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Wireless Body Area Sensor Networks
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Wireless Body Area Sensor Networks

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

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 9653

Special Issue Editors

Prof. Dr. Joarder Kamruzzaman

E-Mail Website
Guest Editor
Centre for Smart Analytics, Federation University Australia, Ballarat, VIC 3842, Australia
Interests: Internet of Things; machine learning; data analytics; cybersecurity
Special Issues, Collections and Topics in MDPI journals
Dr. Venki Balasubramanian

E-Mail Website
Guest Editor
Federation University Australia, Victoria, Australia
Interests: Wireless sensor networks; eHealth; cloud computing; network simulations

Special Issue Information

Dear Colleagues,

Recent advances in wireless communications and sensor technologies have accelerated the rapid development of Wireless Body Area Networks (WBAN) devices. The advent of advanced medical sensors that are capable to monitor the physiological data of the patient and can transmit to the Cloud using fast wireless and mobile communications for processing, analysing and raising alerts to the clinicians is becoming a reality. WBAN is the key component in the Internet of Medical Things (IoMT), and has applications in other domains, apart from healthcare, which include military, sport and fitness, entertainment and education.

Despite recent advancements, the successful deployment of civilian and commercial use is still in its infancy. Some of the challenges include smart bio sensor development, medical certification, energy efficiency, in-body and off-body communication protocols, data processing, Quality of Service (QoS) of WBAN applications under constrained resources, and security and privacy of healthcare data communication and storage.

This Special Issue is dedicated to addressing the issues, but is not limited to the above, related to wireless body area networks.

Prof. Dr. Joarder Kamruzzaman
Dr. Venki Balasubramanian
Guest Editors

Manuscript Submission Information

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. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short 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 thoroughly refereed through a single-blind 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 semimonthly 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 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Biosensors
  • Sensor implant
  • Sensor energy harvesting
  • WBAN communication protocol
  • WBAN applications
  • QoS in WBAN
  • Security and privacy
  • Blockchain
  • Sensor storage

Published Papers (3 papers)

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Research

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21 pages, 4477 KiB  
Article
Wireless Body Area Network Control Policies for Energy-Efficient Health Monitoring
by Yair Bar David, Tal Geller, Ilai Bistritz, Irad Ben-Gal, Nicholas Bambos and Evgeni Khmelnitsky
Sensors 2021, 21(12), 4245; https://doi.org/10.3390/s21124245 - 21 Jun 2021
Cited by 3 | Viewed by 2142
Abstract
Wireless body area networks (WBANs) have strong potential in the field of health monitoring. However, the energy consumption required for accurate monitoring determines the time between battery charges of the wearable sensors, which is a key performance factor (and can be critical in [...] Read more.
Wireless body area networks (WBANs) have strong potential in the field of health monitoring. However, the energy consumption required for accurate monitoring determines the time between battery charges of the wearable sensors, which is a key performance factor (and can be critical in the case of implantable devices). In this paper, we study the inherent trade-off between the power consumption of the sensors and the probability of misclassifying a patient’s health state. We formulate this trade-off as a dynamic problem, in which at each step, we can choose to activate a subset of sensors that provide noisy measurements of the patient’s health state. We assume that the (unknown) health state follows a Markov chain, so our problem is formulated as a partially observable Markov decision problem (POMDP). We show that all the past measurements can be summarized as a belief state on the true health state of the patient, which allows tackling the POMDP problem as an MDP on the belief state. Then, we empirically study the performance of a greedy one-step look-ahead policy compared to the optimal policy obtained by solving the dynamic program. For that purpose, we use an open-source Continuous Glucose Monitoring (CGM) dataset of 232 patients over six months and extract the transition matrix and sensor accuracies from the data. We find that the greedy policy saves ≈50% of the energy costs while reducing the misclassification costs by less than 2% compared to the most accurate policy possible that always activates all sensors. Our sensitivity analysis reveals that the greedy policy remains nearly optimal across different cost parameters and a varying number of sensors. The results also have practical importance, because while the optimal policy is too complicated, a greedy one-step look-ahead policy can be easily implemented in WBAN systems. Full article
(This article belongs to the Special Issue Wireless Body Area Sensor Networks)
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19 pages, 7999 KiB  
Article
Channel Modeling of an Optical Wireless Body Sensor Network for Walk Monitoring of Elderly
by Alassane Kaba, Stephanie Sahuguede and Anne Julien-Vergonjanne
Sensors 2021, 21(9), 2904; https://doi.org/10.3390/s21092904 - 21 Apr 2021
Cited by 6 | Viewed by 1917
Abstract
The growing aging of the world population is leading to an aggravation of diseases, which affect the autonomy of the elderly. Wireless body sensor networks (WBSN) are part of the solutions studied for several years to monitor and prevent loss of autonomy. The [...] Read more.
The growing aging of the world population is leading to an aggravation of diseases, which affect the autonomy of the elderly. Wireless body sensor networks (WBSN) are part of the solutions studied for several years to monitor and prevent loss of autonomy. The use of optical wireless communications (OWC) is seen as an alternative to radio frequencies, relevant when electromagnetic interference and data security considerations are important. One of the main challenges in this context is optical channel modeling for efficiently designing high-reliability systems. We propose here a suitable optical WBSN channel model for tracking the elderly during a walk. We discuss the specificities related to the model of the body, to movements, and to the walking speed by comparing elderly and young models, taking into account the walk temporal evolution using the sliding windowing technique. We point out that, when considering a young body model, performance is either overestimated or underestimated, depending on which windowing parameter is fixed. It is, therefore, important to consider the body model of the elderly in the design of the system. To illustrate this result, we then evaluate the minimal power according to the maximal bandwidth for a given quality of service. Full article
(This article belongs to the Special Issue Wireless Body Area Sensor Networks)
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Review

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23 pages, 4327 KiB  
Review
State-of-the-Art Wearable Sensors and Possibilities for Radar in Fall Prevention
by José Gabriel Argañarás, Yan Tat Wong, Rezaul Begg and Nemai Chandra Karmakar
Sensors 2021, 21(20), 6836; https://doi.org/10.3390/s21206836 - 14 Oct 2021
Cited by 10 | Viewed by 4399
Abstract
Radar technology is constantly evolving, and new applications are arising, particularly for the millimeter wave bands. A novel application for radar is gait monitoring for fall prevention, which may play a key role in maintaining the quality of life of people as they [...] Read more.
Radar technology is constantly evolving, and new applications are arising, particularly for the millimeter wave bands. A novel application for radar is gait monitoring for fall prevention, which may play a key role in maintaining the quality of life of people as they age. Alarming statistics indicate that one in three adults aged 65 years or older will experience a fall every year. A review of the sensors used for gait analysis and their applications to technology-based fall prevention interventions was conducted, focusing on wearable devices and radar technology. Knowledge gaps were identified, such as wearable radar development, application specific signal processing and the use of machine learning algorithms for classification and risk assessment. Fall prevention through gait monitoring in the natural environment presents significant opportunities for further research. Wearable radar could be useful for measuring gait parameters and performing fall risk-assessment using statistical methods, and could also be used to monitor obstacles in real-time. Full article
(This article belongs to the Special Issue Wireless Body Area Sensor Networks)
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