Quantifying the impact of scheduling and mobility on IR-UWB localization in body area networks

International audience—In the context of radiolocation in Wireless Body Area Networks (WBANs), nodes positions can be estimated through time-based ranging algorithms. For instance, the distance separating a couple of nodes can be estimated accurately by measuring the Round Trip Time of Flight of an Impulse Radio Ultra Wideband (IR-UWB) link. This measure usually relies on two or three messages transactions. Such exchanges take time and a rapid mobility of the nodes can reduce the ranging accuracy and consequently impact nodes localization process. In this paper, we quantify this localization error by confronting two broadcast-based optimized implementations of the three-way ranging algorithm with real mobility traces, acquired through a motion capture system. We then evaluate, in the same scenarios, the impact of the MAC-level scheduling of the packets within a TDMA frame localization accuracy. The results, obtained with the WSNet simulator, show that MAC scheduling can be utilized to mitigate the effect of nodes mobility

From the Characterization of Ranging Error to the Enhancement of Nodes Localization for Group of Wireless Body Area Networks

International audienceTime-based localization in Wireless Body Area Networks (WBANs), has attracted growing research interest for the last past years. Nodes positions can be estimated based on peer-to-peer radio transactions between devices. Indeed, the accuracy of the localization process could be highly affected by different factors , such as the WBAN channels where the signal is propagating through, as well as the nodes mobility that bias the peer-to-peer range estimation, and thus, the final achieved localization accuracy. The goal of this paper consists in characterizing the impact of mobility and WBAN channel on the ranging and localization estimation, based on real mobility traces acquired through a motion capture system. More specifically, the ranging error is evaluated over all the WBANs links (i.e. on-body, off-body and body-to-body links), while an impulse Radio Ultra-Wideband (IR-UWB) physical layer, as well as a TDMA-based Medium Access Control (MAC) are playing on. The simulation results show that the range measurement error can be modeled as a Gaussian distribution. To deal with the gaus-sianity observation of ranging error and to provide high positioning accuracy, an adjustable extended Kalman Filter (EKF) is proposed

Implementing a blood management protocol during the entire perioperative period allows a reduction in transfusion rate in major orthopedic surgery: a before-after study

BACKGROUND Patient blood management (PBM) must be promoted in orthopedic surgery and relies on different strategies implemented during the entire perioperative period. Our aim was to assess whether the introduction of a pre‐, intra‐, and postoperative PBM protocol combining erythropoietin (EPO), ferric carboxymaltose (FCM), and tranexamic acid was effective in reducing perioperative transfusion and postoperative anemia. STUDY DESIGN AND METHODS In a two‐phase prospective observational study, all patients admitted for total hip or knee arthroplasty were included the day before surgery. In Phase 1, use of EPO, iron, and tranexamic acid was left to the discretion of the anesthesiologists. In Phase 2, a protocol combining these treatments was implemented in the perioperative period. Perioperative hemoglobin levels and transfusion rates were recorded. RESULTS A total of 367 patients were included (184 and 183 in Phase 1 and 2, respectively). During Phase 2, implementing a PBM protocol allowed an increase in preoperative EPO prescription in targeted patients (i.e., with Hb < 13 g/dL; 18 [38%] vs. 34 [62%], p = 0.03) and in postoperative use of intravenous iron (12 [6%] vs. 32 [18%], p = 0.001) and tranexamic acid (157 [86%] vs. 171 [94%] patients, p = 0.02). In Phase 2, the number of patients who received transfusions (24 [13%] vs. 5 [3%], p = 0.0003) and of patients with a Hb level of less than 10 g/dL at discharge (46 [25%] vs. 26 [14%], p = 0.01) were reduced. CONCLUSION Introduction of a PBM protocol, using EPO, FCM, and tranexamic acid, reduces the number of perioperative transfusions and of patients with a Hb level of less than 10 g/dL at discharge

Structuring an event ontology for disease outbreak detection

<p>Abstract</p> <p>Background</p> <p>This paper describes the design of an event ontology being developed for application in the machine understanding of infectious disease-related events reported in natural language text. This event ontology is designed to support timely detection of disease outbreaks and rapid judgment of their alerting status by 1) bridging a gap between layman's language used in disease outbreak reports and public health experts' deep knowledge, and 2) making multi-lingual information available.</p> <p>Construction and content</p> <p>This event ontology integrates a model of experts' knowledge for disease surveillance, and at the same time sets of linguistic expressions which denote disease-related events, and formal definitions of events. In this ontology, rather general event classes, which are suitable for application to language-oriented tasks such as recognition of event expressions, are placed on the upper-level, and more specific events of the experts' interest are in the lower level. Each class is related to other classes which represent participants of events, and linked with multi-lingual synonym sets and axioms.</p> <p>Conclusions</p> <p>We consider that the design of the event ontology and the methodology introduced in this paper are applicable to other domains which require integration of natural language information and machine support for experts to assess them. The first version of the ontology, with about 40 concepts, will be available in March 2008.</p

Collective activities in a technology-mediated medical team. An analysis of epidemiological alert management

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An energy consumption model of variable preamble sampling MAC protocols for wireless sensor networks

Variable preamble sampling is a technique used for accessing the medium in low-power constrained networks such as wireless sensor networks. We provide an optimal bound for power consumption in preamble sampling techniques, and we present a model of this technique as a function of power consumption and time of radio utilization. We compare our model by means of experimental experiences performed with commercially-available hardware. Our model shows the tendency of the network for constant and variable preamble sampling approaches and may be used to analyze large networks without actually deploying the

Malevolent Creativity and Social Media: Creating Anti-immigration Communities on Twitter

This paper examines the role played by malevolent linguistic creativity in the generation and maintenance of anti-immigration communities on Twitter. In order to understand this phenomenon, we combined data science and qualitative techniques for the analysis of 112,789 pro- and anti-immigration tweets with a focus on their hashtags. Our analysis pointed to the fact that anti-immigration users on this social media platform have a distinct behavior and employ a series of specific strategies in creating echo chambers online. One of these strategies has to do with the use of new words and slogan variations which have a clear identity function and serve the pragmatic purpose of building community. Some reflections on the relation between creativity and social media are offered at the end