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Special Issue "Advances in Body Sensor Networks: Sensors, Systems, and Applications"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 31 March 2017

Special Issue Editors

Guest Editor
Prof. Dr. Giancarlo Fortino

DIMES - Department of Informatics, Modeling, Electronics, and Systems, University of Calabria, Via P. Bucci, cubo 41C, 87036 Rende (CS), Italy
Website | E-Mail
Interests: body area networks; internet of things; affective computing; cloud computing; agent-based computing
Co-Guest Editor
Dr. Hassan Ghasemzadeh

School of Electrical Engineering and Computer Science, Washington State University
Website | E-Mail
Interests: embedded systems; pervasive computing; smart health; cyber physical systems
Co-Guest Editor
Prof. Wenfeng Li

Department of Logistics Engineering, Wuhan University of Technology, China
Website | E-Mail
Interests: body area networks; internet of things; logistics
Co-Guest Editor
Dr. Yin Zhang

School of Information and Safety Engineering, Zhongnan University of Economics and Law, China
Website | E-Mail
Interests: body area networks; emotion-aware computing; multimedia systems
Co-Guest Editor
Prof. Luca Benini

Department of Electrical, Electronic, and Information Engineering, University of Bologna, Italy
Website | E-Mail
Interests: body sensor networks; networks-on-chip; ambient intelligence

Special Issue Information

Dear Colleagues,

A wireless body sensor network (or simply BSN) is a networked collection of wearable (programmable) sensor nodes that can communicate among themselves and also with other smart devices and other ambient sensors. The sensor nodes have computation, storage, wireless transmission, and sensing capabilities. Common physiological sensed signals/data include body motion, skin temperature, heart rate, skin conductivity, brain and muscle activities, and biomarkers. To perform both online and offline analyses of data streams, BSNs were recently assisted by cloud computing-based infrastructures providing flexible storage and scalable processing. A wide range of application scenarios is enabled by BSN technologies, even though m-Health applications probably represent the most emblematic and diffused example. Specifically, BSN-based systems can be used to directly monitor several vital signs continuously and non-invasively, as tiny wireless sensors are placed on the skin and sometimes integrated with the garments. Such signals can allow inferring the onset or progression of different diseases at an early stage or supporting rehabilitation. Moreover, BSNs are strategic enablers for many other application domains such as: e-Sport, e-Fitness, e-Wellness, and e-Social. However, many issues still exist in the BSN research area from several points of view: hardware (e.g., new biosensor boards), communications (e.g. more efficient MAC-level protocols), distributed software systems (e.g., collaborative smartphone- and/or BSN-based platforms), and novel applications including advanced data processing algorithms.

In this Special Issue we aim at dealing with the aforementioned issues and, in particular, we are mainly interested in the following topics:

  • Novel biosensor architectures
  • Energy-efficient protocols for body sensor networks
  • Frameworks for context-aware body sensor networks
  • Cloud-assisted body sensor networks
  • Virtualization of wearable devices and systems
  • Information fusion algorithms for body sensor networks data
  • Body sensor networks for emotion-aware computing and systems
  • Activity recognition based on body sensor networks
  • Interconnection, integration, interoperability issues
  • Smart body area networks and Internet of Things
  • Applications for BSNs in strategic domains (e.g. healthcare, sport/fitness, logistics, manufacturing, emergency response, military, etc.)

Prof. Giancarlo Fortino
Guest Editor

Dr. Hassan Gasemzadeh
Prof. Wenfeng Li
Dr. Yin Zhang
Prof. Luca Benini
Co-Guest Editors

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs).

