Download full-text PDF

Modeling Propagation Characteristics for Arm-Motion in Wireless Body Area Sensor Networks

Article (PDF Available)  · August 2012with28 Reads
DOI: 10.1109/BWCCA.2012.38} · Source: arXiv
Abstract
To monitor health information using wireless sensors on body is a promising new application. Human body acts as a transmission channel in wearable wireless devices, so electromagnetic propagation modeling is well thought-out for transmission channel in Wireless Body Area Sensor Network (WBASN). In this paper we have presented the wave propagation in WBASN which is modeled as point source (Antenna), close to the arm of the human body. Four possible cases are presented, where transmitter and receiver are inside or outside of the body. Dyadic Green's function is specifically used to propose a channel model for arm motion of human body model. This function is expanded in terms of vector wave function and scattering superposition principle. This paper describes the analytical derivation of the spherical electric field distribution model and the simulation of those derivations.
arXiv:1208.2332v1 [cs.SY] 11 Aug 2012
1
Modeling Propagation Characteristics for
Arm-Motion in Wireless Body Area Sensor
Networks
Q. Ain, A. Ikram, N. Javaid, U. Qasim
, Z. A. Khan
§
University of Alberta, Alberta, Canada
Department of Electrical Engineering, COMSATS
Institute of Information Technology, Islamabad, Pakistan.
§
Faculty of Engineering, Dalhousie University, Halifax, Canada.
Abstract—To monitor health information using wireless sensors
on body is a promising new application. Human body acts as a
transmission channel in wearable wireless devices, so electromag-
netic propagation modeling is well thought-out for transmission
channel in Wireless Body Area Sensor Network (WBASN). In
this paper we have presented the wave propagation in WBASN
which is modeled as point source (Antenna), close to the arm
of the human body. Four possible cases are presented, where
transmitter and receiver are inside or outside of the body. Dyadic
Green’s function is specifically used to propose a channel model
for arm motion of human body model. This function is expanded
in terms of vector wave function and scattering superposition
principle. This paper describes the analytical derivation of the
spherical electric field distribution model and the simulation of
those derivations.
Index Terms—Wireless Body Area Networks, Dyadic Green’s
Function
I. INTRODUCTION
Hospitals throughout the world are facing a unique problem,
as the aged population is increased, health-care population is
decreased. Telecommunication community is not doing much
work in the field of medicine however, there is a need of
remote patient monitoring technology. To fulfill this task,
it is required to build communication network between an
external interface and portable sensor devices worn on and
implemented within the body of the user which can be done
by BASNs.
BASNs is not only useful for remote patient monitoring,
but can also establishes within the hospitals; like in operation
theaters and intensive care units. It would enhance patient
comfort as well as provide ease to doctors and nurses to
perform their work efficiently. BAN is used for connecting
body to wireless devices and finds applications in various areas
such as entertainment, defense forces and sports.
The basic step in building any wireless device is to study
the transmission channel and to model it accurately. Channel
modeling is a technique that has been initiated by a group of
researchers throughout the world [1]. They have studied path
loss and performed measurement campaigns for wireless node
on the body [2-8]. Some researchers have taken into account,
the implanted devices which are the area of BAN called
as intra-body communication [9]. For the short range low
data rate communication in BAN, measurement groups have
considered Ultra-Wide Band (UWB) as the appropriate air
interface. The models developed by measurement campaigns
are only path loss models and do not provide any description
of propagation channel.
It is important to study the propagation mechanism of radio
waves on and inside the body in order to develop an accurate
BAN channel model. This study will show the underlying
propagation characteristics. It would help in the development
of BAN transceivers which are much suited to the body
environment.
For a given position of the transmitter on or inside the body
it is required to find out the electromagnetic field on or inside
the body for a BAN channel model. This is quite a critical
problem that requires a large amount of computational power.
Therefore, it is necessary to derive an analytical expression
which will perform this objective. In short this determines
which propagation mechanism takes place, that is reflection,
diffraction and transmission [10]. An appropriate method of
doing this task is by using Dyadic Green’s function. The
solution of canonical problems, such as cylinder, multi layer
and sphere have been solved in Electro Magnetic (EM) theory,
using Dyadic Green’s Functions [11-13].
