836 resultados para Contapassi mHealth Android Smartwatch Smartphone SensorFusion Range_Articolari


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While navigation systems for cars are in widespread use, only recently, indoor navigation systems based on smartphone apps became technically feasible. Hence tools in order to plan and evaluate particular designs of information provision are needed. Since tests in real infrastructures are costly and environmental conditions cannot be held constant, one must resort to virtual infrastructures. This paper presents the development of an environment for the support of the design of indoor navigation systems whose center piece consists in a hands-free navigation method using the Microsoft Kinect in the four-sided Definitely Affordable Virtual Environment (DAVE). Navigation controls using the user's gestures and postures as the input to the controls are designed and implemented. The installation of expensive and bulky hardware like treadmills is avoided while still giving the user a good impression of the distance she has traveled in virtual space. An advantage in comparison to approaches using a head mounted display is that the DAVE allows the users to interact with their smartphone. Thus the effects of different indoor navigation systems can be evaluated already in the planning phase using the resulting system

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myTU, eine persnliche Lernplattform fr Smartphones, die seit 2011 an der Technischen Universitt Bergakademie Freiberg im Einsatz ist, wird zuknftig mit neuen und erweiterten Funktionen ausgestattet. Ziel ist es eine generalisierte Lernplattform fr alle Hochschulen anzubieten, die das BYOD-Konzept konsequent umsetzt. Ausgehend von der derzeitigen Struktur und Umfang des Projektes wird eine Verbindung mit OPAL geschaffen, das Layout und die Schnittstellen generalisiert, Funktionen erweitert und ein mehrstufiges Authentisierungskonzept entwickelt und integriert. Im Folgenden wird der Status Quo erlutert und neue Konzepte des Projektes vorgestellt.

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Mit der Idee eines generischen, an vielfltige Hochschulanforderungen anpassbaren Studierenden-App-Frameworks haben sich innerhalb des Arbeitskreises Web der ZKI ca. 30 Hochschulen zu einem Entwicklungsverbund zusammengefunden. Ziel ist es, an den beteiligten Einrichtungen eine umfassende Zusammenstellung aller elektronischen Studienservices zu evaluieren, bergreifende Daten- und Metadatenmodelle fr die Beschreibung dieser Dienste zu erstellen und Schnittstellen zu den gngigen Campusmanagementsystemen sowie zu Infrastrukturen der elektronischen Lehre (LMS, Druckdienste, elektronischen Katalogen usw.) zu entwickeln. In einem abschlieenden Schritt werden auf dieser Middleware aufsetzende Studienmanagement-Apps fr Studierende erstellt, die die verschiedenen Daten- und Kommunikationsstrme der standardisierten Dienste und Kommunikationskanle bndeln und in eine fr den Studierenden leicht zu durchschauende, navigationsfreundliche Aufbereitung kanalisiert. Mit der Konzeption eines dezentralen, ber eine Vielzahl von Hochschulen verteilten Entwicklungsprojektes unter einer zentralen Projektleitung wird sichergestellt, dass redundante Entwicklungen vermieden, bundesweit standardisierte Serviceangebote angeboten und Wissenstransferprozesse zwischen einer Vielzahl von Hochschulen zur Nutzung mobiler Devices (Smartphones, Tablets und entsprechende Apps) angeregt werden knnen. Die Untersttzung der Realisierung klarer Schnittstellenspezifikationen zu Campusmanagementsystemen durch deren Anbieter kann durch diese breite Interessensgemeinschaft ebenfalls gestrkt werden. Weiterhin zentraler Planungsinhalt ist ein Angebot fr den App-Nutzer zum Aufbau eines datenschutzrechtlich integeren, persnlichen E-Portfolios. Details finden sich im Kapitel Projektziele weiter unten.

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Today, pupils at the age of 15 have spent their entire life surrounded by and interacting with diverse forms of computers. It is a routine part of their day-to-day life and by now computer-literacy is common at very early age. Over the past five years, technology for teens has become predominantly mobile and ubiquitous within every aspect of their lives. To them, being online is an implicitness. In Germany, 88% of youth aged between 12-19 years own a smartphone and about 20% use the Internet via tablets. Meanwhile, more and more young learners bring their devices into the classroom and pupils increasingly demand for innovative and motivating learning scenarios that strongly respond to their habits of using media. With this development, a shift of paradigm is slowly under way with regard to the use of mobile technology in education. By now, a large body of literature exists, that reports concepts, use-cases and practical studies for effectively using technology in education. Within this field, a steadily growing body of research has developed that especially examines the use of digital games as instructional strategy. The core concern of this thesis is the design of mobile games for learning. The conditions and requirements that are vital in order to make mobile games suitable and effective for learning environments are investigated. The base for exploration is the pattern approach as an established form of templates that provide solutions for recurrent problems. Building on this acknowledged form of exchanging and re-using knowledge, patterns for game design are used to classify the many gameplay rules and mechanisms in existence. This research draws upon pattern descriptions to analyze learning game concepts and to abstract possible relationships between gameplay patterns and learning outcomes. The linkages that surface are the starting bases for a series of game design concepts and their implementations are subsequently evaluated with regard to learning outcomes. The findings and resulting knowledge from this research is made accessible by way of implications and recommendations for future design decisions.