Keywords

  • Body Area Networks
  • Multi-sensor Fusion Algorithms
  • Distributed Architectures
  • Emotion-Aware Wearable Systems
  • Bio-Sensors

Published Papers (12 papers)

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Research

Open AccessArticle A Wellness Mobile Application for Smart Health: Pilot Study Design and Results
Sensors 2017, 17(3), 611; doi:10.3390/s17030611
Received: 15 February 2017 / Revised: 13 March 2017 / Accepted: 15 March 2017 / Published: 17 March 2017
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Abstract
Wellness is one of the main factors crucial in the avoidance of illness or disease. Experience has shown that healthy lifestyle programs are an important strategy to prevent the major shared risk factors for many diseases including cardiovascular diseases, strokes, diabetes, obesity, and
[...] Read more.
Wellness is one of the main factors crucial in the avoidance of illness or disease. Experience has shown that healthy lifestyle programs are an important strategy to prevent the major shared risk factors for many diseases including cardiovascular diseases, strokes, diabetes, obesity, and hypertension. Within the ambit of the Smart Health 2.0 project, a Wellness App has been developed which has the aim of providing people with something similar to a personal trainer. This Wellness App is able to gather information about the subject, to classify her/him by evaluating some of her/his specific characteristics (physical parameters and lifestyle) and to make personal recommendations to enhance her/his well-being. The application can also give feedback on the effectiveness of the specified characteristics by monitoring their evolution over time, and can provide a positive incentive to stimulate the subject to achieve her/his wellness goals. In this paper, we present a pilot study conducted in Calabria, a region of Italy, aimed at an evaluation of the validity, usability, and navigability of the app, and of people’s level of satisfaction with it. The preliminary results show an average score of 77.16 for usability and of 76.87 for navigability, with an improvement of the Wellness Index with a significance average of 95% and of the Mediterranean Adequacy Index with a significance average of as high as 99%. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle Performance Analysis of Different Backoff Algorithms for WBAN-Based Emerging Sensor Networks
Sensors 2017, 17(3), 492; doi:10.3390/s17030492
Received: 15 November 2016 / Revised: 20 February 2017 / Accepted: 24 February 2017 / Published: 2 March 2017
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Abstract
The Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) procedure of IEEE 802.15.6 Medium Access Control (MAC) protocols for the Wireless Body Area Network (WBAN) use an Alternative Binary Exponential Backoff (ABEB) procedure. The backoff algorithm plays an important role to avoid collision
[...] Read more.
The Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) procedure of IEEE 802.15.6 Medium Access Control (MAC) protocols for the Wireless Body Area Network (WBAN) use an Alternative Binary Exponential Backoff (ABEB) procedure. The backoff algorithm plays an important role to avoid collision in wireless networks. The Binary Exponential Backoff (BEB) algorithm used in different standards does not obtain the optimum performance due to enormous Contention Window (CW) gaps induced from packet collisions. Therefore, The IEEE 802.15.6 CSMA/CA has developed the ABEB procedure to avoid the large CW gaps upon each collision. However, the ABEB algorithm may lead to a high collision rate (as the CW size is incremented on every alternative collision) and poor utilization of the channel due to the gap between the subsequent CW. To minimize the gap between subsequent CW sizes, we adopted the Prioritized Fibonacci Backoff (PFB) procedure. This procedure leads to a smooth and gradual increase in the CW size, after each collision, which eventually decreases the waiting time, and the contending node can access the channel promptly with little delay; while ABEB leads to irregular and fluctuated CW values, which eventually increase collision and waiting time before a re-transmission attempt. We analytically approach this problem by employing a Markov chain to design the PFB scheme for the CSMA/CA procedure of the IEEE 80.15.6 standard. The performance of the PFB algorithm is compared against the ABEB function of WBAN CSMA/CA. The results show that the PFB procedure adopted for IEEE 802.15.6 CSMA/CA outperforms the ABEB procedure. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle A Doppler Radar System for Sensing Physiological Parameters in Walking and Standing Positions
Sensors 2017, 17(3), 485; doi:10.3390/s17030485
Received: 30 January 2017 / Revised: 21 February 2017 / Accepted: 24 February 2017 / Published: 1 March 2017
