Review of Wireless Body Sensor Networks

Abstract

Wireless body area networks (WBANs) are emerging as important networks that are applicable in various fields. WBAN gives its users access to body sensor data and resources anywhere in the world with the help of the internet. These sensors offer promising applications in areas such as real-time health monitoring, interactive gaming, and consumer electronics. WBAN does not force the patient to stay in the hospital which saves a lot of physical movement. This paper reviews a review of WBANs. We study the following: prior researches, applications and architectures of WBAN, and compression sensing techniques.

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International Journal of Engineering & Technology, 9 (4) (2020) 863-870
International Journal of Engineering & Technology
Website: www.sciencepubco.com/index.php/IJET
Research paper
Review of Wireless Body Sensor Networks
Sondous Sulaiman Wali1, Mohammed Najm Abdullah2
1Computer Engineering Department, University of Technology, Baghdad, Iraq
2Computer Engineering Department, University of Technology, Baghdad, Iraq
*Corresponding author E-mail: sondoussulaiman@gmail.com
Abstract
Wireless body area networks (WBANs) are emerging as important networks that are applicable in various fields. WBAN gives its users
access to body sensor data and resources anywhere in the world with the help of the internet. These sensors offer promising applications
in areas such as real-time health monitoring, interactive gaming, and consumer electronics. WBAN does not force the patient to stay in
the hospital which saves a lot of physical movement. This paper reviews a review of WBANs. We study the following: prior researches,
applications and architectures of WBAN, and compression sensing techniques.
Keywords: Compression sensing; Healthcare; Sensors; Wireless Body Area Network; WBAN survey.
1. Introduction
A Wireless Body Sensor Network is an emerging technology
that can be the application in E-Health care systems [1-2]. A
WBSN typically consists of a collection of low-power,
miniaturized, and lightweight devices with wireless
communication capabilities that operate in the proximity of a
human body. Generally speaking, these devices can be
distinguished into three types: sensors, actuators, and personal
digital assistants (PDA) [3]. The PDA acts as a sink to collect all
the information attained by the sensors and transmit it to the
users (patient, nurse, physician, etc.) via an external gateway [4].
Gartner states that the worldwide wearable devices have
generated a revenue of $28.7 billion in 2016, and is expected to
grow from 275 million units in 2016 to 477 million units in 2020,
generating a revenue of $61.7 billion [5]. The Global mobile data
traffic forecast by Cisco predicts that, by 2020, the number of
wearable devices will increase to 601 million globally [6].
According to a survey conducted by Ericsson Consumer Lab
(Stockholm, Sweden), 60% of the participants believe that, in
the next five years, biomedical sensors like smart patches,
indigestible pills, and other implantable chips would be
commonly used [7]. WBSNs consists of various sensors which
are placed in, around, or on the human body to monitor the
various parameter like temperature, blood pressure, ECG, EEG,
etc. The involvement of WBSN started with defense when this
technology was used in their activity [8]. Since then, it has
evolved in human life and presently it is used in every field of
life. The WBSNs can be applied in numerous medical and non-
medical applications. [9]
Sensors are placed on both the inside and outside of the body
and various bodily information is transmitted and received.
Signals can even be sent to the nearest hospital in emergencies.
However, because WBSNs must operate in and on the human
body, unlike traditional wireless sensor networks (WSNs),
sensor size in WBSNs is extremely small and energy resources
are limited. Therefore, it is crucial to reduce the energy
consumption of sensors in WBSN environments [10].
The underlying aims of WBAN are to acquire physiological data
from the patient(s) for steady monitoring that conclusively needs
an efficient routing approach [11]. The reliable, secure, and
efficient implementation of routing protocol is a challenging task
in WBAN due to its unique characteristics and limitations, such
as energy reduction or overheating of implanted sensors nodes.
The heat-rise and energy depletion influences the constancy of a
network; hence the data is transmitted through various paths in
WBAN. During the last decade, several studies have been
carried out, and many systems have been developed on WBAN.
