An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks

A high degree of reliability for critical data transmission is required in body sensor networks (BSNs). However, BSNs are usually vulnerable to channel impairments due to body fading effect and RF interference, which may potentially cause data transmission to be unreliable. In this paper, an adaptive and flexible fault-tolerant communication scheme for BSNs, namely AFTCS, is proposed. AFTCS adopts a channel bandwidth reservation strategy to provide reliable data transmission when channel impairments occur. In order to fulfill the reliability requirements of critical sensors, fault-tolerant priority and queue are employed to adaptively adjust the channel bandwidth allocation. Simulation results show that AFTCS can alleviate the effect of channel impairments, while yielding lower packet loss rate and latency for critical sensors at runtime.Comment: 10 figures, 19 page

Performance Evaluation of Wearable Sensor Systems: A Case Study in Moderate-Scale Deployment in Hospital Environment

A wearable sensor system enables continuous and remote health monitoring and is widely considered as the next generation of healthcare technology. The performance, the packet error rate (PER) in particular, of a wearable sensor system may deteriorate due to a number of factors, particularly the interference from the other wearable sensor systems in the vicinity. We systematically evaluate the performance of the wearable sensor system in terms of PER in the presence of such interference in this paper. The factors that affect the performance of the wearable sensor system, such as density, traffic load, and transmission power in a realistic moderate-scale deployment case in hospital are all considered. Simulation results show that with 20% duty cycle, only 68.5% of data transmission can achieve the targeted reliability requirement (PER is less than 0.05) even in the off-peak period in hospital. We then suggest some interference mitigation schemes based on the performance evaluation results in the case study

BodyCloud: a SaaS approach for community body sensor networks

Body Sensor Networks (BSNs) have been recently introduced for the remote monitoring of human activities in a broad range of application domains, such as health care, emergency management, fitness and behaviour surveillance. BSNs can be deployed in a community of people and can generate large amounts of contextual data that require a scalable approach for storage, processing and analysis. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of data streams generated in BSNs. This paper proposes BodyCloud, a SaaS approach for community BSNs that supports the development and deployment of Cloud-assisted BSN applications. BodyCloud is a multi-tier application-level architecture that integrates a Cloud computing platform and BSN data streams middleware. BodyCloud provides programming abstractions that allow the rapid development of community BSN applications. This work describes the general architecture of the proposed approach and presents a case study for the real-time monitoring and analysis of cardiac data streams of many individuals

Web-based sensor streaming wearable for respiratory monitoring applications.

This paper presents a system for remote monitoring of respiration of individuals that can detect respiration rate, mode of breathing and identify coughing events. It comprises a series of polymer fabric-sensors incorporated into a sports vest, a wearable data acquisition platform and a novel rich internet application (RIA) which together enable remote real-time monitoring of untethered wearable systems for respiratory rehabilitation. This system will, for the first time, allow therapists to monitor and guide the respiratory efforts of patients in real-time through a web browser. Changes in abdomen expansion and contraction associated with respiration are detected by the fabric sensors and transmitted wirelessly via a Bluetooth-based solution to a standard computer. The respiratory signals are visualized locally through the RIA and subsequently published to a sensor streaming cloud-based server. A web-based signal streaming protocol makes the signals available as real-time streams to authorized subscribers over standard browsers. We demonstrate real-time streaming of a six-sensor shirt rendered remotely at 40 samples/s per sensor with perceptually acceptable latency (<0.5s) over realistic network conditions

Is the timed-up and go test feasible in mobile devices? A systematic review

The number of older adults is increasing worldwide, and it is expected that by 2050 over 2 billion individuals will be more than 60 years old. Older adults are exposed to numerous pathological problems such as Parkinson’s disease, amyotrophic lateral sclerosis, post-stroke, and orthopedic disturbances. Several physiotherapy methods that involve measurement of movements, such as the Timed-Up and Go test, can be done to support efficient and effective evaluation of pathological symptoms and promotion of health and well-being. In this systematic review, the authors aim to determine how the inertial sensors embedded in mobile devices are employed for the measurement of the different parameters involved in the Timed-Up and Go test. The main contribution of this paper consists of the identification of the different studies that utilize the sensors available in mobile devices for the measurement of the results of the Timed-Up and Go test. The results show that mobile devices embedded motion sensors can be used for these types of studies and the most commonly used sensors are the magnetometer, accelerometer, and gyroscope available in off-the-shelf smartphones. The features analyzed in this paper are categorized as quantitative, quantitative + statistic, dynamic balance, gait properties, state transitions, and raw statistics. These features utilize the accelerometer and gyroscope sensors and facilitate recognition of daily activities, accidents such as falling, some diseases, as well as the measurement of the subject's performance during the test execution.info:eu-repo/semantics/publishedVersio