II. MOTIVATION
Recently, WBASNs shows potential due to increasing ap-
plication in medical health care. In WBASNs, each sensor
in the body sends it’s data to antenna,both sensors and
antenna are worn directly on the body. Examples include
sensors which can measure Brain activity, blood pressure,
body movement and automatic emergency calls. We require
simple and generic body area propagation models to develop
efficient and low power radio systems near the human body. To
achieve better performance and reliability, wave propagation
needs to be modeled correctly. Few studies have focused on
analytic model of propagation around a cylinder (as human
body resembles a cylinder) using different functions. These
functions involve Mathieu function, Dyadic Green’s function,
Maxwell’s equations, Finite Difference Time Domain (FDTD)
and Uniform Theory of Diffraction (UTD). Some of these
approaches have already proven effective for evaluating body
area communication system proposals.
2
Finite Difference Time Domain had successfully measured
the communication scenarios. Complete Ultra-Wide band
models have been developed using measurements and simula-
tions, however they do not consider the physical propagation
mechanism. So, the researchers have to rely on ad-hoc model-
ing approaches which can result in less accurate propagation
trends and inappropriate modeling choices [14, 15].
Uniform Theory of Diffraction depends on a ray tracing
mechanism allowing propagation channel to be explained in
terms of ray diffraction around the body . It typically based
on high-frequency approximations which is not valid for low
frequencies, also not useful when antenna is very close to the
body [16].
A generic approach is proposed to understand the body area
propagation by considering the body as a lossy cylinder and
antenna as a point source by using Maxwell’s equation. A
solution for a line source near lossy cylinder is derived using
addition theorem of Hankel functions then the line source
is converted into the point source by taking inverse Fourier
transform. The model accurately predicts the path loss model
and can be extended to all frequencies and polarities but this
is limited in scope and not always physically motivated [17].
Mathieu functions are also used for body area propagation
model. The human body is treated as a lossy dielectric elliptic
cylinder with infinite length and a small antenna is treated as
three-dimensional (3-D) polarized point source. First the three-
dimensional problem of cylinder is resolved into 2-D problem
by using Fourier transform and then this can be expanded in
terms of Eigen functions in cylindrical coordinates. By using
Mathieu function exact expression of electric field distribution
near the human body is deduced [18].
The propagation characteristics of cylindrical shaped human
body have been derived using Dyadic Green’s functions.
The model includes the cases of transmitter and receiver
presents either inside or outside of the body and also provides
simulation plots of Electric field with different values of
angle (θ). All the above proposals describe the propagation
characteristics of cylindrically shaped human model [19].
We have developed a simple but generic approach to
body area propagation derived from Dyadic Green’s Function
(DGF). This approach is for arm motion of human body.
When the human arm is moved in r, θ, φ direction, propagation
characteristics of spherical shaped have been derived using
DGF. First, we use spherical vector Eigen functions for finding
the scattering superposition. Four cases are considered for
either transmitter or receiver is located inside or outside the
body. Finally, simulated results of electric field distribution
with different values of angle have shown.
III. MATHEMATICAL MODELING FOR ARM MOTION
USING DYADIC GREENS FUNCTION
In this paper, spherical symmetry is used to represent in
and around the arm of the human body. A point on body is
a sensor, denoted by x which represents (r,Θ,φ) coordinates
in the spherical coordinate system and x
0
is the location of
transmitting antenna. (r,Θ ,φ) are unit vectors along radial,
angle of elevation from z-axis and azimuthal angle from x-
axis as shown in figure 1.
Fig. 1. Human body model showing arm motion in 3D.
A. Electric Field Propagation Characteristics
Let E(x) be electric field at point x due to current source
J(x
0
). The general formula for Electric field can be written
as:
E(x) = µ
p
Z Z Z
V
G(x, x
o
)J(x, x
0
)dv (1)
V is volume of source, J(X
0
) is the current source,
G(x, x
0
) is the Dyadic Green’s function
ω
is the radian
frequency of transmission and
µ
p
is magmatic permeability of
the medium. A Dyadic Green’s function is a type of function
used to solve inhomogeneous differential equations subject to
specific initial conditions or boundary condition.