The various characteristics of WBAN have raised the number of
issues in different layers of WBAN. At the physical layer
problems of interoperability, temperature control, changing
topology, interference, fault acceptance, security, etc. The issues
related to the MAC layer are dynamic channel assignment,
control packets overhead, protocol overhead, throughput,
synchronization, delay control, etc. The problems related to the
network layer are mobility, localization, traffic control,
temperature and heat control, optimum routing, etc. [12].

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2. Related works
In this section, the state of the WBSN. Details about these
models are provided next. Table 1 summarizes several studies
on WSBN using various modeling techniques.
In [28] The QoS values computed through the DRT profile
provide maximum reliability of data transmission within an
acceptable latency and data rates. The DRT is based on the
carrier sense multiple access with collision avoidance
(CSMA/CA) channel access mechanism and considers IEEE
802.15.4 (low-rate WPAN) and IEEE 802.15.6 (WBASN).
Then, a detailed performance analysis of different frequency
bands are done which are standardized for WBASNs, that is,
420MHz, 868MHz, 2.4GHz, and so forth. Finally, a series of
experiments are conducted to produce statistical results for the
DRT profile concerning delay, reliability, and packet delivery
ratio (PDR). The calculated results are verified through
extensive simulations in the CASTALIA 3.2 framework using
the OMNET++ network simulator.
In [29] Develop an Intel Galileo based WBSN platform. The
physiological characteristics such as (Electrocardiogram) ECG
captured from the human body can be used as an exclusive way
for entity identifications (EIs) to authenticate data in WBSNs.
using Matlab software. developed fuzzy vault based data
authentication methods for entity identification in WBSNs.The
HKD-10A sensor for ECG collection from the human and Wi-
Fi module (N-2230) is used for wireless data transmission
between source and destination. Three fuzzy vaults-based
security algorithms for entity identification are also compared
namely; MWFT, SWFT, and AC/DFT. The AC/DCT provides
better FRR, FAR, and HTER values than MWFT and SWFT.
In [30] used The Castalia simulator and OMNET ++ provide
power Proficiency in collecting patient data. In the data link
layer, MAC (Medium Access Control) protocols WBAN helps
with energy efficiency. The attributes like ECG, pulse rate,
temperature are reported to the doctor and relatives/caretaker of
patients for every hour to alert them.
In [31] simulate the energy consumption, throughput, and
reliability for both, ZigBee IEEE 802.15.4 Mac protocol and
BAN IEEE 802.15.6 exploited in medical applications using
Guaranteed Time Slot (GTS) and polling mechanisms by
CASTALIA software. Then, compare and analyze the
simulation results. These results show that focused on giving
decisive factors to choose the appropriate MAC protocol in a
medical context depending on the energy consumption, some
used nodes, and sensors data rates.
In [32] The identification process for establishing a decision
matrix is based on a crossover of ‘time of arrival of the patient
at the hospital/multi-services’ and ‘hospitals’ within mHealth.
Then, the development of a decision matrix for hospital selection
is based on the MAHP method. Finally, the validation of the
system that is used.
In [33] Implement several scenarios using Castalia taking into
account variable packet rate, network size, and temporal
behavior in both single-hop and multiple hop WBAN
configurations to evaluate performance in terms of QoS
parameters such as packets received and power consumption.
The experimental results of the simulation show, the received
packets for each node degraded to a higher packet rate
considering the n temporal model compared to no temporal
model.
In [34] IEEE 802.15.4, Medium Access Control Protocol is
designed to ensure the timely delivery of medical data, along
with meeting QoS requirements for healthcare applications
based on a wireless body sensor network. Guaranteed time slots
(GTS) are allotted according to the variable rate of
heterogeneous data traffic that is sensed by different sensor
nodes ensuring energy efficiency, low latency, high throughput,
etc. We simulated different scenarios representing normal and
critical conditions of patients using Castalia 3.3 and OMNeT++.
The results showed that there is a significant reduction in power
consumption of 20% depending on the diversity of the GTS
configuration. Average time-varying GTS, temporal, and varied,
unrelieved time-packets are 76% at 8 nodes and 66% by varying
GTS, no Temporal at 11 nodes within the 240 ms delay allowed
in the healthcare application.
