Wireless body sensor networks for health-monitoring applications

This is an author-created, un-copyedited version of an article accepted for publication in Physiological Measurement. The publisher is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at http://dx.doi.org/10.1088/0967-3334/29/11/R01

Optimal fault-tolerant placement of relay nodes in a mission critical wireless network

The operations of many critical infrastructures (e.g., airports) heavily depend on proper functioning of the radio communication network supporting operations. As a result, such a communication network is indeed a mission-critical communication network that needs adequate protection from external electromagnetic interferences. This is usually done through radiogoniometers. Basically, by using at least three suitably deployed radiogoniometers and a gateway gathering information from them, sources of electromagnetic emissions that are not supposed to be present in the monitored area can be localised. Typically, relay nodes are used to connect radiogoniometers to the gateway. As a result, some degree of fault-tolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given fault-tolerance. In this paper address the problem of computing a deployment for relay nodes that minimises the relay node network cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (fault-tolerance). We show that the above problem can be formulated as a Mixed Integer Linear Programming (MILP) as well as a Pseudo-Boolean Satisfiability (PB-SAT) optimisation problem and present experimental results com- paring the two approaches on realistic scenarios

An Energy Driven Architecture for Wireless Sensor Networks

Most wireless sensor networks operate with very limited energy sources-their batteries, and hence their usefulness in real life applications is severely constrained. The challenging issues are how to optimize the use of their energy or to harvest their own energy in order to lengthen their lives for wider classes of application. Tackling these important issues requires a robust architecture that takes into account the energy consumption level of functional constituents and their interdependency. Without such architecture, it would be difficult to formulate and optimize the overall energy consumption of a wireless sensor network. Unlike most current researches that focus on a single energy constituent of WSNs independent from and regardless of other constituents, this paper presents an Energy Driven Architecture (EDA) as a new architecture and indicates a novel approach for minimising the total energy consumption of a WS

Sensor node acceleration signatures and electromyography in synchronisation and sequencing analysis in sports: a rowing perspective

Following a review of the key determinants of successful rowing, a wireless body sensor network was developed to monitor boat and body segment acceleration and surface electromyography in major muscles recruited during the rowing stroke cycle. Its design was optimised to yield maximum information about the rowing stroke cycle from fewest sensors and minimise the power consumption of the nodes. The system was validated against the Qualisys motion capture and high-speed camera system with most Pearson correlation coefficients in excess of r = 0.8. On-land ergometer experimentation allowed muscle recruitment over the stroke cycle to be studied, with data from multiple experiments combined using correlation of the acceleration signatures of back and thigh nodes (r = 0.95). It was demonstrated that it was possible to identify one of the common rowing errors of ‘shooting-the-slide’ from the data collected, and that a marked decrease in correlation of good-to-bad technique over the drive phase of the stroke (0.95 reducing to 0.34 in the experiment undertaken) could be used to indicate the presence of this error. Extension of the wireless body sensor network to encompass boat and two oarsmen was demonstrated, allowing correlation of their rowing signatures to be studied, indicating their cohesion as a crew

Concept and development of an autonomous wearable micro-fluidic platform for real time pH sweat analysis

In this work the development of an autonomous, robust and wearable micro-fluidic platform capable of performing on-line analysis of pH in sweat is discussed. Through the means of an optical detection system based on a surface mount light emitting diode (SMD LED) and a light photo sensor as a detector, a wearable system was achieved in which real-time monitoring of sweat pH was performed during 55 minutes of cycling activity. We have shown how through systems engineering, integrating miniaturised electrical components, and by improving the micro-fluidic chip characteristics, the wearability, reliability and performance of the micro-fluidic platform was significantly improved

On-Body Channel Measurement Using Wireless Sensors

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Improve Performance Wireless Sensor Network Localization using RSSI and AEMM

Improve wireless sensor network localisation performance using RSSI and an advanced error minimisation method (AEMM). WSNs remain domain-specific and are typically deployed to support a single application. However, as WSN nodes become more powerful, it becomes increasingly important to investigate how multiple applications can share the same WSN infrastructure. Virtualisation is a technology that may allow for this sharing. The issues surrounding wireless sensor node localisation estimation are still being researched. There are a large number of Wireless Sensor Networks (WSNs) with limited computing, sensing, and energy capabilities. Localisation is one of the most important topics in wireless sensor networks (WSNs) because location information is typically useful for many applications. The locations of anchor nodes and the distances between neighbouring nodes are the primary data in a localisation process. The complexity and diversity of current and future wireless detector network operations drive this. Several single schemes have been proposed and studied for position estimation, each with advantages and limitations. Nonetheless, current methods for evaluating the performance of wireless detector networks are heavily focused on a single private or objective evaluation. Accurate position information in a wireless detector network is critical for colourful arising operations (WSN). It is critical to reducing the goods of noisy distance measures to improve localisation accuracy. Existing works (RSSI) are detailed and critically evaluated, with a higher error rate using a set of scenario requirements. Our proposed method (AEMM) is critical for detecting and dealing with outliers in wireless sensor networks to achieve a low localisation error rate. The proposed method (AEMM) for localisation and positioning nodes in wireless sensor networks supported by IOT and discovering the appropriate position of several nodes addresses all of the issues in WSN