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In this paper, we describe agent-based content retrieval for opportunistic networks, where requesters can delegate content retrieval to agents, which retrieve the content on their behalf. The approach has been implemented in CCNx, the open source CCN framework, and evaluated on Android smart phones. Evaluations have shown that the overhead of agent delegation is only noticeable for very small content. For content larger than 4MB, agent-based content retrieval can even result in a throughput increase of 20% compared to standard CCN download applications. The requester asks every probe interval for agents that have retrieved the desired content. Evaluations have shown that a probe interval of 30s delivers the best overall performance in our scenario because the number of transmitted notification messages can be decreased by up to 80% without significantly increasing the download time.

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BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

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Web surveys are becoming increasingly popular in survey research. Compared with face-to-face, telephone and mail surveys, web surveys may contain a different and new source of measurement error and bias: the type of device that respondents use to answer the survey questions. To the best of our knowledge, this is the first study that tests whether the use of mobile devices affects survey characteristics and stated preferences in a web-based choice experiment. The web survey was carried out in Germany with 3,400 respondents, of which 12 per cent used a mobile device (i.e. tablet or smartphone), and comprised a stated choice experiment on externalities of renewable energy production using wind, solar and biomass. Our main finding is that survey characteristics such as interview length and acquiescence tendency are affected by the device used. In contrast to what might be expected, we find that, compared with respondents using desktop computers and laptops, mobile device users spent more time to answer the survey and are less likely to be prone to acquiescence bias. In the choice experiment, mobile device users tended to be more consistent in their stated choices, and there are differences in willingness to pay between both subsamples.

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Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meals effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 12%, which led to a mean absolute error of 6 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

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In this paper, we present a revolutionary vision of 5G networks, in which SDN programs wireless network functions, and where Mobile Network Operators (MNO), Enterprises, and Over-The-Top (OTT) third parties are provided with NFV-ready Network Store. The proposed Network Store serves as a digital distribution platform of programmable Virtualized Network Functions (VNFs) that enable 5G application use-cases. Currently existing application stores, such as Apple's App Store for iOS applications, Google's Play Store for Android, or Ubuntu's Software Center, deliver applications to user specific software platforms. Our vision is to provide a digital marketplace, gathering 5G enabling Network Applications and Network Functions, written to run on top of commodity cloud infrastructures, connected to remote radio heads (RRH). The 5G Network Store will be the same to the cloud as the application store is currently to a software platform.

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Spurred by the consumer market, companies increasingly deploy smartphones or tablet computers in their operations. However, unlike private users, companies typically struggle to cover their needs with existing applications, and therefore expand mobile software platforms through customized applications from multiple software vendors. Companies thereby combine the concepts of multi-sourcing and software platform ecosystems in a novel platform-based multi-sourcing setting. This implies, however, the clash of two different approaches towards the coordination of the underlying one-to-many inter-organizational relationships. So far, however, little is known about impacts of merging coordination approaches. Relying on convention theory, we addresses this gap by analyzing a platform-based multi-sourcing project between a client and six software vendors, that develop twenty-three custom-made applications on a common platform (Android). In doing so, we aim to understand how unequal coordination approaches merge, and whether and for what reason particular coordination mechanisms, design decisions, or practices disappear, while new ones emerge.

