950 resultados para wearable, computing, body, area, network, bluetooth, android, wristOx2


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In questa tesi verranno affrontati due argomenti principali. Il primo sono le tecnologie wearable, comprendendo anche la notazione più generica di tecnologie bearable, che si stanno sempre più diffondendo negli ultimi anni; il secondo sono le BAN (Body Area Network), reti di sensori e dispositivi posti sul corpo umano, utilizzate per rendere possibile la comunicazione e l'interazione fra i device wearable. Si partirà da una trattazione di tipo generico degli argomenti, descrivendo l'architettura fisica delle tecnologie, con focalizzazione sull'aspetto informatico prevalentemente che su quello elettronico e telecomunicazionistico. Si parlerà degli attuali impieghi dei dispositivi e delle reti, e delle loro probabili evoluzioni future. Si introdurranno poi i protocolli di comunicazione principali e se ne analizzeranno le differenze, decretando se sia o meno conveniente puntare su uno o sull'altro rispetto alle esigenze di progetto. Verrà introdotto il sistema operativo Android, descrivendo la sua architettura e fornendo le informazioni basilari per comprendere al meglio il rapporto esistente con la tecnologia Bluetooth.

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Body Area Network, a new wireless networking paradigm, promises to revolutionize the healthcare applications. A number of tiny sensor nodes are strategically placed in and around the human body to obtain physiological information. The sensor nodes are connected to a coordinator or a data collector to form a Body Area Network. The tiny devices may sense physiological parameters of emergency in nature (e.g. abnormality in heart bit rate, increase of glucose level above the threshold etc.) that needs immediate attention of a physician. Due to ultra low power requirement of wireless body area network, most of the time, the coordinator and devices are expected to be in the dormant mode, categorically when network is not operational. This leads to an open question, how to handle and meet the QoS requirement of emergency data when network is not operational? Emergency handling becomes more challenging at the MAC layer, if the channel access related information is unknown to the device with emergency message. The aforementioned scenarios are very likely scenarios in a MICS (Medical Implant Communication Service, 402-405 MHz) based healthcare systems. This paper proposes a mechanism for timely and reliable transfer of emergency data in a MICS based Body Area Network. We validate our protocol design with simulation in a C++ framework. Our simulation results show that more than 99 p ercentage of the time emergency messages are reached at the coordinator with a delay of 400ms.

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Wireless Body Area Networks (WBANs) consist of a number of miniaturized wearable or implanted sensor nodes that are employed to monitor vital parameters of a patient over long duration of time. These sensors capture physiological data and wirelessly transfer the collected data to a local base station in order to be further processed. Almost all of these body sensors are expected to have low data-rate and to run on a battery. Since recharging or replacing the battery is not a simple task specifically in the case of implanted devices such as pacemakers, extending the lifetime of sensor nodes in WBANs is one of the greatest challenges. To achieve this goal, WBAN systems employ low-power communication transceivers and low duty cycle Medium Access Control (MAC) protocols. Although, currently used MAC protocols are able to reduce the energy consumption of devices for transmission and reception, yet they are still unable to offer an ultimate energy self-sustaining solution for low-power MAC protocols. This paper proposes to utilize energy harvesting technologies in low-power MAC protocols. This novel approach can further reduce energy consumption of devices in WBAN systems.

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Channel randomness can be exploited to generate secret keys. However, to ensure secrecy, it is necessary that the channel response of any eavesdropping party remain sufficiently de-correlated with that of the legitimate users'. In this paper, we investigate whether such de-correlation occurs for a body area network (BAN) operating in an indoor environment at 2.45 GHz. The hypothetical BAN configuration consisted of two legitimate transceivers, one situated on the user's left wrist and the other on the user's waist. The eavesdroppers were positioned in either a co-located or distributed manner in the area surrounding the BAN user. Using the simultaneous channel response measured at the legitimate BAN nodes and the eavesdropper positions for stationary and mobile scenarios, we analyze the localized correlation coefficient. This allows us to determine if it is possible to generate secret keys in the presence of multiple eavesdroppers in an indoor environment. Our experimental results show that although channel reciprocity was observed for both the stationary and the mobile scenarios, a higher de-correlation between the legitimate users' channels was observed for the stationary case. This indicates that mobile scenarios are better suited for secret key generation.

