Wireless Body Sensor Networks

2016 ◽  
Vol 5 (2) ◽  
pp. 1-30 ◽  
Author(s):  
Wassim Itani ◽  
Ayman Kayssi ◽  
Ali Chehab
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Design Patterns ◽  
Careful Analysis ◽  
The Body ◽  
Security And Privacy ◽  
Body Sensor Networks ◽  
Main Body ◽  
Body Sensor Network ◽  
Technical Discussion

In this paper, the authors provide a detailed overview and technical discussion and analysis of the latest research trends in securing body sensor networks. The core of this work aims at: (1) identifying the resource limitations and energy challenges of this category of wireless sensor networks, (2) considering the life-critical applications and emergency contexts that are encompassed by body sensor network services, and (3) studying the effect of these peculiarities on the design and implementation of rigorous and efficient security algorithms and protocols. The survey discusses the main advancements in the design of body sensor network cryptographic services (key generation and management, authentication, confidentiality, integrity, and privacy) and sheds the light on the prominent developments achieved in the field of securing body sensor network data in Cloud computing architectures. The elastic virtualization mechanisms employed in the Cloud, as well as the lucrative computing and storage resources available, makes the integration of body sensor network applications, and Cloud platforms a natural choice that is packed with various security and privacy challenges. The work presented in this paper focuses on Cloud privacy and integrity mechanisms that rely on tamper-proof hardware and energy-efficient cryptographic data structures that are proving to be well-suited for operation in untrusted Cloud environments. This paper also examines two crucial design patterns that lie at the crux of any successful body sensor network deployment which are represented in: (1) attaining the right balance between the degree, complexity, span, and strength of the cryptographic operations employed and the energy resources they consume. (2) Achieving a feasible tradeoff between the privacy of the human subject wearing the body sensor network and the safety of this subject. This is done by a careful analysis of the medical status of the subject and other context-related information to control the degree of disclosure of sensitive medical data. The paper concludes by presenting a practical overview of the cryptographic support in the main body sensor network development frameworks such and TinyOS and SPINE and introduces a set of generalized guideline patterns and recommendations for designing and implementing cryptographic protocols in body sensor network environments.

Wireless Body Sensor Networks

2019 ◽  
pp. 731-763
Author(s):  
Wassim Itani ◽  
Ayman Kayssi ◽  
Ali Chehab
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Design Patterns ◽  
Careful Analysis ◽  
Body Sensor Networks ◽  
Main Body ◽  
Body Sensor Network ◽  
Related Information ◽  
Technical Discussion ◽  
The Right

In this paper, the authors provide a detailed overview and technical discussion and analysis of the latest research trends in securing body sensor networks. The core of this work aims at: (1) identifying the resource limitations and energy challenges of this category of wireless sensor networks, (2) considering the life-critical applications and emergency contexts that are encompassed by body sensor network services, and (3) studying the effect of these peculiarities on the design and implementation of rigorous and efficient security algorithms and protocols. The survey discusses the main advancements in the design of body sensor network cryptographic services (key generation and management, authentication, confidentiality, integrity, and privacy) and sheds the light on the prominent developments achieved in the field of securing body sensor network data in Cloud computing architectures. The elastic virtualization mechanisms employed in the Cloud, as well as the lucrative computing and storage resources available, makes the integration of body sensor network applications, and Cloud platforms a natural choice that is packed with various security and privacy challenges. The work presented in this paper focuses on Cloud privacy and integrity mechanisms that rely on tamper-proof hardware and energy-efficient cryptographic data structures that are proving to be well-suited for operation in untrusted Cloud environments. This paper also examines two crucial design patterns that lie at the crux of any successful body sensor network deployment which are represented in: (1) attaining the right balance between the degree, complexity, span, and strength of the cryptographic operations employed and the energy resources they consume. (2) Achieving a feasible tradeoff between the privacy of the human subject wearing the body sensor network and the safety of this subject. This is done by a careful analysis of the medical status of the subject and other context-related information to control the degree of disclosure of sensitive medical data. The paper concludes by presenting a practical overview of the cryptographic support in the main body sensor network development frameworks such and TinyOS and SPINE and introduces a set of generalized guideline patterns and recommendations for designing and implementing cryptographic protocols in body sensor network environments.

