changes to the
user’s daily task and time plan.
In order to motivate the users to continue the game and
exercise plans on long term, the game provides awareness
about the user’s personal performance. This is done by
visualizing the current total score of the user and comparing it
to the average and best scores, and also show a representation
of the player with the best performance for a certain exercise.
Additionally, the game will show best practices in terms of the
gained physical activity habits which have been learned For
this purpose, we analyze sensor data and develop mechanisms
for recognition of higher-level physical activity behavior.
V. WBASN FRAMEWORK
The WBASN is a wireless network used for communication
among sensor nodes operating on the human body in order to
monitor vital body parameters and movements. A WBASN
based on low cost wireless sensor network technologies could
greatly benefit patient monitoring systems. Such system allows
easy internetworking with other devices and networks thus
offering health care workers easy access to the patient’s critical
as well as non-critical data. The WBASN based monitoring
system can also be used to monitor obese youth performance to
assist them in their daily exercises activities. This type system
could be seen as a special purpose wireless sensor network with
a number of particular system design requirements that
incorporate wearable operating sensors. Specifically, it consists
of multiple on-body sensor nodes, capable of sampling,
processing, and communicating one or more physiological
signs (such as heart activity, brain activity, movements, blood
pressure and oxygen saturation) over an extended period. Such
physiological signs are measured using different types of
sensed signals such as the electrocardiogram (ECG),
electroencephalogram (EEG), and acceleration. Also, it is used
for communication among sensor nodes operating on, or inside
the human body in order to monitor vital body parameters and
movements as well as to enable its user with quality of life,
assisted living, and entertainment purposes.
Recent improvements in WBASNs signal processing and
communications have motivated great interest in application
development of wireless technology in healthcare and
biomedical research. The WBASNs Signal Processing and
Communications (WSPC) framework consists of three major
components for real-time applications, namely sensing and
preprocessing (SAP), application-specific WBASN
communication (AWC), and data analysis and feedback (DAF)
to the patient. SAP contains a number of sensors for capturing a
raw data related to medical phenomena including blood
pressure, respiratory rate, ECG, and EEG. The AWC utilizes
application-specific wireless protocols such as ZigBee or
Bluetooth to transfer data from body sensors to the gateway,
less commonly, in case of high data rates without compression,
Wi-Fi protocol may be utilized for intensive data transmission.
Analysis of raw data including, detection and classification of
patient’s medical bio signals will occur at the DAF component,
providing strict and accurate criteria for the physician to make
recommendations that sometimes fed back to the patient to
provide proactive treatment suggestions. Figure 2 shows the
conceptual view of the WSPC framework [17]