Situation-Aware Ambient Assisted Living and Ambient Intelligence Data Integration for Efficient Eldercare - E-Healthcare Systems and Wireless Communications - page 322

Wireless Sensor Networks To avoid misunderstandings, we define eHealth

in the context of our work as follows: eHealth cov-
ers all technologies and methodologies used for
retrieving, storing and processing person-related
health data (vital parameters, medication status,
disease history) with the purpose to maintain or
improve a person's health. We see eHealth as a
key facilitator of cooperation between healthcare
providers across boundaries. eHealth enables
the collaboration of health, nursing and medical
institutions to achieve a higher quality of health-
care, more efficient processes, and better access
to services for patients and medical personnel.

Smart environments rely on sensory data from
the real world (Lewis, 2005). Therefore, sensor
networks, especially Wireless Sensor Networks
(WSNs), which enable an environmental per-
ception in a more unobtrusive way than wired
networks, play a key role in pervasive health
care. WSNs typically consist of a multitude of
cooperating sensor nodes, also called motes,
which cover a particular area. Sensor nodes are
often deployed rather spontaneously and form
an ad-hoc network by using self-organizing al-
gorithms and protocols (Karl & Willig, 2005).
Wireless sensors are available for many different
hardware and software platforms. TinyOS (Hill,
Szewczyk, Woo, Hollar, Culler, & Pister, 2000),
for example, is a component-based operating
system for wireless sensor networks, which can
be programmed using nesC (Levis, et al., 2005).
Other platforms for WSNs development are Sen-
tilla or the.NET Micro Edition. Sentilla (Sentilla
Corporation, 2009) hosts a virtual machine on its
sensor nodes, which allows to run Java programs,
while the.NET Micro Edition requires devices,
which must run a restricted version of the Com-
mon Language Runtime (CLR) to execute C#
programs (Kühner, 2008). Additional the.NET
Micro Edition provides a hardware emulator for
rapid prototyping and debugging.
Motes were originally designed to be deployed
randomly (possibly by air plane) in areas that
cannot be reached easily by individuals and to be
able to work independently for a long period of
time, for example for watching wildfires (Chac-
zko & Ahmad, 2005). As there is no permanent
power supply available in such scenarios, motes
rely on battery power. Energy consumption is
therefore a critical issue. Pervasive healthcare
faces similar problems due to wearable sensors or
sensors attached to moveable apartment interior.
The wireless sensor communication requires a

Health Data Exchange

Healthcare services are accessed by all parts
of the society. In Austria, this leads to many
health institutions and organizations responsible
for healthcare. Electronic health identification
systems, like the Austrian e-Card (SVC, 2010)
enable, in theory, people to access and allow the
transfer of their individual healthcare data. From
a technical point of view, the Austrian health sys-
tem is vastly inhomogeneous and thus efficient
electronic patient data exchange is still a vision
for the future.
With organizations using hand-written data
and others using IT-supported care documenta-
tion systems, as well as environments and sys-
tems which collect data (for example Wireless
Sensor Networks), communication breaches are
inevitable. Data that are relevant for care are often
communicated inadequately or with considerable
delay between the person's home, ambulant care,
and related institutions like hospitals and nursing
homes (Mayr & Lehner, 2008b). According to an
estimation (Ament-Rambow, 2003), 80% of the
problems occurring at organizational boundaries
arise from inadequate communication between
the system partners.