scholarly journals Developing a Powerful and Resilient Smart Body Sensor Network through Hypercube Interconnection

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Ahmad S. Almogren
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Intelligent Systems ◽  
Intelligent Design ◽  
State Of The Art ◽  
The Body ◽  
Sensor Nodes ◽  
Body Sensor Networks ◽  
Embedded Computing ◽  
Body Sensor Network

With recent advances in wireless sensor networks and embedded computing technologies, body sensor networks (BSNs) have become practically feasible. BSNs consist of a number of sensor nodes located and deployed over the human body. These sensors continuously gather vital sign data of the body area to be used in various intelligent systems in smart environments. This paper presents an intelligent design of the body sensor network based on virtual hypercube structure backbone termed as Smart BodyNet. The main purpose of the Smart BodyNet is to provide resilience for the BSN operation and reduce power consumption. Various experiments were carried out to show the performance of the Smart BodyNet design as compared to the state-of-the-art approaches.

Security and Privacy in Body Sensor Networks

2013 ◽  
pp. 100-127
Author(s):  
Wassim Itani ◽  
Ayman Kayssi ◽  
Ali Chehab
Keyword(s):  
Sensor Networks ◽  
Network Security ◽  
Sensor Network ◽  
Security And Privacy ◽  
Body Sensor Networks ◽  
Security Framework ◽  
Body Sensor Network ◽  
Related Information ◽  
Sensor Network Security ◽  
Security Operations

In this chapter, we present a comprehensive survey of the state of the art research in the field of body sensor networks security and privacy. We identify the main security challenges introduced by body sensor networks by thoroughly analyzing the specifics of this category of wireless sensor networks and present the prominent security and privacy architectures available to protect body sensor infrastructures. The presented protocols are categorized based on the security services they provide. Moreover, the chapter studies two main challenges that we believe are the most critical in the body sensor network security and privacy context: (1) achieving the correct balance between the complexity of the protocol security operations employed and the energy consumption they incur, and (2) attaining the right tradeoff between privacy and safety by utilizing the patient’s vital signals and other context-related information to minimize the amount of private data released. To provide a practical insight into the presented concepts, this chapter presents an overview of the main cryptographic APIs available in popular sensor networks operating systems such as TinyOS and recommends a collection of best practices and usage patterns for developing secure sensor health care applications and services. We conclude by presenting a blueprint body sensor network security framework employing a secure combination of the technical building blocks described in the chapter sections. Recommendations on the advantages and drawbacks of each building block are suggested whenever the latter is added to the security framework.

scholarly journals Interference Aware Priority Based Packet Forwarding in Wireless Sensor Network using Bluetooth

2019 ◽  
Vol 8 (3S2) ◽  
pp. 177-180
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
The Body ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Body Sensor Networks ◽  
Body Parts ◽  
Packet Forwarding

Wireless Sensor Networks consists of several nodes that are distributed over a particular area. These sensor nodes are able to sense the changes in environmental parameters like temperature and carbon monoxide. Depending upon the ability each sensor node possess the type of wireless sensor networks may vary: that is either Homogeneous or Heterogeneous. This particular paper is concentrated on a homogeneous network. In this paper, an Interference Aware Priority based Packet Forwarding in Wireless Sensor Network using Bluetooth (IAPFB) scheme is proposed which helps in the congestion control in Wireless Sensor Network. The main idea behind this paper is that ; avoid the interference and collision between the nodes in the network while transmitting the data packets and also the higher priority data must forwarded first than a low priority one. The main application of this concept is the Body Sensor Networks. That is the body sensors for grabbing the signals from various body parts is used as the operating network. Signals from different body parts may have different priority levels and the proposed scheme can easily deal with the priorities. Simulated results shows comparatively good results for the proposed method.