B. Spherical Wave Vector Eigen Function
As we are considering arm motion of human body, so
spherical symmetry is used by taking shoulder as center. For
this, spherical eigen functions are used to write the Dyadic
Green’s function.
Dyadic Green’s function is basically depends on the spher-
ical vector eigen functions [14]. These eigen functions are
L
nhk
(χ), M
nhk
(χ) and N
nhk
(χ), where k is the wave number
of medium, n is an integer, h is a real number and x is a point
in space. These all are the solutions to the Helmholtz equation
having three components in r, Θ and φ. These vector eigen
functions are given by [19]:
L
nhk
(χ) =
nhk
(χ)] (2)
M
nhk
(χ) = ×
nhk
(χ)] (3)
N
nhk
(χ) =
1
k
×
nhk
(χ)] (4)
3
In above eigen functions, Laplacian operator in the spherical
coordinate system is . It’s mathematical expression is given
as:
=
r
+
r∂θ
+
r sin θφ
(5)
x represents the point in space having components r, Θ
and φ. Solution of Helmoltz equation is Ψ
nhk
(x) which is the
scalar eigen function [19].
nhk
(χ)] = Z
n
(ηr)P
h
n
(cos θ)
cos
sin
(6)
Z
n
is a general spherical function of order n. For sphere
we use Hankle function of first and second order which are
defined as:
[Z
n
(ηr)] = (1)
n
(ηr)(
d
drη
2
r
)
n
(
sin(ηr )
ηr
)
n
(7)
η is the propagation constant in direction of φ, whereas
k
2
= η
2
+ h
2
. The laplace operator is applied and find the
eigen values L
nhk
, M
nhk
and N
nhk
by using eigen function.
The vector eigen function in (2), (3) and (4) becomes:
L
nhk
(χ) =
Z
n
(ηr)
r
P
h
n
(cos θ)
cos
sin
+
z
n
(ηr)
r
θ
P
h
n
(cos θ)
cos
sin
+
hZ
n
(ηr)
r sin θ
P
h
n
(cos θ)
sin
cos
(8)
M
nhk
(χ) =
hZ
n
(ηr)
sin θ
P
h
n
(cos θ)
sin
cos
Z
n
(ηr)
θ
P
h
n
(cos θ)
cos
sin
(9)
N
nhk
(χ) =
nZ
n
(ηr)
kr
P
h
n
(cos θ)
cos
sin
+
1
kr
rZ
n
(ηr)
r
P
h
n
(cos θ)
cos
sin
h
sin θ
P
h
n
(cos θ)
sin
cos
(10)
These three vector eigen function are perpendicular among
themselves as well as with respect to each other [11]. In the
form of matrices, vector Eigen functions can be written in this
form,
L
nhk
(χ) =
Z
n
)(ηr)
r
P
h
n
(cos θ)
cos
sin
Z
n
(ηr)
r
P
h
n
(cos θ)
cos
sin
hZ
n
(ηr)
sin θ
P
h
n
(cos θ)
sin
cos
(11)
M
nhk
(χ) =
0
hZ
n
(ηr)
r
P
h
n
(cos θ)
cos
sin
Z
n
(ηr)
P
h
n
(cos θ)
sin
cos
θ
(12)
N
nhk
(χ) =
hZ
n
(ηr)
kr
P
h
n
(cos θ)
cos
sin
n
(ηr)
krr
P
h
n
(cos θ)
cos
sin
θ
h
sin θ
P
h
n
(cos θ)
sin
cos
(13)
C. Scattering Superposition
In scattering problems, it is desirable to determine an
unknown scattered field that is due to a known incident field.