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Abstract
Doppler radar can be implemented for sensing physiological parameters wirelessly at a distance. Detecting respiration rate, an important human body parameter, is essential in a range of applications like emergency and military healthcare environments, and Doppler radar records actual chest motion. One challenge
[...] Read more.
Doppler radar can be implemented for sensing physiological parameters wirelessly at a distance. Detecting respiration rate, an important human body parameter, is essential in a range of applications like emergency and military healthcare environments, and Doppler radar records actual chest motion. One challenge in using Doppler radar is being able to monitor several patients simultaneously and in different situations like standing, walking, or lying. This paper presents a complete transmitter-receiver Doppler radar system, which uses a 4 GHz continuous wave radar signal transmission and receiving system, to extract base-band data from a phase-shifted signal. This work reports experimental evaluations of the system for one and two subjects in various standing and walking positions. It provides a detailed signal analysis of various breathing rates of these two subjects simultaneously. These results will be useful in future medical monitoring applications. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle A Fast Channel Assignment Scheme for Emergency Handling in Wireless Body Area Networks
Sensors 2017, 17(3), 477; doi:10.3390/s17030477
Received: 2 December 2016 / Revised: 21 February 2017 / Accepted: 24 February 2017 / Published: 27 February 2017
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Abstract
Ubiquitous healthcare is a promising technology that has attracted significant attention in recent years; this has led to the realization of wireless body area networks (WBANs). For designing a robust WBAN system, the WBAN has to solve the drawbacks of wireless technology. Also,
[...] Read more.
Ubiquitous healthcare is a promising technology that has attracted significant attention in recent years; this has led to the realization of wireless body area networks (WBANs). For designing a robust WBAN system, the WBAN has to solve the drawbacks of wireless technology. Also, a WBAN has to support immediate, reliable data transmission for medical services during emergencies. Hence, this study proposes a new MAC superframe structure that can handle emergencies by delivering strongly correlated regular data to a caretaker, within a certain time threshold. Simulation results demonstrate that the proposed MAC protocol achieves low latency and high throughput. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle IEEE 802.15.4 Frame Aggregation Enhancement to Provide High Performance in Life-Critical Patient Monitoring Systems
Sensors 2017, 17(2), 241; doi:10.3390/s17020241
Received: 3 November 2016 / Revised: 18 January 2017 / Accepted: 23 January 2017 / Published: 28 January 2017
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Abstract
In wireless body area sensor networks (WBASNs), Quality of Service (QoS) provision for patient monitoring systems in terms of time-critical deadlines, high throughput and energy efficiency is a challenging task. The periodic data from these systems generates a large number of small packets
[...] Read more.
In wireless body area sensor networks (WBASNs), Quality of Service (QoS) provision for patient monitoring systems in terms of time-critical deadlines, high throughput and energy efficiency is a challenging task. The periodic data from these systems generates a large number of small packets in a short time period which needs an efficient channel access mechanism. The IEEE 802.15.4 standard is recommended for low power devices and widely used for many wireless sensor networks applications. It provides a hybrid channel access mechanism at the Media Access Control (MAC) layer which plays a key role in overall successful transmission in WBASNs. There are many WBASN’s MAC protocols that use this hybrid channel access mechanism in variety of sensor applications. However, these protocols are less efficient for patient monitoring systems where life critical data requires limited delay, high throughput and energy efficient communication simultaneously. To address these issues, this paper proposes a frame aggregation scheme by using the aggregated-MAC protocol data unit (A-MPDU) which works with the IEEE 802.15.4 MAC layer. To implement the scheme accurately, we develop a traffic patterns analysis mechanism to understand the requirements of the sensor nodes in patient monitoring systems, then model the channel access to find the performance gap on the basis of obtained requirements, finally propose the design based on the needs of patient monitoring systems. The mechanism is initially verified using numerical modelling and then simulation is conducted using NS2.29, Castalia 3.2 and OMNeT++. The proposed scheme provides the optimal performance considering the required QoS. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle Value-Based Caching in Information-Centric Wireless Body Area Networks
