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The authors 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. They present a diagnostic quality driven mechanism for remote ECG monitoring, which enables a notation of priorities encoded into the wave segments.
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