Using the principle of scattering superposition we can write
Dyadic Greens equation as superposition of direct wave and
scattering wave. In Figure 2, concept of scattering superposi-
tion is shown in which there is a sensor located inside the arm
of body considered as sphere. The sensor transmits the wave
to antenna which is divided in two parts as Direct wave and
Scattered wave. The Direct wave is considered as wave directly
transmits from sensor to transmitter and scattered wave is
composed of reflection and transmission waves. Therefore,
general equation of scattering superposition is illustrated as:
G(x, x
0
) = G
d
(x, x
0
) + G
s
(x, x
0
) (14)
Dyadic Greens equation is divided in to two parts as direct
wave [G
d
(x, x
0
)] and scattered wave [G
s
(x, x
0
)]. The direct
wave corresponds to direct from source to measuring point
and scattered is the reflection and transmission waves due to
presence of dielectric interface.
D. Superposition of Direct Wave
The direct component of DGF is given as [11]:
G
d
(x, x
0
) =
rr
k
2
(δ(x x
0
) +
8π
Z
−∞
dh
X
n=−∞
1
n
2
x×
(
M
(1)
nhk
(X)
N
M
nhk
(X
0
) + N
(1)
nhk
(X)
N
N
nhk
(X
0
)
M
nhk
(X)
N
M
(1)
nhk
(X
0
) + N
nhk
(X)
N
N
(1)
nhk
(X
0
)
(15)
In the above equation of DGF, r > r
0
is for first case and
r < r
0
is second case.The denotes the conjugation and
N
is for the Dyadic product. Here we introduces superscript (1)
for outgoings wave and other for standing waves. If the vector
eigen function has the superscript (1) then, H
(1)
n
is chosen for
Z
n
and J
n
should be used otherwise.
E. Superposition of Scattered Wave
Here we discuss four different scenarios for the scatter-
ing components of DGF along with boundary conditions
G
s
(x, x
0
). (i) Both receiver and transmitter are inside the
body. (ii) The receiver is located outside and transmitter is
located inside the body. (iii) The receiver is located inside
and transmitter is outside the body. (iv) Both transmitter and
receiver are located outside the body. Receiver and transmitter
are in the order: 1 denotes the medium inside human body
and 2 is for free space medium.
F. Transmitter and Receiver Located Inside Body
In this case, Receiver and Transmitter both located inside
the body so we can write Dyadic Green’s equation as,
4
Fig. 2. Scattering Superposition
G
(11)
s
(x, x
0
) =
8π
Z
−∞
dh
X
−∞
1
η
2
x
×[M
nhk1
N
nhk1
]R
1
2 ×
(
N
nhk1
(X
0
)
T
M
nhk1
(X
0
)
T
(16)
R
12
contains reflection coefficients. R
12
is calculated in
literature using boundary conditions, its matrix is given by
[16]:
R
12
= [J
n
(η
1
d)H
n
(η
2
d) H
n
(η
2
d)J
n
(η
1
d)]
1
×[H
n
(η
2
d)H
n
(η
1
d) H
n
(η
1
d)J
n
(η
2
d)]
1
(17)
In the above equation of reflection coefficient ’d’ represents
radius of spherical body model, η
2
1
= k
2
1
h
2
, η
2
2
= k
2
2
h
2
, k
2
1
= ω
2
µ
1
ǫ
1
, k
2
2
= ω
2
µ
2
ǫ
2
. The 2x2 matrices for j
n
(ηd)
and H
n
(ηd) are expressed as:
B
n
(η
p
d) =
1
η
2
p
d
×
ωǫ
p
η
p
dB
n
(η
p
d) nhB
n
(η
p
nhB
n
(η
p
ωµ
p
η
p
dB
n
(η
p
d)
(18)
B
n
is either H
(1orJ
n
)
n
, B(.) is the derivative of B w.r.t the
whole argument, and p=1,2
G. Transmitter Located Inside and Receiver Located Outside
Body
In this case DGF can be written as :
G
(21)
s
(x, x
0
) =
Z
−∞
dh
X
n=−∞
1
η
2
×[N
nhk
.M
nhk
]T
12
N
nhk1
(x
0
)
T
M
nhk1
(x
0
)
T
(19)
In the above equation T
12
is a transmission coefficient
Matrix and given as:
T 12 =
2ω
πη
2
1
d
[J
n
(η
1
d)H
n
(η
2
d) H
n
(η
2
d)J
n
(η