Sensors 2017, 17(1), 181; doi:10.3390/s17010181
Received: 14 November 2016 / Revised: 2 January 2017 / Accepted: 12 January 2017 / Published: 19 January 2017
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Abstract
We propose a resilient cache replacement approach based on a Value of sensed Information (VoI) policy. To resolve and fetch content when the origin is not available due to isolated in-network nodes (fragmentation) and harsh operational conditions, we exploit a content caching approach.
[...] Read more.
We propose a resilient cache replacement approach based on a Value of sensed Information (VoI) policy. To resolve and fetch content when the origin is not available due to isolated in-network nodes (fragmentation) and harsh operational conditions, we exploit a content caching approach. Our approach depends on four functional parameters in sensory Wireless Body Area Networks (WBANs). These four parameters are: age of data based on periodic request, popularity of on-demand requests, communication interference cost, and the duration for which the sensor node is required to operate in active mode to capture the sensed readings. These parameters are considered together to assign a value to the cached data to retain the most valuable information in the cache for prolonged time periods. The higher the value, the longer the duration for which the data will be retained in the cache. This caching strategy provides significant availability for most valuable and difficult to retrieve data in the WBANs. Extensive simulations are performed to compare the proposed scheme against other significant caching schemes in the literature while varying critical aspects in WBANs (e.g., data popularity, cache size, publisher load, connectivity-degree, and severe probabilities of node failures). These simulation results indicate that the proposed VoI-based approach is a valid tool for the retrieval of cached content in disruptive and challenging scenarios, such as the one experienced in WBANs, since it allows the retrieval of content for a long period even while experiencing severe in-network node failures. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle PlaIMoS: A Remote Mobile Healthcare Platform to Monitor Cardiovascular and Respiratory Variables
Sensors 2017, 17(1), 176; doi:10.3390/s17010176
Received: 5 December 2016 / Revised: 11 January 2017 / Accepted: 12 January 2017 / Published: 19 January 2017
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Abstract
The number of elderly and chronically ill patients has grown significantly over the past few decades as life expectancy has increased worldwide, leading to increased demands on the health care system and significantly taxing traditional health care practices. Consequently, there is an urgent
[...] Read more.
The number of elderly and chronically ill patients has grown significantly over the past few decades as life expectancy has increased worldwide, leading to increased demands on the health care system and significantly taxing traditional health care practices. Consequently, there is an urgent need to use technology to innovate and more constantly and intensely monitor, report and analyze critical patient physiological parameters beyond conventional clinical settings in a more efficient and cost effective manner. This paper presents a technological platform called PlaIMoS which consists of wearable sensors, a fixed measurement station, a network infrastructure that employs IEEE 802.15.4 and IEEE 802.11 to transmit data with security mechanisms, a server to analyze all information collected and apps for iOS, Android and Windows 10 mobile operating systems to provide real-time measurements. The developed architecture, designed primarily to record and report electrocardiogram and heart rate data, also monitors parameters associated with chronic respiratory illnesses, including patient blood oxygen saturation and respiration rate, body temperature, fall detection and galvanic resistance. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle On Connectivity of Wireless Sensor Networks with Directional Antennas
Sensors 2017, 17(1), 134; doi:10.3390/s17010134
Received: 6 November 2016 / Revised: 28 December 2016 / Accepted: 5 January 2017 / Published: 12 January 2017
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Abstract
In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their
[...] Read more.
In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle An Approach to Biometric Verification Based on Human Body Communication in Wearable Devices