In [35] a Wireless Body Sensor Network (WBSN) based,
portable, easily affordable, miniatured, accurate “Heartrate
Monitoring System (HMS)”. HMS can be used to regularly
examine the cardiac condition at home or hospital to avoid or
early detection of any serious condition. The system was
validated with the case study of forty healthy young subjects.
The results produced by HMS were, each subjects’ 99% data
was in the custom range and all subjects were healthy.
In [36] A routing algorithm based on ant optimization
technology was used to efficiently distribute energy use to
nodes. Thus reducing energy consumed and prolonging the life
cycle of the nodes, as well as avoiding damage to the patient's
body tissues. The protocol was initially compared with the
conventional LEACH routing protocol to demonstrate its
efficiency in extending node life, and then it was used with the
experimental network to examine energy uses. The results
obtained were compared with other results obtained through
conventional and advanced routing protocols, and there was a
significant reduction in power consumption which proved the
efficiency of the algorithm.
In [37] a general analytical model for performance evaluation of
the IEEE 802.15.6 based WBANs with heterogeneous traffic in
terms of priority. The model is composed of two complementary
submodels. The first is a renewal reward-based analytical sub-
model that efficiently describes the IEEE 802.15.6 CSMA/CA
Back-off process. The second sub-model is an M/G/1 queuing
model with a non-preemptive priority. Using Matlab and Maple,
we analyzed the analytical model under ideal channel conditions
and saturated network traffic regimes. Then, we performed
simulations of the IEEE 802.15.6 standard using the Castalia
Simulator based on OMNeT++. Results showed the accuracy of
the model for managing WBANs with heterogeneous traffic.
In [38] An application classification algorithm and a packet flow
mechanism are developed by incorporating SDN principles with
WBAN to effectively manage complex and critical traffic in the
network. Furthermore, a Sector-Based Distance (SBD) protocol
is designed and utilized to facilitate the SDWBAN
communication framework. Finally, the proposed SDWBAN
framework is evaluated through the CASTALIA simulator in
terms of Packet Delivery Ratio (PDR) and latency. The
experimental outcomes show that the system achieves high
throughput and low latency for emergency traffic in SDWBANs.

International Journal of Engineering & Technology
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Table 1: Literature survey
Author
name
Simulation
devise or
method
Methodology
Future scope in research
Evaluation results of the
proposed
Year of
publication
Negra et
al.[13]
-
Numerous techniques have
proven to support WBAN
applications, such as remote
monitoring, biofeedback,
and living assistance by
responding to specific
service quality requirements
(QoS).
-
-
2016
Habib et al.
[14]
Adaptive
sampling
technique
Progress on energy-efficient
mechanisms based on data
reduction for BSNs. It
reviewed compressive
sensing and adaptive
sampling approaches to
reduce the amount of data
collected and transmitted
over the network.
Reduce the number of bits
needed to represent the
sensed data before
transmission, while taking
into consideration the trade-
off between the
computational cost and the
compression ratio. Then,
combine the compressive data
model with an adaptive
sampling technique to further
reduce the collected data
before transmission.
Provided a discussion about the
differences and the advantages of
the different techniques and
formalized an open question
concerning the data compression
in BSNs.
2017
Hegde and
Prasad [15]
OMNeT++,
Castalia3.2
The lower layer parameters
in WBAN by analyzing
throughput using Temporal
and noTemporal variations
-
Evaluates for WSNs over wired
networks and results in WBAN in
medical applications with greater
efficiency. Requirement of QoS
with limitation of power in sensor
nodes of WBANs, and deploying
equipment in larger numbers with
low cost and high efficiency.
2017
CHEN et al
[16]
FPGA and
synthesized by
the VLSI
technique
A VLSI implementation of
a micro control unit (MCU)
for wireless body sensor
networks (WBSNs). This
design consists of interface,
encryption, four register
banks, compression, and
detection of QRS points.
VLSI implementation using
adiabatic logic
MCU design contained 7.61k gate
counts and consumed 1.33 mW
when operating at 200 MHz by
using a 90-nm CMOS process.
April 2017
Sodagariet al.
[17]
CR
Investigates how cognitive
radio and dynamic spectrum
access are used for BANs to
save spectral resources.