1
d)]
1
×
ε
1
0
0 ε
(20)
H. Both Transmitter and Receiver Located Outside Body
G
s
(x, x
0
) =
Z
−∞
dh
X
n=−∞
1
n
2
×[M
nhk
N
nhk
]R
2
1
n
N
n
hk(X
0
)
T
M
n
hk(X
0
)
T
(21)
Similarly as R
12
, R
21
is the reflection coefficient matrix
and it is given as:
R21 = [J
n
(η
1
d)H
n
(η
2
d) H
n
(η
2
d)J
n
(η
1
d)]
1
×[J
n
(η
2
d)J
n
(η
1
d) J
n
(η
1
d)J
n
(η
2
d)]
(22)
I. Transmitter Located Outside and Receiver Inside Body
In this case, we can write DGF as:
G
s
(x, x
0
) =
Z
−∞
dh
X
n=−∞
1
n
2
×[M
nhk
N
nhk
]T
21
N
nhk1
(x
0
)
T
M
nhk1
(x
0
)
T
(23)
5
T
12
is the transmission coefficient matrix, given as:
T 21 =
2ω
Πηd
[J
n
(η
1
d)H
n
(η
2
d) H
n
(η
2
d)J
n
(η
2
2
d)]
1
×
ε
2
0
0 µ
2
(24)
IV. TRANSMITTER AND RECEIVER LOCATED OUTSIDE OF
THE BODY
In this section we presents the equation which is required
for simulation. With the help of simulation it will be easy to
study the propagation characteristics of arm motion making
spherical pattern.
G
s
(x, x
0
) =
Z
−∞
dh
X
n=−∞
1
n
2
G
nh
(x, x
0
)dh
(25)
G
nh
(x, x
0
) is stated as:
G
nh
(x, x
0
) =
N
nhk
(X)
1
M
nhk
(X)
1
× R21
N
nhk
(X
0
)
T
M
nhk
(X
0
)
T
(26)
V. SIMULATIONS
As we have defined earlier, arm motion at different angles
are presenting spherical pattern. Therefore, we simulate the
radio propagation environment having radius d = 1 5cm, meg-
natic permeability for human body (assume that permeability
of human body is approximately equal to air) µ
2
= 1.256 ×
10
6, similarly electric permittivity ε
2
= 2.5 63 × 10
10.
The dielectric constant is mean value of all tissues of human
body. We take the surrounding homogeneous medium to be
air with megnatic permeability µ
1
= 1.256 × 1 0
6 and
electric permittivity ε
1
= 8.8542 × 10
12. Frequency up
to GHz is used for BAN communication, which is for ISM
band. The Transmission frequency for simulation is 1GHz.
We assumed that the transmitter is acting as point source
at x
0
= (16cm,
π
2
, 0). The radial distance of receiver is
r
0
= 18cm from the central spherical axis of shoulder. For the
simulation, we assumed that receiver move along the azimuthal
angle for varying values of φ
0
and different heights from the
center of shoulder.
For simulation, we consider equation (25) in which
G
nh
(x, x
0
) is used in matrix form of eigen functions. This
equation has an integration which is not possible so we
approximate it to summation. Thus, we approximate equation
(25) in to this form:
G
s
(x, x
0
) =
L
X
l=L
Q
X
n=Q
1
n
2
G
nh
(x, x
0
)dh
(27)
L and Q are the truncation limits and H are the step
size of integration. N and H are so small that could be
ignored and has no effect on calculations. We only presents
electric propagation of multi-path reflection and transmission
waves of scattering DGF.This is more significant to represent
the attribute of arm motion as compared to the direct DGF.
Figure 2,3 and 4 show the scattering DGF (simulation) of
electric field with the change in θ.
Fig. 3. Magnitude of scattered field component E
φ
versus angle φ,with
different values of d and the angle is θ =
π
6
Using equation (27), we have three components in r,θ and
φ direction. Every Component of electric field is plotted as a
function of azimuthal angle φ. The values of φ is (0 to 2π),
whereas at z coordinate different values of receiver has been
plotted. The electric field is plotted, which is vector addition
of three components. These all parameters are shown in the
simulation graph.