Sensors 2017, 17(1), 125; doi:10.3390/s17010125
Received: 13 October 2016 / Revised: 2 January 2017 / Accepted: 4 January 2017 / Published: 10 January 2017
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Abstract
In this paper, an approach to biometric verification based on human body communication (HBC) is presented for wearable devices. For this purpose, the transmission gain S21 of volunteer’s forearm is measured by vector network analyzer (VNA). Specifically, in order to determine the chosen
[...] Read more.
In this paper, an approach to biometric verification based on human body communication (HBC) is presented for wearable devices. For this purpose, the transmission gain S21 of volunteer’s forearm is measured by vector network analyzer (VNA). Specifically, in order to determine the chosen frequency for biometric verification, 1800 groups of data are acquired from 10 volunteers in the frequency range 0.3 MHz to 1500 MHz, and each group includes 1601 sample data. In addition, to achieve the rapid verification, 30 groups of data for each volunteer are acquired at the chosen frequency, and each group contains only 21 sample data. Furthermore, a threshold-adaptive template matching (TATM) algorithm based on weighted Euclidean distance is proposed for rapid verification in this work. The results indicate that the chosen frequency for biometric verification is from 650 MHz to 750 MHz. The false acceptance rate (FAR) and false rejection rate (FRR) based on TATM are approximately 5.79% and 6.74%, respectively. In contrast, the FAR and FRR were 4.17% and 37.5%, 3.37% and 33.33%, and 3.80% and 34.17% using K-nearest neighbor (KNN) classification, support vector machines (SVM), and naive Bayesian method (NBM) classification, respectively. In addition, the running time of TATM is 0.019 s, whereas the running times of KNN, SVM and NBM are 0.310 s, 0.0385 s, and 0.168 s, respectively. Therefore, TATM is suggested to be appropriate for rapid verification use in wearable devices. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle Fuzzy Computing Model of Activity Recognition on WSN Movement Data for Ubiquitous Healthcare Measurement
Sensors 2016, 16(12), 2053; doi:10.3390/s16122053
Received: 4 October 2016 / Revised: 22 November 2016 / Accepted: 23 November 2016 / Published: 3 December 2016
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Abstract
Ubiquitous health care (UHC) is beneficial for patients to ensure they complete therapeutic exercises by self-management at home. We designed a fuzzy computing model that enables recognizing assigned movements in UHC with privacy. The movements are measured by the self-developed body motion sensor,
[...] Read more.
Ubiquitous health care (UHC) is beneficial for patients to ensure they complete therapeutic exercises by self-management at home. We designed a fuzzy computing model that enables recognizing assigned movements in UHC with privacy. The movements are measured by the self-developed body motion sensor, which combines both accelerometer and gyroscope chips to make an inertial sensing node compliant with a wireless sensor network (WSN). The fuzzy logic process was studied to calculate the sensor signals that would entail necessary features of static postures and dynamic motions. Combinations of the features were studied and the proper feature sets were chosen with compatible fuzzy rules. Then, a fuzzy inference system (FIS) can be generated to recognize the assigned movements based on the rules. We thus implemented both fuzzy and adaptive neuro-fuzzy inference systems in the model to distinguish static and dynamic movements. The proposed model can effectively reach the recognition scope of the assigned activity. Furthermore, two exercises of upper-limb flexion in physical therapy were applied for the model in which the recognition rate can stand for the passing rate of the assigned motions. Finally, a web-based interface was developed to help remotely measure movement in physical therapy for UHC. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle Potential of Wake-Up Radio-Based MAC Protocols for Implantable Body Sensor Networks (IBSN)—A Survey
Sensors 2016, 16(12), 2012; doi:10.3390/s16122012
Received: 19 October 2016 / Revised: 18 November 2016 / Accepted: 21 November 2016 / Published: 29 November 2016
PDF Full-text (673 KB) | HTML Full-text | XML Full-text
Abstract
With the advent of nano-technology, medical sensors and devices are becoming highly miniaturized. Consequently, the number of sensors and medical devices being implanted to accurately monitor and diagnose a disease is increasing. By measuring the symptoms and controlling a medical device as close
[...] Read more.