Specifically, the features
associated with the usage of
the three major cognitive
radio paradigms of
underlay, interweave and
overlay in these networks.
Investigation of the
performance of CR-enabled
MWBANs with moving
bodies.
A comparison between the
common methods of spectrum
sensing as well as spectrum
access. It also focused on fixed
and triggered sensing and access
timing methods.
2018
Takabayashi
et al. [18]
MATLAB
The performance of the
quality of service (QoS)
control scheme in a multi-
hop WBAN based on the
IEEE Std. 802.15.6 is
evaluated.
Evaluate on a WBAN due to
the existence of selfish nodes.
it will also devise a method of
removing detected selfish
nodes.
The Pd became high when the
ratio of the measurement value at
the first collision and the second
collision was 1: 2, and the Fd
became low when the rate was 2:
1. It was also found that the Pd
decreased with the increase in the
number of nodes.
2018
Waheed. et
al.
[19]
Two-Way
Relay
Cooperation
The reliability and energy
efficiency in WBAN
applications play a vital
role. The analytical
expressions for energy
efficiency (EE) and packet
error rate (PER) are
formulated for two-way
relay cooperative
communication. link length
extension and diversity is
achieved by joint network-
channel (JNC) coding the
cooperative link.
-
provided a gain of approximately
54% inefficient link length
compared to the direct link for in-
body communication, 51.6% for
on-body LOS, and 50% for on-
body NLOS. It is shown that an
extended hop length of 7.5 10% in
one-way relay communication and
5–7.5% in two-way relay
cooperation for in-body, 8.5–14%
for one-way relay communication,
and 5.5–8.5% for two-way relay
cooperation in on-body LOS
scenario and 5–7% for one-way
relay communication and 3.5–5%
for two-way relay cooperation in
case of on-body NLOS is
achieved for cooperative
communication in the simplest
case
February
2018

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International Journal of Engineering & Technology
Bhatia and
Kumar [20]
MADM
method
Investigates for best
network selection from the
available networks
depending upon different
QoS requirements for
different WBAN
applications. The different
multiple attribute decision-
making algorithms are used.
Application of game theory
approach for network
selection.
The scheme can select the best
network for different data traffics
for cognitive-enabled WBANs.
March 2018
Khan, R. A.,
& Pathan,
A.-S. K. [21]
-
Tiny-sized sensors could be
placed on the human body
to record various
physiological parameters
and these sensors are
capable of sending data to
other devices.
An interesting direction
would be investigating edge
computing-based/assisted
BSN systems and would also
have an impact on the BSN
and WBASN
-
March 2018
Omuro et
al.[22]
CSMA/CA
These works detect the
selfish node in WBAN
utilizing CSMA/CA defined
in IEEE 802.15.6
an effective error control
scheme for multi-hop
WBANs should be
considered. Also, PHY
evaluation indexes were
mainly considered. Hence,
evaluating the system delay
and throughput in the network
layer should be considered for
multi-hop cases. As an
extension of IEEE Std.
802.15.6, cases with greater
than three hops should also be
evaluated and analyzed
theoretically.
The numerical results show that
the scheme outperforms the
standard scheme in terms of the
PDFR, some transmissions, and
energy efficiency. Case 3 showed
better performance than the other
cases at both hops. When d2hops
was fixed, it was shown that
performance became optimal
when d1st = d2nd (except Case 2)
from computer simulations and
theoretical analysis. This result is
expected to greatly contribute to
the optimization of how nodes and
hubs are arranged when designing
a WBAN.
November
2018
Murtaza
Cicioğlu and
Ali Çalhan
[23]
SDN, WBAN
routing
algorithm
a WBAN architecture based
on the SDN approach with a
new energy‐aware routing
algorithm for healthcare
architecture is proposed. To
develop a more flexible
architecture, a controller
that manages all HUBs is
designed. The proposed
architecture is modeled
using the Riverbed Modeler
software for performance
analysis.
Develop new algorithms
using fuzzy logic for multi‐
attribute decision making,
considering different
parameters such as specific
absorption rate (SAR) and
data rate to improve routing
algorithm. The routing
algorithm is designed only for
inter‐WBAN communication.