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BACKGROUND The European AIDS Clinical Society (EACS) guidelines are intended for all clinicians involved in the care of HIV-positive persons, and are available in print, online, and as a free App for download for iPhone and Android. GUIDELINE HIGHLIGHTS The 2015 version of the EACS guidelines contains major revisions in all sections; antiretroviral treatment (ART), comorbidities, coinfections and opportunistic diseases. Among the key revisions is the recommendation of ART for all HIV-positive persons, irrespectively of CD4 count, based on the Strategic Timing of AntiRetroviral Treatment (START) study results. The recommendations for the preferred and the alternative ART options have also been revised, and a new section on the use of pre-exposure prophylaxis (PrEP) has been added. A number of new antiretroviral drugs/drug combinations have been added to the updated tables on drug-drug interactions, adverse drug effects, dose adjustment for renal/liver insufficiency and for ART administration in persons with swallowing difficulties. The revisions of the coinfection section reflect the major advances in anti-hepatitis C virus (HCV) treatment with direct-acting antivirals with earlier start of treatment in individuals at increased risk of liver disease progression, and a phasing out of interferon-containing treatment regimens. The section on opportunistic diseases has been restructured according to individual pathogens/diseases and a new overview table has been added on CD4 count thresholds for different primary prophylaxes. CONCLUSIONS The diagnosis and management of HIV infection and related coinfections, opportunistic diseases and comorbidities continue to require a multidisciplinary effort for which the 2015 version of the EACS guidelines provides an easily accessable and updated overview.

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During the last decade wireless mobile communications have progressively become part of the peoples daily lives, leading users to expect to be alwaysbest-connected to the Internet, regardless of their location or time of day. This is indeed motivated by the fact that wireless access networks are increasingly ubiquitous, through different types of service providers, together with an outburst of thoroughly portable devices, namely laptops, tablets, mobile phones, among others. The anytime and anywhere connectivity criterion raises new challenges regarding the devices battery lifetime management, as energy becomes the most noteworthy restriction of the end-users satisfaction. This wireless access context has also stimulated the development of novel multimedia applications with high network demands, although lacking in energy-aware design. Therefore, the relationship between energy consumption and the quality of the multimedia applications perceived by end-users should be carefully investigated. This dissertation addresses energy-efficient multimedia communications in the IEEE 802.11 standard, which is the most widely used wireless access technology. It advances the literature by proposing a unique empirical assessment methodology and new power-saving algorithms, always bearing in mind the end-users feedback and evaluating quality perception. The new EViTEQ framework proposed in this thesis, for measuring video transmission quality and energy consumption simultaneously, in an integrated way, reveals the importance of having an empirical and high-accuracy methodology to assess the trade-off between quality and energy consumption, raised by the new end-users requirements. Extensive evaluations conducted with the EViTEQ framework revealed its flexibility and capability to accurately report both video transmission quality and energy consumption, as well as to be employed in rigorous investigations of network interface energy consumption patterns, regardless of the wireless access technology. Following the need to enhance the trade-off between energy consumption and application quality, this thesis proposes the Optimized Power save Algorithm for continuous Media Applications (OPAMA). By using the end-users feedback to establish a proper trade-off between energy consumption and application performance, OPAMA aims at enhancing the energy efficiency of end-users devices accessing the network through IEEE 802.11. OPAMA performance has been thoroughly analyzed within different scenarios and application types, including a simulation study and a real deployment in an Android testbed. When compared with the most popular standard power-saving mechanisms defined in the IEEE 802.11 standard, the obtained results revealed OPAMAs capability to enhance energy efficiency, while keeping end-users Quality of Experience within the defined bounds. Furthermore, OPAMA was optimized to enable superior energy savings in multiple station environments, resulting in a new proposal called Enhanced Power Saving Mechanism for Multiple station Environments (OPAMA-EPS4ME). The results of this thesis highlight the relevance of having a highly accurate methodology to assess energy consumption and application quality when aiming to optimize the trade-off between energy and quality. Additionally, the obtained results based both on simulation and testbed evaluations, show clear benefits from employing userdriven power-saving techniques, such as OPAMA, instead of IEEE 802.11 standard power-saving approaches.

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Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, Inselspital (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospitals restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the users experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

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Presentacin en la 4ta. Conferencia Regional del CLACAI. Reafirmando el legado de Cairo: Aborto legal y seguro. Lima, 21 y 22 de Agosto de 2014