With the advent of nano-technology, medical sensors and devices are becoming highly miniaturized. Consequently, the number of sensors and medical devices being implanted to accurately monitor and diagnose a disease is increasing. By measuring the symptoms and controlling a medical device as close as possible to the source, these implantable devices are able to save lives. A wireless link between medical sensors and implantable medical devices is essential in the case of closed-loop medical devices, in which symptoms of the diseases are monitored by sensors that are not placed in close proximity of the therapeutic device. Medium Access Control (MAC) is crucial to make it possible for several medical devices to communicate using a shared wireless medium in such a way that minimum delay, maximum throughput, and increased network life-time are guaranteed. To guarantee this Quality of Service (QoS), the MAC protocols control the main sources of limited resource wastage, namely the idle-listening, packet collisions, over-hearing, and packet loss. Traditional MAC protocols designed for body sensor networks are not directly applicable to Implantable Body Sensor Networks (IBSN) because of the dynamic nature of the radio channel within the human body and the strict QoS requirements of IBSN applications. Although numerous MAC protocols are available in the literature, the majority of them are designed for Body Sensor Network (BSN) and Wireless Sensor Network (WSN). To the best of our knowledge, there is so far no research paper that explores the impact of these MAC protocols specifically for IBSN. MAC protocols designed for implantable devices are still in their infancy and one of their most challenging objectives is to be ultra-low-power. One of the technological solutions to achieve this objective so is to integrate the concept of Wake-up radio (WuR) into the MAC design. In this survey, we present a taxonomy of MAC protocols based on their use of WuR technology and identify their bottlenecks to be used in IBSN applications. Furthermore, we present a number of open research challenges and requirements for designing an energy-efficient and reliable wireless communication protocol for IBSN. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle Analysis of Aggregation Delay for Multisource Sensor Data with On-Off Traffic Pattern in Wireless Body Area Networks
Sensors 2016, 16(10), 1622; doi:10.3390/s16101622
Received: 1 July 2016 / Revised: 21 September 2016 / Accepted: 26 September 2016 / Published: 30 September 2016
PDF Full-text (2351 KB) | HTML Full-text | XML Full-text
Abstract
Data aggregation plays an important role to improve the transmission efficiency in wireless body area networks (WBANs); however, it inherently induces additional aggregation delay. Therefore, the effect of packet aggregation on WBAN applications, which are vulnerable to delay, must be analyzed rigorously. In
[...] Read more.
Data aggregation plays an important role to improve the transmission efficiency in wireless body area networks (WBANs); however, it inherently induces additional aggregation delay. Therefore, the effect of packet aggregation on WBAN applications, which are vulnerable to delay, must be analyzed rigorously. In this paper, we analyze the packet aggregation delay for multisource sensor data with an on-off traffic pattern in WBANs. Considering two operational parameters of the aggregation threshold and aggregation timer, we calculate the probability that a packet aggregation occurs during a unit time and then derive the average aggregation delay in closed-form. The analysis results show that the aggregation delay increases as the aggregation timer or aggregation threshold increases, but is bounded below a certain level according to the number of active sensors and their on-off traffic attribute. This implies that the data aggregation technique can maximize the transmission efficiency while satisfying a given delay requirement in the WBAN system. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Secure Device Pairing Protocol based on Wireless Channel Characteristics for Body Area Networks
Author: Chitra Javali (chitra.javali@unsw.edu.au)
Abstract: The increased usage of wireless body area networks (WBANs) in healthcare applications underscores the importance of secure communication among the body sensor devices. Associating a device with an existing network poses a major challenge. We present SeAK, a secure light-weight device pairing protocol for WBAN based on received signal strength (RSS) obtained by dual-antenna transceivers utilizing spatial diversity. Our extensive experimental results demonstrate that SeAK - securely authenticates a nearby device and generates a 128-bit secret key in 640 msec, and achieves 100% key agreement, an entropy of ~ 0.98 - 0.99 bits, and mutual information of 0.9896 - 0.9982 bits between the legitimate devices.

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