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delay for patients who need immediate medical
treatment. Field experiments show that our solu-
tion offers better performance than conventional
wireless protocols.
Our proposed solution provides a networking
solution to forward vital signs to the sink(s) reli-
ably while guaranteeing the QoS requirements,
which depend on the patient's triage condition
and the data type. Our solution is based on the
assumption that patients have been categorized
into three triage classes. This assumption can be
removed by integrating with data aggregation
techniques that can provide high-level assessment
of the physiological status and movement activities
using the sampled sensor readings.
Future work will be to evaluate the performance
of our solution in real medical environments such
as emergency rooms in the hospital. Moreover,
algorithms to categorize patients into “red”, “yel-
low” and “green” classes by jointly considering
different types of vital signs will also be designed
and developed. Advanced signal processing
techniques will also be researched and applied
to recover the lost data or even the original vital
sign signals at the receiver.
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for Healthcare and Assisted Living Environments
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REFERENCES
Gidlund, M., & Wang, G. (2009). Uplink sched-
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