It is therefore planned to use
the routing algorithm
developed in future studies in
intra‐WBAN communication.
IEEE 802.15.6 for intra‐WBAN
communication and WBANFlow
architecture for inter‐WBAN
communication are developed,
and all the QoS requirements are
met. At the same time, a new
energy‐aware routing algorithm
named SDNRouting, which runs
on the controller and its
performance is analyzed for
different cases.
April 2019
Abidi et al.
[24]
MATLAB
proposed an effective new
protocol for the wireless
body area network, using a
gate body sensor, to direct
data to its final destination
focus on Study cooperation
between the contract to
improve system performance.
satisfactory results in terms of
network stability and lifetime.
Because of the collaborative
characteristics of wireless body
area networks
April 2019
Alkhayyat et
al. [25]
TCMN,
IEEE
802.15.6.
A cognitive cooperative
communication with two
master nodes, namely, as
two cognitive master nodes
(TCMN), which can
eliminate the collision and
reduce the retransmission
process.
Design and investigate a
MAC protocol for inter-
WBSN cooperation.
The energy-saving of the TCMN
is 99% concerning DTM and
ICCM under IEEE 802.15.6
CSMA.
May 2019
Latha R and
Vetrivelan P
[26]
Telemedicine
techniques,
Bayes' theory.
A collection of telemedicine
techniques used by
WBANs. The probability of
sending emergency
messages can be determined
using Bayes' theory with
probability evidence. The
maximum linear regression
linear prediction (MAP) can
be applied, and the binary
classification can be used as
a substitute for MLE.
-
Explains the network model with
16 variables, with one describing
immediate consultation, as well as
another three describing
emergency monitoring, delay-
sensitive monitoring, and general
monitoring. The remaining 12
variables are observations related
to latency, cost, packet loss rate,
data rate, and jitter.
April 2020
Zeinab
Shahbazi and
Yung-Cheol
Byun[27]
Castalia and
Blockchain
technique
Wireless Body Area
Networks (WBANs) used
by Castalia a simulation
tool its comparison is made
with Multipath Ring
Routing Protocol (MRRP),
thermal-aware routing
The planning to extend the
proposed protocol to deal
with the different body
postures, i.e., the postural
movement of the body will be
considered along with the
maintained temperature and
energy of the network.
The protocol performs
significantly better in balancing
of temperature (to avoid damaging
heat effect on the body tissues)
and energy consumption (to
prevent the replacement of battery
and to increase the embedded
sensor node life) with efficient
June 2020

International Journal of Engineering & Technology
867
3. WBAN Application
Wireless body area network applications are proving
themselves very efficiently and these applications are not
just for human health care monitoring but there are also
many other applications such as sports, fitness, gaming,
electronics, measuring body position, location of a person,
military, and many other that are using WBAN approach
for different purposes, Figure1 shows some applications
that are used by human and are based on WBAN systems.
The astonishing use of WBAN applications is for health
care, entertainment, sports, and fitness applications, all
these applications are very demanding and reliable.
From the list of many advanced WBAN applications, few
are fully developed and can empower their technologies
in a real time environment; some of these applications are
discussed below. [39]
Fig. 1. Applications of WBAN. [39]
3.1 Health Care
Health care and a health delivery system based on
WBSN requires multidisciplinary research and
development in biology, physiology, physics, chemistry,
micro/nanotechnologies, material sciences, industrial
sectors like medical devices, electronics, microchips,
technical textiles, and telecommunications and related
engineering disciplines. Moreover, all economically
developed countries are undergoing social changes such
as aging populations, further integration of people with
disabilities, and an increase in chronic diseases. These
changes will accelerate further development and market
growth of WBSNs. [40]
3.2 Entertainment
Wireless body sensor networks (WBSNs) mostly consist
of low-cost sensor nodes and implanted devices which
generally have extremely limited capability of
computations and energy capabilities. Mobile wearable
and wireless muscle computer interfaces have been
integrated with the WBSN sensors for various
applications such as rehabilitation, sports, entertainment,
gaming, and healthcare. [41]
3.2 Lifestyle and Sports
In Sports, WBSN can be used to examine the health of
the athletes. Readings can be taken from the athletes
without requiring them to exercise on a treadmill.