Classification of sporting activities using smartphone accelerometers

In this paper we present a framework that allows for the automatic identification of sporting activities using commonly available smartphones. We extract discriminative informational features from smartphone accelerometers using the Discrete Wavelet Transform (DWT). Despite the poor quality of their accelerometers, smartphones were used as capture devices due to their prevalence in today’s society. Successful classification on this basis potentially makes the technology accessible to both elite and non-elite athletes. Extracted features are used to train different categories of classifiers. No one classifier family has a reportable direct advantage in activity classification problems to date; thus we examine classifiers from each of the most widely used classifier families. We investigate three classification approaches; a commonly used SVM-based approach, an optimized classification model and a fusion of classifiers. We also investigate the effect of changing several of the DWT input parameters, including mother wavelets, window lengths and DWT decomposition levels. During the course of this work we created a challenging sports activity analysis dataset, comprised of soccer and field-hockey activities. The average maximum F-measure accuracy of 87% was achieved using a fusion of classifiers, which was 6% better than a single classifier model and 23% better than a standard SVM approach

Low power body sensor network design based on relaying of creeping waves in the unlicensed 2.4GHz band

Body Sensor Networks are an important enabling technology for future applications in remote medical diagnostics. Practical deployments of these systems have only recently edged closer to viability, due in part to advances in low power electronics and System-On-Chip devices. Wireless communication between these sensors remains a daunting challenge, and designers typically leverage existing industrial standards designed for applications with significantly different communications requirements. This Thesis proposes a wireless communications platform designed specifically for body mounted sensors, exploiting a phenomenon in electromagnetic wave propagation known as a creeping wave. Relaying of these waves leads to a highly reliable body sensor network with very low power consumption in the unlicensed 2.4 GHz band. A link budget is derived based on the creeping wave component of the transmitted signal, which is then used to design a spread spectrum wireless transceiver. Significant attention is given to interference mitigation, allowing the system to co-exist with other wireless devices on the internationally unlicensed band. Fading statistics from both anechoic and high multipath scenarios are used to define a channel model for the system. The link budget and channel model lead to the proposed use of relaying as a power savings technique, and this concept is a core feature of the design. This technique is shown to provide reliable total body coverage with very low transmission power, a result that has eluded body sensor networks to date. Various relaying topologies are discussed, and robust operation for highly mobile users is achieved via sensor handoffs, a concept that resembles a similar solution in cellular networks. The design extends to define a polling protocol and packet structures. Objective performance metrics are defined, and the proposed system is evaluated in line with these metrics. The power reduction of the suggested approach is analyzed by comparing the network lifetime and energy-per-bit to those of a reference system offering the same quality of service without relaying. The analysis results in generic closed form expressions of significant gains. The improvement in network lifetime increases with the number of sensors and settles at approximately 8x104, 7x106, 7x107 and 3x108 for 2,4,6 and 8 relaying nodes respectively. The energy-per-bit is shown to decrease by 2, 116, 828 and 2567 for 2, 4, 6 and 8 relay nodes respectively

Experimental investigation into novel methods of reliable and secure on-body communications with low system overheads

Until recently the concept of wearable biosensors for purposes of medical monitoring was restricted to wired sensor applications. Recent advances in electronics and wireless communications have made the possibility of removing the wire from sensor applications a possibility. These advances have led to the development of small scale, wearable, sensing and communication platforms that can be placed on the human body creating the foundation for a Body Sensor Network (BSN). Body Sensor Networks aim to remove the restrictions that traditional wired sensors impose. The anticipation is that BSNs will permit the monitoring of physiological signals in any environment without limitation, giving Physicians the ability to monitor patients more closely and in environments that they cannot monitor today. Even with the recent advancements of electronics and wireless communications there are still many unanswered questions for practical solutions of BSNs that prevent BSNs from replacing traditional wired systems altogether. There is a great need for research into BSN architectures to set the standard for wireless sensor monitoring. In this work a development platform has been created for the investigation into the design and implementation of practical BSN solutions. The platform is used to compare BSN architectures and provide quantifiable results. From this work BSN architecture components that provide optimizations in system performance, energy, network lifetime and security are recommended. In Chapter 3 BSN network architectures employing the use of relaying of creeping waves is investigated. The investigation includes experimental analysis of various test environments. Experimentation demonstrates that the relaying of creeping waves offers considerable performance gains when compared to non-relay networks. For example, relaying is shown to increase network-lifetime by a factor of 13, decrease energy-per-bit requirements by 13 dB and provide the ability for the network to compensate for considerably wider fade margins. In Chapter 4 utilizing the randomness of the wireless channel for securing on-body communications with low overheads is considered. A low-complexity algorithm for establishing symmetric encryption keys is presented and validated. The algorithm relies on readily available RSSI measurements obtained from existing packets being sent and received in the network. The generated bit sequences from the algorithm are evaluated for matching between two communicating parties and mismatching with a malicious eavesdropper. It is shown that the algorithm produces long sequences of highly random bits that are perfectly matched between legitimate parties and highly mismatched with the eavesdropper

SPINE: A domain-specific framework for rapid prototyping of WBSN applications

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