System Design and Data Fusion in Body Sensor Networks

2012 ◽  
pp. 1-25 ◽  
Author(s):  
Kai Lin ◽  
Min Chen ◽  
Joel J. P. C. Rodrigues ◽  
Hongwei Ge
Keyword(s):  
Sensor Networks ◽  
Data Fusion ◽  
System Design ◽  
Sensor Network ◽  
Evaluation Method ◽  
Data Evaluation ◽  
Body Sensor Networks ◽  
Sensory Data ◽  
Redundant Data ◽  
Healthcare Monitoring

Body Sensor Networks (BSNs) are formed by the equipped or transplanted sensors in the human body, which can sense the physiology and environment parameters. As a novel e-health technology, BSNs promote the deployment of innovative healthcare monitoring applications. In the past few years, most of the related research works have focused on sensor design, signal processing, and communication protocol. This chapter addresses the problem of system design and data fusion technology over a bandwidth and energy constrained body sensor network. Compared with the traditional sensor network, miniaturization and low-power are more important to meet the requirements to facilitate wearing and long-running operation. As there are strong correlations between sensory data collected from different sensors, data fusion is employed to reduce the redundant data and the load in body sensor networks. To accomplish the complex task, more than one kind of node must be equipped or transplanted to monitor multi-targets, which makes the fusion process become sophisticated. In this chapter, a new BSNs system is designed to complete online diagnosis function. Based on the principle of data fusion in BSNs, we measure and investigate its performance in the efficiency of saving energy. Furthermore, the authors discuss the detection and rectification of errors in sensory data. Then a data evaluation method based on Bayesian estimation is proposed. Finally, the authors verify the performance of the designed system and the validity of the proposed data evaluation method. The chapter is concluded by identifying some open research issues on this topic.

Body Sensor Network for Ubiquitous Health Monitoring

2015 ◽  
Vol 03 (02) ◽  
pp. 163-169
Author(s):  
Lianying Ji ◽  
Tongbi Kang ◽  
Lingtong Tian ◽  
Meijun Xiong ◽  
Wendong Xiao ◽  
...  
Keyword(s):  
Sensor Network ◽  
Health Monitoring ◽  
The Body ◽  
Physiological Signals ◽  
Context Information ◽  
Network System ◽  
Team Members ◽  
Body Sensor Network ◽  
Elderly Health ◽  
Local Map

A body sensor network system has been developed for ubiquitous health monitoring of multiple mobile subjects, which is referred to as UbiHealth. On the body, there are micro-sensors to capture physiological signals of electrocardiography (ECG), blood pressure, respiration and temperature, as well as context information of activity and position. Sensors are coordinated by an on-body gateway, where data are collected, pre-processed and wirelessly sent to the server. The server receives, stores and processes signals from multiple gateways, providing overview of those subjects on a local map, and real-time health status of individual subjects. The application scenarios include, for example, health monitoring for rescue team members in a hazard, and elderly health monitoring in a community.

BSN-Based Activity Classification: A Low Complexity Windowing-&-Classification Approach

2012 ◽  
Vol 85 ◽  
pp. 53-58 ◽  
Author(s):  
Matteo Giuberti ◽  
Gianluigi Ferrari
Keyword(s):  
Sensor Networks ◽  
Low Complexity ◽  
The Body ◽  
Body Sensor Networks ◽  
Detection Accuracy ◽  
Activity Classification ◽  
First Case ◽  
Monitoring Applications ◽  
Healthcare Monitoring ◽  
The Time Domain

Wireless sensor networks (WSNs) are becoming more and more attractive because of their flexibility. In particular, WSNs are being applied to a user body in order to monitor and detect some activities of daily living (ADL) performed by the user (e.g., for medical purposes). This class of WSNs are typically denoted as body sensor networks (BSNs). In this paper, we discuss BSN-based human activity classification. In particular, the goal of our approach is to detect a sequence of activities, chosen from a limited set of fixed known activities, by observing the outputs generated by accelerometers and gyroscopes at the sensors placed over the body. In general, our framework is based on low-complexity windowing-&-classification. First, we consider the case of disjoint (in the time domain) activities; then, we extend our approach to encompass a scenario with consecutive non-disjoint activities. While in the first case windowing is separate from classification, in the second case windowing and classification need to be carried out jointly. The obtained results show a significant detection accuracy of the proposed method, making it suitable for healthcare monitoring applications.

Sign in / Sign up

Export Citation Format

Share Document