Coaches can take a closer look at the strong and weak
points of an athlete by measuring various body
conditions like change in a heartbeat, oxygen level, etc.
during a race and other real-life scenarios. This can help
in improving their shortcomings and improving their
skills.
3.3 Military
Uses of WBSN in defense are many. Examining the
health condition of soldiers, checking the level of
hydration, tracking their location and body temperature
monitoring are few of them. All the readings can be used
for providing help to the soldiers when they get injured,
to get an idea of when strength, precision, attention have
to be enhanced and can also be used for reducing
incidents of friendly fire due to misunderstanding in
identity by telling them their exact location and identity
time to time. [42]
4. Architecture of WBSN
In this section, Table 2. the architectures of the WBSN.
Details about the previous researches:
5. Compressive sensing
Compressed sensing (CS) is a signal processing
technique that enables signal reconstruction from a small
set of linear projections, called measurements, provided
the signal is sparse in some domain. Compressed sensing
(CS) has emerged as a promising framework to address
these challenges because of its energy-efficient data
reduction procedure [44]. Compressive sensing samples
the signal by a much smaller number of samples than
required by the Nyquist–Shannon theorem. It is based on
an assumption of sparsity for the signal. Naturally, this
assumption is true for most data forms of information in
nature. Compressive sensing mainly is a challenge to:
a. Compressively measure a signal while its
information content is kept preserved.
b. To recover the original signal after
compressive sensing. The compressive
method has a great application potential
and can be used in a wide range of
applications, like:
• Location-based services [45].
• Signal processing [46].
• Texture analysis [47].
• Power line communications [48].
• Power quality analysis [49–51].
• Power system planning [52-53].
• Human motion analysis [54].
algorithm (TARA), and
Shortest-Hop (SHR).
data transmission achieving a high
throughput value.
Entertainment
and Gaming
Consumer
Electronics
Emergency
Services
Medical
WBAN
Sports
and
Fitness
Personal
Health Care
LifeStyle
Military

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Table 2: comparison between previous architectures
Author name
Architectures of the WBSN
Communications performed in WBSN
Year of
publication
Tier1
Tier2
Tier3
Sonakshi
Gupta and
Parminder
Kaur. [43]
The on-body and /or
embedded wearable
sensors hubs
Base stations
(sink)
The remote
medical
server by
means of
the standard
base, for
example,
web.
October
2015
Khan et
al.[21]
Electroencephalogram
(EEG),
electrocardiogram
(ECG),
electromyography
(EMG), or blood
pressure measuring
sensors.
Personal server
(PS), known as
the sink or the
base station
(BS).
A medical
doctor, or a
medical
center, or
any medical
database.
March 2018
Zheng et al.
[12]
sensors attached to
the body surface or
implanted into the
body.
Smartphones,
personal
computers, or
other
intelligent
electronic
devices.
The
terminal
data center
is mainly
composed
of remote
servers
providing
various
applications.
April 2019
Murtaza
Cicioğlu and
Ali Çalhan.
[23]
sensor nodes and a
HUB, IEEE 802.15.6
Gateway, such
as a Wi‐Fi
SDN
approach
April 2019
Zeinab
Shahbazi and
Yung-Cheol
Byun[25]
All sensor nodes
implanted in or on the
human body
Through
wireless
technology
such as
Bluetooth,
WiFi, and
ZigBee.
The
blockchain
model
June 2020
• Medical image processing [55].
• Human–robot interaction [56].
• Electrocardiogram processing [57].
• Image enhancement [58-59].
• Image adaptation [60].
• Software-intensive systems [61].
• Agriculture machinery [62-63].
• Data mining [64].
6. Conclusion
In this paper, we review previous researches on
wireless body area networks. In particular, this work
provides an overview of previous researches,
applications, and architectures in WBAN and sensor
compression technology. WBAN is a very useful
emerging technology having immense utilities and
benefits in daily life not only for Healthcare but also for
Athletic training, Public Safety, Consumer electronics,
secure authentication, and Safeguarding of uniformed
personnel. We feel that this review can be considered as
a source of inspiration for future research directions.
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