By taking the value of θ =
π
6
, figure 2 shows that magnitude
of electric field (E
φ
) is decreasing as the distance of receiving
antenna is increasing from the sensor (transmitting antenna).
The plot shows electric field component at different values of
φ, varying from 0 to 2π. In this case, E
φ
is decreasing from
(4080 to 4 065)dB by replacing the receiving antenna from 0
cm to 10 cm.
In Figure 3 , when we take value of θ =
π
3
, magnitude of
electric field (E
φ
) again decreases as the antenna moves away
from sensor. For the values of φ from 0 to 2π, E
φ
has different
values from (4060 from 4068)dB. By changing position of
receiving antenna from 0 cm to 10 cm.
The values of distance and φ are same, as described in the
above graphs by only replacing the parameter θ = π. Similarly
in figure 4 values of E
φ
change from (4082 to 4074)dB
by moving the position of receiver away from transmitting
antenna, which in return decreases the electric field intensity.
6
Fig. 4. Magnitude of scattered field component E
φ
versus angle φ,with
different values of d and the angle is θ =
π
3
Fig. 5. Magnitude of scattered field component E
φ
versus angle φ,with
different values of d and the angle is θ = π
VI. CONCLUSION
We have proposed a generic approach to derive an ana-
lytical channel modeling and propagation characteristics of
arm motion as spherical model. To predict the electric field
around body, we have formulated a two step procedure based
on Dyadic Green’s function. First, we derive Eigen functions
of spherical model then calculated the scattering superposition
to come across reflection and transmission waves of antenna.
The model includes four cases where transmitter or receiver is
located inside or outside of the body. This model is presented
to understand complex problem of wave propagation in and
around arm of human body. Simulation shows that Electric
field decreases when receiver moves away from the shoulder
with change of angle θ.
REFERENCES
[1] T. Zasowski, F. Althaus, M. Stager, A. Wittneben, and G. Troster, ”Uwb
for noninvasive wireless body area networks: Channel measurements and
results, Proc. IEEE Conf. on Ultra Wideband Systems and Technologies,
pp. 285-289, Nov 2003.
[2] A. Fort, J. Ryckaert, C. Desset, P.D. Doncker, P. Wambacq, and L.V.
Biesen, ”Ultra-wideband channel model for communication around the
human body, IEEE Journal on Selected Areas in Communications, vol.
24, no. 4, pp. 927-933, April 2006.
[3] H. Ghannoum, C. Roblin, and X. Begaud,”Inves-
tigationoftheuwbon-bodypropagationchannel,
http://uei.ensta.fr/roblin/papers/WPMC2006HGBANmodel.pdf, 2005.
[4] D. Nierynck, C. Williams, and A. Nix, M.
Beach, ”Channelcharacterisationforpersonalareanetworks,
http://rose.bris.ac.uk/dspace/bitstream/1983/893/1/TD-05-115.pdf, Nov.
2007.
[5] A. Alomainy, Y. Hao, X. Hu, C.G. Parini, and P.S. Hall, ”Uwb on-
body radio propagation and system modelling for wireless body-centric
networks, IEE Proc. Commun., vol. 153, no. 1, pp. 107-114, 2006.
[6] Y. Zhao, Y. Hao, A. Alomainy, and C. Parini, ”Uwb on-body radio channel
modelling using ray theory and sub-band fdtd method, IEEE Trans. On
Microwave Theory and Techniques, Special Issue on Ultra- Wideband,
vol. 54, no. 4, pp. 1827-1835, 2006.
[7] J. Ryckaert, P.D. Doncker, R. Meys, A.D.L. Hoye, and S. Donnay, ”Chan-
nel model for wireless communication around human body, Electronic
Letters, vol. 40, no. 9, 2004.
[8] I.Z. Kovacs, G.F. Pedersen, P.C.F. Eggers, and K. Olesen, ”Ultra wideband
radio propagation in body area network scenarios, IEEE 8th Intl. symp.
on Spread Spectrum Techniques and Applications, pp. 102-106, 2004.
[9] J.A. Ruiz, J. Xu, and S. Shiamamoto, ”Propagation characteristics of
intra-body communications for body area networks, 3rd IEEE Conf. on
Consumer Communications and Networking, vol. 1, pp. 509-503, 2006.
[10] T. Zasowski, G. Meyer, F. Althaus, and A. Wittneben, ”Propagation
effects in uwb body area networks, IEEE Intrenational Conference on
7UWB, pp. 16-21, 2005.
[11] Z. Xiang and Y. Lu, ”Electromagnetic dyadic green’s function in
cylindrically multilayered media,” IEEE Trans. on Microwave Theory and
Techniques, vol. 44, no. 4, pp. 614-621, 1996.
[12] P.G. Cottis, G.E. Chatzarakis, and N.K. Uzunoglu, ”Electromagnetic
energy deposition inside a three-layer cylindrical human body model
caused by near-?eld radiators, IEEE Trans. on Microwave Theory and
Techniques, vol. 38, no. 8, pp. 415-436, 1990.
[13] S.M.S Reyhani and R.J. Glover, ”Electromagnetic modeling of spherical
head using dyadic green’s function, IEE Journal, , no. 1999/043, pp. 8/1-
8/5, 1999.
[14] T.Zasowski, F. Althaus, M. Stager, A. Wittneben and G. Troster, ”UWB
for noninvasive wireless body area networks: channel measurement
and results.”in 2003 IEEE conference on Ultra-Wide band system and
technologies,2003.pp.285-289.
[15] A. Alomainy, Y. Hao, X.Hu,C.G. Parini and P.S. Hall, ”UWB on-body
radio propagation and system modeling for body centric networks, in
IEEE communication proceeding, vol. 153, no. 1, February 2006, pp.
107-114.
[16] D. A. Macnamara, C, Pistorius and J. Malherbe, In troduction to the
uniform geometrical theory of diffraction. Artech House:Boston, 1991.
[17] C.T. Tai, Dyadic Green’s Functions in Electromagnetic Theory, IEEE,
New York, 1993.
[18] Le-Wei Li, Senior Member, IEEE, Mook-Seng Leong, Senior Member,
IEEE, Pang-Shyan Kooi, Member, IEEE,and Tat-Soon Yeo, Senior Mem-
ber, IEEE
[19] Astha Gupta, Thushara D. Abhayapala, Body Area Networks: Radio
Channel Modelling and Propagation Charaterstics”.
Project
optimization,GA,BPSO,WDO,ACO,appliances scheduling,hybrid power generation,solar PV and diesel generator
Project
Designing routing protocol for balanced energy consumption in underwater wireless sensor networks
Conference Paper
January 2008
    Many current and future wireless devices are wearable and use the human body as a carrier. This has made the body an important part of the transmission channel of these wireless devices. Inclusion of the body as a transmission channel will see future wireless networks rely heavily on Body Area Networks (BAN). BAN will be used not only in medical applications but also in personal area network... [Show full abstract]
    Article
    September 2013 · Health and Technology
      A review of earlier work on Wireless Body Area Networks (WBANs) is given here as these networks have gained a lot of research attention in recent years since they offer tremendous benefits for remote health monitoring and continuous, real-time patient care. However, as with any wireless communication, data security in WBANs is a challenging design issue. Since such networks consist of small... [Show full abstract]
      Article
      Full-text available
        Ultra wideband (UWB) is a promising technology for wireless body area networks (WBANs). The authors investigate the wave propagation in the frequency range of 1-6-GHz for non-line-of-sight (NLOS) channels from the front to back of a human body by considering different wave polarisations: perpendicular and tangential with respect to the body. Time domain electromagnetic (EM) simulation using... [Show full abstract]
        Article
          Using wireless sensors placed on a person to continuously monitor health information is a promising new application. At the same time, new low-power wireless standards such as Bluetooth and Zigbee have been proposed for short range, low data-rate communication matching the requirements of these bio-medical applications. However, there are currently few measurements or models describing... [Show full abstract]
          Discover more