| Conference Paper |
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| Title |
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Diagnostic Quality Driven Physiological Data Collection for Personal Healthcare
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| Abstract |
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We believe that each individual is unique, and that it
is necessary for diagnosis purpose to have a distinctive
combination of signals and data features that fits the personal
health status. It is essential to develop mechanisms for reducing
the amount of data that needs to be transferred (to mitigate the
troublesome periodically recharging of a device) while
maintaining diagnostic accuracy. Thus, the system should not
uniformly compress the collected physiological data, but
compress data in a personalized fashion that preserves the
important signal features for each individual such that it is
enough to make the diagnosis with a required high confidence
level. We present a diagnostic quality driven mechanism for
remote ECG monitoring, which enables a notation of priorities
encoded into the wave segments. The priority is specified by
the diagnosis engine or medical experts and is dynamic and
individual dependent. The system pre-processes the collected
physiological information according to the assigned priority
before delivering to the backend server. We demonstrate that
the proposed approach provides accurate inference results
while effectively compressing the data.
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| Download |
Paper: PDF file of paper
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| Information & Date |
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To appear 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Vancouver, British Columbia, Canada, August. 2008
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| Authors |
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David Jea
Rahul Balani
Ju-Lan Hsu
Dae-Ki Cho
Mario Gerla
Mani B. Srivastava
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