre, K. Cho, and Y. Bengio, “Empirical evaluation of gated recurrent neural networks on sequence modeling,” pp. 1–9, 2014.N. Zerrouki, F. Harrou, Y. Sun, and A. Houacine, “Vision-based human action classification,” vol. 18, no. 12, pp. 5115–5121, 2018.Panahi, L., & Ghods, V. (2018). Human fall detection using machine vision techniques on RGB–D images. Biomedical Signal Processing and Control, 44, 146-153. doi:10.1016/j.bspc.2018.04.014Y. Li, K.C. Ho, and M. Popescu, “A microphone array system for automatic fall detection,” vol. 59, no. 2, pp. 1291–1301, 2012.Taramasco, C., Rodenas, T., Martinez, F., Fuentes, P., Munoz, R., Olivares, R., … Demongeot, J. (2018). A Novel Monitoring System for Fall Detection in Older People. IEEE Access, 6, 43563-43574. doi:10.1109/access.2018.2861331C. Wang et al., “Low-power fall detector using triaxial accelerometry and barometric pressure sensing,” vol. 12, no. 6, pp. 2302–2311, 2016.S.B. Khojasteh and E. De Cal, “Improving fall detection using an on-wrist wearable accelerometer,” pp. 1–28.Theodoridis, T., Solachidis, V., Vretos, N., & Daras, P. (2017). Human Fall Detection from Acceleration Measurements Using a Recurrent Neural Network. IFMBE Proceedings, 145-149. doi:10.1007/978-981-10-7419-6_25F. Sposaro and G. Tyson, “iFall : an android application for fall monitoring and response,” pp. 6119–6122, 2009.A. Ngu, Y. Wu, H. Zare, A.P. B, B. Yarbrough, and L. Yao, “Fall detection using smartwatch sensor data with accessor architecture,” vol. 2, pp. 81–93.P. Jantaraprim and P. Phukpattaranont, “Fall detection for the elderly using a support vector machine,” no. 1, pp. 484–490, 2012.Aziz, O., Musngi, M., Park, E. J., Mori, G., & Robinovitch, S. N. (2016). A comparison of accuracy of fall detection algorithms (threshold-based vs. machine learning) using waist-mounted tri-axial accelerometer signals from a comprehensive set of falls and non-fall trials. Medical & Biological Engineering & Computing, 55(1), 45-55. doi:10.1007/s11517-016-1504-yV. Carletti, A. Greco, A. Saggese, and M. Vento, “A smartphone-based system for detecting falls using anomaly detection,” vol. 6978, 2017, pp. 490–499.Yacchirema, D., de Puga, J. S., Palau, C., & Esteve, M. (2018). Fall detection system for elderly people using IoT and Big Data. Procedia Computer Science, 130, 603-610. doi:10.1016/j.procs.2018.04.11

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