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be done such as assessing the patient's condition
and providing efficient QoS support to medical
applications during triage.
As for assessing one patient's condition us-
ing the wireless medical sensors, it is obvious
that different vital signs or sensed data should
be jointly considered in order to make a correct
judgment. Just collecting vital signs and using
threshold values is not sufficient to issue alerts of
critical condition. For example, a hiker's health
condition may vary with time based on intensity
in climbing the terrain and weather condition
leading to changes in vital signs. Depending on
the application, correlating vital signs with the
amount of activity will help avoid false alerts.
Moreover, depending on the type and amount of
activity, the sampling frequency of vital signs can
be varied rather than keeping it fixed. For example,
when used on coma patients, the sudden abnormal
movements of comatose patient can trigger more
frequent collection of vital signs. Also, when used
in geriatric care the falling of people can be used
as trigger to collect vital signs and issue alerts.
Different assessments of patient's condition may
require different combinations of vital signs. Some
may even involve assessing the mental status of
the patient, which is hard as it requires not only
the physiological vital sign measurements. And
this calls for the research on advanced data pro-
cessing/fusion techniques.
QoS support for WBANs is a relatively un-
explored area for wireless vital sign monitoring.
Different vital signs have different QoS require-
ments. Critical vital signs (e.g., ECG data) should
be sent to the sink in less delay than non-critical
vital signs (e.g., body temperature). Moreover,
QoS support for different patients depends on the
medical condition of these patients. Vital signs
from patients who need immediate medical care
should be transmitted faster with higher reliability
than those from patients in non-critical status.
Finally, solutions for vital sign monitoring may
vary when patients are in different medical sce-
narios. For example, vital sign monitoring in the
pre-hospital environment is quite different from
that in the hospital due to lack of networking infra-
structure. The vital sign monitoring solution should
be able to adapt to different medical scenarios
when patients are moved along these scenarios
during triage. These factors, i.e., requirements of
vital signs, patient status, and influence of medi-
cal environment, have to be jointly considered to
optimize the performance of wireless vital sign
monitoring solutions. Existing solutions are still
in a preliminary stage and much research effort is
still needed. The proposed solutions should also
be evaluated using testbeds or real experiments.
Currently, these testbeds or experiments in the
medical environment are still limited in number.
After all, it is necessary to fully test and improve
these solutions before they can be used in real
medical applications.
CONCLUSION
Many solutions to avoid interference and to guar-
antee QoS requirements have been proposed for
wireless sensor networks in the past years. These
solutions, however, are not tailored for medical
applications for healthcare monitoring, where vital
signs should be forwarded to the medical team
reliably within a specified delay in order to save
lives in critical situations such as in-hospital triage.
In this chapter, we proposed, implemented,
and evaluated a novel in-network solution to
prioritize the transmission of patient vital signs
for in-hospital triage using wireless body area
networks. A cross-layer communication solution
jointly considering three functionalities - routing,
medium access control, and scheduling - was
designed to support the interference-aware priori-
tization services based on both patient condition
and healthcare data content. By providing better
wireless channels to patients who need more im-
mediate services and scheduling packets based
on the patient's condition and data requirements,
our solution offers higher reliability and lower
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