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Negli ultimi dieci anni si è rinnovata l’esigenza di sviluppare nuove tecnologie legate alla telemedicina, specie a seguito dello sviluppo dei sistemi di telecomunicazione che consentono ad ogni persona di avere a disposizione sistemi portatili, come gli smartphone, sempre connessi e pronti a comunicare. Lo stesso sviluppo si è avuto all’interno dei sistemi sanitari in cui è diventato fondamentale informatizzare le attività ospedaliere per via del contesto demografico a cui si va incontro: invecchiamento della popolazione e aumento del numero di pazienti affetti da malattie croniche. Tutti questi aspetti portano all’attuazione di un cambiamento strategico. Le Body Area Network, fulcro di questo lavoro di tesi, rappresentano la risposta a questa necessità. Si spiegano l'architettura e le tecnologie abilitanti per la realizzazione di queste reti di sensori, gli standard di comunicazione tramite i quali avviene la trasmissione dei dati e come le reti si interfacciano con i pazienti e le strutture sanitarie. Si conclude con una panoramica sui sensori di una BAN e alcuni esempi in commercio.

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The deployment of home-based smart health services requires effective and reliable systems for personal and environmental data management. ooperation between Home Area Networks (HAN) and Body Area Networks (BAN) can provide smart systems with ad hoc reasoning information to support health care. This paper details the implementation of an architecture that integrates BAN, HAN and intelligent agents to manage physiological and environmental data to proactively detect risk situations at the digital home. The system monitors dynamic situations and timely adjusts its behavior to detect user risks concerning to health. Thus, this work provides a reasoning framework to infer appropriate solutions in cases of health risk episodes. Proposed smart health monitoring approach integrates complex reasoning according to home environment, user profile and physiological parameters defined by a scalable ontology. As a result, health care demands can be detected to activate adequate internal mechanisms and report public health services for requested actions.

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The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.

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Body Area Networks are unique in that the large-scale mobility of users allows the network itself to travel across a diverse range of operating domains or even to enter new and unknown environments. This network mobility is unlike node mobility in that sensed changes in inter-network interference level may be used to identify opportunities for intelligent inter-networking, for example, by merging or splitting from other networks, thus providing an extra degree of freedom. This paper introduces the concept of context-aware bodynets for interactive environments using inter-network interference sensing. New ideas are explored at both the physical and link layers with an investigation based on a 'smart' office environment. A series of carefully controlled measurements of the mesh interconnectivity both within and between an ambulatory body area network and a stationary desk-based network were performed using 2.45 GHz nodes. Received signal strength and carrier to interference ratio time series for selected node to node links are presented. The results provide an insight into the potential interference between the mobile and static networks and highlight the possibility for automatic identification of network merging and splitting opportunities. © 2010 ACM.

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This paper investigates the characteristics of the complex received signal in body area networks for two environments at the opposite ends of the multipath spectrum at 2.45 GHz. Important attributes of the complex channel such as the Gaussianity of the quadrature components and power imbalance, which form the basis of many popular fading models, are investigated. It is found that in anechoic environments the assumption of Gaussian distributed quadrature components will not always yield a satisfactory fit. Using a complex received signal model which considers a non-isotropic scattered signal contribution along with the presence of an optional dominant signal component, we use an autocorrelation function originally derived for mobile-to-mobile communications to model the temporal behavior of a range of dynamic body area network channels with considerable success. In reverberant environments, it was observed that the real part of the complex autocorrelation function for body area network channels decayed slightly quicker than that expected in traditional land mobile channels. © 2013 IEEE.

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One of the major challenges in healthcare wireless body area network (WBAN) applications is to control congestion. Unpredictable traffic load, many-to-one communication nature and limited bandwidth occupancy are among major reasons that can cause congestion in such applications. Congestion has negative impacts on the overall network performance such as packet losses, increasing end-to-end delay and wasting energy consumption due to a large number of retransmissions. In life-critical applications, any delay in transmitting vital signals may lead to death of a patient. Therefore, in order to enhance the network quality of service (QoS), developing a solution for congestion estimation and control is imperative. In this paper, we propose a new congestion detection and control protocol for remote monitoring of patients health status using WBANs. The proposed system is able to detect congestion by considering local information such as buffer capacity and node rate. In case of congestion, the proposed system differentiates between vital signals and assigns priorities to them based on their level of importance. As a result, the proposed approach provides a better quality of service for transmitting highly important vital signs.

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Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed.