E-Health Telecommunication Systems and Networks, 2012, 1, 19-25
http://dx.doi.org/10.4236/etsn.2012.12004 Published Online June 2012 (http://www.SciRP.org/journal/etsn)
A WBAN for Human Movement Kinematics and
ECG Measurements
Ahmed Baraka, Ahmed Shokry, Ihab Omar, Saged Kamel, Tarek Fouad,
Mohamad Abou El-Nasr, Heba Shaban
Arab Academy for Science, Technology & Ma ri time Transport (AASTMT) , Alexandria, Egypt
Email: hshaban@vt.edu
Received April 1, 2012; revised May 10, 2012; accepted May 26, 2012
ABSTRACT
Biomedical applications of body area networks (BANs) are evolving, where taking periodic medical readings of pa-
tients via means wireless technologies at home or in the office will aid physicians to periodically supervise the p atient’s
medical status without having to see the patient. Thus, one important objective of BANs is to provide the doctor with
the medical readings that can be collected electronically without being in close proximity to the patient. This is done
through the measurement of the patient’s physiological signals via means of wearable sensors. This paper investigates
wireless BAN cooperation via actual measurements of human movement kinematics and electrocardiogram (ECG),
which are believed to prov ide p atien ts with easy h ealthcare for continuous health-monitorin g. The collected information
will be processed using specially designed software, which in turn will enable the patient to send a full medical chart to
the physician’s electronic device. In this way, physicians will have the ability to monito r their patients more efficiently.
Keywords: Body Area Networks (BANs); Electrocardiogram (ECG); Human Gait; and Movement Kinematics
1. Introduction
Body area networks (BANs) are the systems of sensors/
devices that cooperate in close proximity to a person’s
body to provide a benefit to the user. There are multiple
applications of BANs including medical and non-medical
applications. Recently, wireless technology has invaded
the medical area of BANs with a wide range of capa-
bilities. These applications typically use biomedical sen-
sors to monitor the physiological signals of patients, such
as electrocardiogram (ECG), blood oxygen level, blood
pressures, blood glucose, body weight, heart rate, oxygen
saturation, etc [1-6].
Wireless technology enables clinician s to mon itor th eir
patients’ remotely and give them timely health informa-
tion and support. Especially, in emergency situations,
real-time health parameter is crucial. According to the
American Heart Association, treatment of a patient ex-
periencing ventricular fibrillation within the first 12 mi-
nutes of cardiac arrest brings a survival rate of 48% -
75%. On the other hand, long-term health-monitoring
requires intensive and repetitive assessment that could
last for months or even years to regain the lost fu nctions,
such as in the case of rehabilitation. Thus, one of the
main challenges in such a case is being able to monitor
patients for long-times in domestic environments. BANs
provide a promising solu tion for such situation s, however
currently, BAN technology is emerging, and there are a
lot of problems to address. One of the key challenges
associated with BANs is the integration and coordinatio n
of multiple sensors with different app lications [1-6].
This paper’s aim is to investigate wireless BAN co-
operation for human movement tracking and ECG mea-
surements, which are believed to provide patients with
easy healthcare for continuous health-monitoring. In ad-
dition, taking periodic medical readings at home or in the
office will aid physicians to periodically supervise the
patient’s medical status without having to see the patient
via means wireless technologies. The collected mea-
surement data will be processed using specially desig ned
software, which will help sending a full medical record
of the patient to an electronic device in the acquisition of
the physician using wireless technology. Figure 1 shows
a schematics diagram of the implemented WBAN. We
consider a WBAN that uses wireless wearable sensors
for gait kinematics and ECG measurements. The pro-
posed WBAN is assumed to use commercially available
noninvasive wireless sensors, as will be shown in detail
in later sections.
This paper is organized as follows. Section 2 explains
gait analysis, and gives a brief overview of its types and
measurement parameters. Then, Section 3 provides a
short overview of ECG. Section 4 describes the actual
measurements. Future work is provided in Section 5, and
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