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En un ejercicio no extenuante la frecuencia cardaca (FC) guarda una relacin lineal con el consumo mximo de oxgeno (V O2max) y se suele usar como uno de los parmetros de referencia para cuantificar la capacidad del sistema cardiovascular. Normalmente la frecuencia cardaca puede remplazar el porcentaje de V O2max en las prescripciones bsicas de ejercicio para la mejora de la resistencia aerbica. Para obtener los mejores resultados en la mejora de la resistencia aerbica, el entrenamiento de los individuos se debe hacer a una frecuencia cardaca suficientemente alta, para que el trabajo sea de predominio dinmico con la fosforilacin oxidativa como fuente energtica primaria, pero no tan elevada que pueda suponer un riesgo de infarto de miocardio para el sujeto que se est entrenando. Los programas de entrenamiento de base mnima y de base ptima, con ejercicios de estiramientos para prevenir lesiones, son algunos de los programas ms adecuados para el entrenamiento de la resistencia aerbica porque maximizan los beneficios y minimizan los riesgos para el sistema cardiovascular durante las sesiones de entrenamiento. En esta tesis, se ha definido un modelo funcional para sistemas de inteligencia ambiental capaz de monitorizar, evaluar y entrenar las cualidades fsicas que ha sido validado cuando la cualidad fsica es la resistencia aerbica. El modelo se ha implementado en una aplicacin Android utilizando la camiseta inteligente GOW running de la empresa Weartech. El sistema se ha comparado en el Laboratorio de Fisiologa del Esfuerzo (LFE) de la Universidad Politcnica de Madrid (UPM) durante la realizacin de pruebas de esfuerzo. Adems se ha evaluado un sistema de guiado con voz para los entrenamientos de base mnima y de base ptima. Tambin el desarrollo del software ha sido validado. Con el uso de cuestionarios sobre las experiencias de los usuarios utilizando la aplicacin se ha evaluado el atractivo de la misma. Por otro lado se ha definido una nueva metodologa y nuevos tipos de cuestionarios diseados para evaluar la utilidad que los usuarios asignan al uso de un sistema de guiado por voz. Los resultados obtenidos confirman la validez del modelo. Se ha obtenido una alta concordancia entre las medidas de FC hecha por la aplicacin Android y el LFE. Tambin ha resultado que los mtodos de estimacin del VO2max de los dos sistemas pueden ser intercambiables. Todos los usuarios que utilizaron el sistema de guiado por voz para entrenamientos de 10 base mnima y de base ptimas de la resistencia aerbica consiguieron llevar a cabo las sesiones de entrenamientos con un 95% de xito considerando unos mrgenes de error de un 10% de la frecuencia cardaca mxima terica. La aplicacin fue atractiva para los usuarios y hubo tambin una aceptacin del sistema de guiado por voz. Se ha obtenido una evaluacin psicolgica positiva de la satisfaccin de los usuarios que interactuaron con el sistema. En conclusin, se ha demostrado que es posible desarrollar sistemas de Inteligencia Ambiental en dispositivos mviles para la mejora de la salud. El modelo definido en la tesis es el primero modelo funcional terico de referencia para el desarrollo de este tipo de aplicaciones. Posteriores estudios se realizarn con el objetivo de extender dicho modelo para las dems cualidades fsicas que suponen modelos fisiolgicos ms complejos como por ejemplo la flexibilidad. Abstract In a non-strenuous exercise, the heart rate (HR) shows a linear relationship with the maximum volume of oxygen consumption (V O2max) and serves as an indicator of performance of the cardiovascular system. The heart rate replaces the %V O2max in exercise program prescription to improve aerobic endurance. In order to achieve an optimal effect during endurance training, the athlete needs to work out at a heart rate high enough to trigger the aerobic metabolism, while avoiding the high heart rates that bring along significant risks of myocardial infarction. The minimal and optimal base training programs, followed by stretching exercises to prevent injuries, are adequate programs to maximize benefits and minimize health risks for the cardiovascular system during single session training. In this thesis, we have defined an ambient intelligence system functional model that monitors, evaluates and trains physical qualities, and it has been validated for aerobic endurance. It is based on the Android System and the GOW Running smart shirt. The system has been evaluated during functional assessment stress testing of aerobic endurance in the Stress Physiology Laboratory (SPL) of the Technical University of Madrid (UPM). Furthermore, a voice system, designed to guide the user through minimal and optimal base training programs, has been evaluated. Also the software development has been evaluated. By means of user experience questionnaires, we have rated the attractiveness of the android application. Moreover, we have defined a methodology and a new kind of questionnaires in order to assess the user experience with the audio exercise guide system. The results obtained confirm the model. We have a high similarity between HR measurements made of our system and the one used by SPL. We have also a high correlation between the VO2max estimations of our system and the SPL system. All users, that tried the voice guidance system for minimal and optimal base training programs, were able to perform the 95% of the training session with an error lower than the 10% of theoretical maximum heart rate. The application appeared attractive to the users, and it has also been proven that the voice guidance system was useful. As result we obtained a positive evaluation of the users' satisfaction while they interacted with the system. In conclusion, it has been demonstrated that is possible to develop mobile Ambient Intelligence applications for the improvement of healthy lifestyle. AmIRTEM model is the first theoretical reference functional model for the design of this kind of applications. Further studies will be realized in order to extend the AmIRTEM model to other physical qualities whose physiological models are more complex than the aerobic endurance.